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diff --git a/_sources/content/reference_notebooks/basic_reference.ipynb b/_sources/content/reference_notebooks/basic_reference.ipynb
index bbf50d2..06c0a5d 100644
--- a/_sources/content/reference_notebooks/basic_reference.ipynb
+++ b/_sources/content/reference_notebooks/basic_reference.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "227ca660",
+   "id": "cef2afd3",
    "metadata": {},
    "source": [
     "# Basic Reference"
@@ -10,7 +10,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "7af7e861",
+   "id": "1e23050d",
    "metadata": {},
    "source": [
     "## 0. Setup\n",
@@ -20,7 +20,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "1d281d9a",
+   "id": "81a5b978",
    "metadata": {},
    "source": [
     "## 1. Overview\n",
@@ -51,7 +51,7 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "id": "8b4e1c9d",
+   "id": "b2435ca4",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -73,7 +73,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f7e8519a",
+   "id": "b782d641",
    "metadata": {},
    "source": [
     "### 2.1 Look Up Services in VO Registry\n",
@@ -84,7 +84,7 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "id": "3383f723",
+   "id": "b0bfcaf4",
    "metadata": {},
    "outputs": [
     {
@@ -128,7 +128,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ccab5881",
+   "id": "2ed33356",
    "metadata": {},
    "source": [
     "#### 2.1.1 Use different arguments/values to modify the simple example\n",
@@ -155,7 +155,7 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "id": "3b96ab71",
+   "id": "7ad3f674",
    "metadata": {},
    "outputs": [
     {
@@ -180,7 +180,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "7739b84c",
+   "id": "02544334",
    "metadata": {},
    "source": [
     "##### Filtering results\n",
@@ -191,7 +191,7 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "id": "8a4022c6",
+   "id": "f063bf6f",
    "metadata": {},
    "outputs": [
     {
@@ -210,7 +210,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "cf67e616",
+   "id": "ecfe0f77",
    "metadata": {},
    "source": [
     "##### Using astropy\n",
@@ -221,7 +221,7 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "id": "2e200ac3",
+   "id": "982dc48a",
    "metadata": {},
    "outputs": [
     {
@@ -238,7 +238,7 @@
      "data": {
       "text/html": [
        "<div><i>Table length=3</i>\n",
-       "<table id=\"table140712745793664\" class=\"table-striped table-bordered table-condensed\">\n",
+       "<table id=\"table140077415297232\" class=\"table-striped table-bordered table-condensed\">\n",
        "<thead><tr><th>short_name</th><th>res_title</th><th>res_description</th></tr></thead>\n",
        "<thead><tr><th>object</th><th>object</th><th>object</th></tr></thead>\n",
        "<tr><td>MAST CS</td><td>MAST ConeSearch</td><td>All MAST catalog holdings are available via a ConeSearch endpoint. \\nThis service provides access to all, with an optional non-standard parameter for an individual catalog to query. \\nThe available missions are listed at http://archive.stsci.edu/vo/mast_services.html, \\nand include Hubble (HST) data, Kepler, K2, IUE, HUT, EUVE, FUSE, UIT, WUPPE, BEFS, TUES, IMAPS, High Level Science Products (HLSP), Copernicus, HPOL, VLA First, XMM-OM, and SWIFT.</td></tr>\n",
@@ -272,7 +272,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f63351a0",
+   "id": "7ee85043",
    "metadata": {},
    "source": [
     "### 2.2 Cone search\n",
@@ -287,36 +287,36 @@
   {
    "cell_type": "code",
    "execution_count": 6,
-   "id": "d9640d74",
+   "id": "df937e09",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
        "<div><i>Table length=316</i>\n",
-       "<table id=\"table140713667413568\" class=\"table-striped table-bordered table-condensed\">\n",
+       "<table id=\"table140077415295216\" class=\"table-striped table-bordered table-condensed\">\n",
        "<thead><tr><th>ObjID</th><th>Zone</th><th>SeqNo</th><th>RA</th><th>DEC</th><th>pmRA</th><th>pmDEC</th><th>e_pmRA</th><th>e_pmDEC</th><th>e_RA</th><th>e_DEC</th><th>Epoch</th><th>B1Mag</th><th>R1s_g</th><th>B2Mag</th><th>B2s_g</th><th>R2Mag</th><th>R2s_g</th><th>NMag</th><th>mag</th><th>B1s_g</th><th>R1Mag</th><th>distance</th></tr></thead>\n",
        "<thead><tr><th></th><th></th><th></th><th>deg</th><th>deg</th><th>mas / yr</th><th>mas / yr</th><th>mas / yr</th><th>mas / yr</th><th>arcsec</th><th>arcsec</th><th>yr</th><th>mag</th><th></th><th>mag</th><th></th><th>mag</th><th></th><th>mag</th><th>mag</th><th></th><th>mag</th><th>arcsec</th></tr></thead>\n",
        "<thead><tr><th>int64</th><th>int32</th><th>int32</th><th>float64</th><th>float64</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>int32</th><th>float32</th><th>int32</th><th>float32</th><th>int32</th><th>float32</th><th>float32</th><th>int32</th><th>float32</th><th>float32</th></tr></thead>\n",
-       "<tr><td>5888400445251</td><td>1371</td><td>282435</td><td>202.472919444444</td><td>47.1954444444444</td><td>2.081668e-13</td><td>2.081668e-13</td><td>0.0</td><td>0.0</td><td>999.0</td><td>999.0</td><td>1981.8</td><td>-999999500.0</td><td>1</td><td>9.4</td><td>9</td><td>-999999500.0</td><td>0</td><td>7.86</td><td>-999999500.0</td><td>0</td><td>8.98</td><td>0.13680981</td></tr>\n",
-       "<tr><td>5892695420475</td><td>1372</td><td>290363</td><td>202.494625</td><td>47.2065472222222</td><td>2.081668e-13</td><td>2.081668e-13</td><td>0.0</td><td>0.0</td><td>332.0</td><td>999.0</td><td>1956.2</td><td>20.13</td><td>3</td><td>-999999500.0</td><td>0</td><td>-999999500.0</td><td>0</td><td>-999999500.0</td><td>-999999500.0</td><td>4</td><td>15.79</td><td>1.225397</td></tr>\n",
-       "<tr><td>5892695420458</td><td>1372</td><td>290346</td><td>202.436875</td><td>47.2094416666667</td><td>2.081668e-13</td><td>2.081668e-13</td><td>0.0</td><td>0.0</td><td>999.0</td><td>359.0</td><td>1976.2</td><td>-999999500.0</td><td>1</td><td>-999999500.0</td><td>0</td><td>-999999500.0</td><td>0</td><td>10.89</td><td>-999999500.0</td><td>0</td><td>13.27</td><td>1.5814886</td></tr>\n",
-       "<tr><td>5892695420468</td><td>1372</td><td>290356</td><td>202.469830555556</td><td>47.2232805555556</td><td>2.081668e-13</td><td>2.081668e-13</td><td>0.0</td><td>0.0</td><td>560.0</td><td>934.0</td><td>1976.2</td><td>-999999500.0</td><td>3</td><td>-999999500.0</td><td>0</td><td>-999999500.0</td><td>0</td><td>18.4</td><td>-999999500.0</td><td>0</td><td>17.78</td><td>1.6813676</td></tr>\n",
-       "<tr><td>5888400445256</td><td>1371</td><td>282440</td><td>202.480638888889</td><td>47.1682194444444</td><td>-20.0</td><td>-6.0</td><td>5.0</td><td>5.0</td><td>205.0</td><td>201.0</td><td>1969.5</td><td>12.79</td><td>8</td><td>-999999500.0</td><td>0</td><td>-999999500.0</td><td>0</td><td>14.87</td><td>-999999500.0</td><td>1</td><td>15.4</td><td>1.6839039</td></tr>\n",
-       "<tr><td>5892695420469</td><td>1372</td><td>290357</td><td>202.4706</td><td>47.2235555555556</td><td>2.081668e-13</td><td>2.081668e-13</td><td>0.0</td><td>0.0</td><td>709.0</td><td>130.0</td><td>1956.2</td><td>15.89</td><td>3</td><td>-999999500.0</td><td>0</td><td>-999999500.0</td><td>0</td><td>-999999500.0</td><td>-999999500.0</td><td>1</td><td>17.68</td><td>1.6983492</td></tr>\n",
-       "<tr><td>5892695420470</td><td>1372</td><td>290358</td><td>202.474338888889</td><td>47.2264416666667</td><td>2.081668e-13</td><td>2.081668e-13</td><td>0.0</td><td>0.0</td><td>200.0</td><td>490.0</td><td>1956.2</td><td>13.49</td><td>4</td><td>-999999500.0</td><td>0</td><td>-999999500.0</td><td>0</td><td>-999999500.0</td><td>-999999500.0</td><td>1</td><td>18.74</td><td>1.8810501</td></tr>\n",
-       "<tr><td>5888400445204</td><td>1371</td><td>282388</td><td>202.423558333333</td><td>47.1977666666667</td><td>2.081668e-13</td><td>2.081668e-13</td><td>0.0</td><td>0.0</td><td>466.0</td><td>480.0</td><td>1969.5</td><td>15.66</td><td>8</td><td>-999999500.0</td><td>0</td><td>-999999500.0</td><td>0</td><td>14.97</td><td>-999999500.0</td><td>1</td><td>15.22</td><td>1.8820878</td></tr>\n",
-       "<tr><td>5888400445231</td><td>1371</td><td>282415</td><td>202.459627777778</td><td>47.1625777777778</td><td>2.081668e-13</td><td>2.081668e-13</td><td>0.0</td><td>0.0</td><td>945.0</td><td>999.0</td><td>1976.2</td><td>-999999500.0</td><td>1</td><td>-999999500.0</td><td>0</td><td>-999999500.0</td><td>0</td><td>17.22</td><td>-999999500.0</td><td>0</td><td>10.02</td><td>2.0023563</td></tr>\n",
+       "<tr><td>5888400445251</td><td>1371</td><td>282435</td><td>202.472919444444</td><td>47.1954444444444</td><td>2.081668e-13</td><td>2.081668e-13</td><td>0.0</td><td>0.0</td><td>999.0</td><td>999.0</td><td>1981.8</td><td>-999999500.0</td><td>1</td><td>9.4</td><td>9</td><td>-999999500.0</td><td>0</td><td>7.86</td><td>-999999500.0</td><td>0</td><td>8.98</td><td>0.13680966</td></tr>\n",
+       "<tr><td>5892695420475</td><td>1372</td><td>290363</td><td>202.494625</td><td>47.2065472222222</td><td>2.081668e-13</td><td>2.081668e-13</td><td>0.0</td><td>0.0</td><td>332.0</td><td>999.0</td><td>1956.2</td><td>20.13</td><td>3</td><td>-999999500.0</td><td>0</td><td>-999999500.0</td><td>0</td><td>-999999500.0</td><td>-999999500.0</td><td>4</td><td>15.79</td><td>1.2253959</td></tr>\n",
+       "<tr><td>5892695420458</td><td>1372</td><td>290346</td><td>202.436875</td><td>47.2094416666667</td><td>2.081668e-13</td><td>2.081668e-13</td><td>0.0</td><td>0.0</td><td>999.0</td><td>359.0</td><td>1976.2</td><td>-999999500.0</td><td>1</td><td>-999999500.0</td><td>0</td><td>-999999500.0</td><td>0</td><td>10.89</td><td>-999999500.0</td><td>0</td><td>13.27</td><td>1.5814877</td></tr>\n",
+       "<tr><td>5892695420468</td><td>1372</td><td>290356</td><td>202.469830555556</td><td>47.2232805555556</td><td>2.081668e-13</td><td>2.081668e-13</td><td>0.0</td><td>0.0</td><td>560.0</td><td>934.0</td><td>1976.2</td><td>-999999500.0</td><td>3</td><td>-999999500.0</td><td>0</td><td>-999999500.0</td><td>0</td><td>18.4</td><td>-999999500.0</td><td>0</td><td>17.78</td><td>1.6813658</td></tr>\n",
+       "<tr><td>5888400445256</td><td>1371</td><td>282440</td><td>202.480638888889</td><td>47.1682194444444</td><td>-20.0</td><td>-6.0</td><td>5.0</td><td>5.0</td><td>205.0</td><td>201.0</td><td>1969.5</td><td>12.79</td><td>8</td><td>-999999500.0</td><td>0</td><td>-999999500.0</td><td>0</td><td>14.87</td><td>-999999500.0</td><td>1</td><td>15.4</td><td>1.6839056</td></tr>\n",
+       "<tr><td>5892695420469</td><td>1372</td><td>290357</td><td>202.4706</td><td>47.2235555555556</td><td>2.081668e-13</td><td>2.081668e-13</td><td>0.0</td><td>0.0</td><td>709.0</td><td>130.0</td><td>1956.2</td><td>15.89</td><td>3</td><td>-999999500.0</td><td>0</td><td>-999999500.0</td><td>0</td><td>-999999500.0</td><td>-999999500.0</td><td>1</td><td>17.68</td><td>1.6983474</td></tr>\n",
+       "<tr><td>5892695420470</td><td>1372</td><td>290358</td><td>202.474338888889</td><td>47.2264416666667</td><td>2.081668e-13</td><td>2.081668e-13</td><td>0.0</td><td>0.0</td><td>200.0</td><td>490.0</td><td>1956.2</td><td>13.49</td><td>4</td><td>-999999500.0</td><td>0</td><td>-999999500.0</td><td>0</td><td>-999999500.0</td><td>-999999500.0</td><td>1</td><td>18.74</td><td>1.8810483</td></tr>\n",
+       "<tr><td>5888400445204</td><td>1371</td><td>282388</td><td>202.423558333333</td><td>47.1977666666667</td><td>2.081668e-13</td><td>2.081668e-13</td><td>0.0</td><td>0.0</td><td>466.0</td><td>480.0</td><td>1969.5</td><td>15.66</td><td>8</td><td>-999999500.0</td><td>0</td><td>-999999500.0</td><td>0</td><td>14.97</td><td>-999999500.0</td><td>1</td><td>15.22</td><td>1.8820877</td></tr>\n",
+       "<tr><td>5888400445231</td><td>1371</td><td>282415</td><td>202.459627777778</td><td>47.1625777777778</td><td>2.081668e-13</td><td>2.081668e-13</td><td>0.0</td><td>0.0</td><td>945.0</td><td>999.0</td><td>1976.2</td><td>-999999500.0</td><td>1</td><td>-999999500.0</td><td>0</td><td>-999999500.0</td><td>0</td><td>17.22</td><td>-999999500.0</td><td>0</td><td>10.02</td><td>2.0023582</td></tr>\n",
        "<tr><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td></tr>\n",
-       "<tr><td>5888400445151</td><td>1371</td><td>282335</td><td>202.351194444444</td><td>47.1387361111111</td><td>4.0</td><td>12.0</td><td>0.0</td><td>12.0</td><td>23.0</td><td>324.0</td><td>1981.2</td><td>20.72</td><td>0</td><td>20.92</td><td>7</td><td>19.53</td><td>3</td><td>-999999500.0</td><td>19.53</td><td>1</td><td>-999999500.0</td><td>5.9008446</td></tr>\n",
-       "<tr><td>5888400445298</td><td>1371</td><td>282482</td><td>202.515788888889</td><td>47.1018111111111</td><td>2.081668e-13</td><td>2.081668e-13</td><td>0.0</td><td>0.0</td><td>394.0</td><td>190.0</td><td>1975.3</td><td>20.84</td><td>0</td><td>-999999500.0</td><td>0</td><td>17.89</td><td>1</td><td>-999999500.0</td><td>17.89</td><td>2</td><td>-999999500.0</td><td>5.915472</td></tr>\n",
-       "<tr><td>5888400445142</td><td>1371</td><td>282326</td><td>202.342727777778</td><td>47.1468222222222</td><td>2.081668e-13</td><td>2.081668e-13</td><td>0.0</td><td>0.0</td><td>999.0</td><td>999.0</td><td>1995.6</td><td>-999999500.0</td><td>0</td><td>21.08</td><td>4</td><td>20.49</td><td>5</td><td>17.92</td><td>20.49</td><td>0</td><td>-999999500.0</td><td>5.934256</td></tr>\n",
-       "<tr><td>5888400445376</td><td>1371</td><td>282560</td><td>202.609608333333</td><td>47.167975</td><td>2.081668e-13</td><td>2.081668e-13</td><td>0.0</td><td>0.0</td><td>999.0</td><td>999.0</td><td>1996.8</td><td>-999999500.0</td><td>0</td><td>-999999500.0</td><td>0</td><td>20.82</td><td>3</td><td>19.06</td><td>20.82</td><td>0</td><td>-999999500.0</td><td>5.9406395</td></tr>\n",
-       "<tr><td>5888400445150</td><td>1371</td><td>282334</td><td>202.350063888889</td><td>47.1384194444444</td><td>2.081668e-13</td><td>2.081668e-13</td><td>0.0</td><td>0.0</td><td>999.0</td><td>999.0</td><td>1975.3</td><td>-999999500.0</td><td>3</td><td>20.53</td><td>1</td><td>-999999500.0</td><td>0</td><td>-999999500.0</td><td>-999999500.0</td><td>0</td><td>19.62</td><td>5.9495263</td></tr>\n",
-       "<tr><td>5888400445175</td><td>1371</td><td>282359</td><td>202.374458333333</td><td>47.1198861111111</td><td>-54.0</td><td>296.0</td><td>13.0</td><td>13.0</td><td>352.0</td><td>352.0</td><td>1981.7</td><td>-999999500.0</td><td>3</td><td>19.74</td><td>3</td><td>20.36</td><td>1</td><td>-999999500.0</td><td>20.36</td><td>0</td><td>19.55</td><td>5.9591174</td></tr>\n",
-       "<tr><td>5892695420507</td><td>1372</td><td>290395</td><td>202.586555555556</td><td>47.2552055555556</td><td>2.081668e-13</td><td>2.081668e-13</td><td>0.0</td><td>0.0</td><td>783.0</td><td>999.0</td><td>1976.2</td><td>20.84</td><td>0</td><td>-999999500.0</td><td>0</td><td>-999999500.0</td><td>0</td><td>19.2</td><td>-999999500.0</td><td>2</td><td>-999999500.0</td><td>5.9714193</td></tr>\n",
-       "<tr><td>5888400445176</td><td>1371</td><td>282360</td><td>202.374952777778</td><td>47.119275</td><td>2.081668e-13</td><td>2.081668e-13</td><td>0.0</td><td>0.0</td><td>200.0</td><td>76.0</td><td>1979.2</td><td>20.84</td><td>2</td><td>19.89</td><td>2</td><td>18.84</td><td>10</td><td>18.56</td><td>18.84</td><td>9</td><td>19.42</td><td>5.9739494</td></tr>\n",
-       "<tr><td>5888400445139</td><td>1371</td><td>282323</td><td>202.340863888889</td><td>47.1474416666667</td><td>-34.0</td><td>-26.0</td><td>13.0</td><td>4.0</td><td>313.0</td><td>111.0</td><td>1985.0</td><td>-999999500.0</td><td>3</td><td>19.1</td><td>9</td><td>18.0</td><td>2</td><td>17.74</td><td>18.0</td><td>0</td><td>19.6</td><td>5.982718</td></tr>\n",
+       "<tr><td>5888400445151</td><td>1371</td><td>282335</td><td>202.351194444444</td><td>47.1387361111111</td><td>4.0</td><td>12.0</td><td>0.0</td><td>12.0</td><td>23.0</td><td>324.0</td><td>1981.2</td><td>20.72</td><td>0</td><td>20.92</td><td>7</td><td>19.53</td><td>3</td><td>-999999500.0</td><td>19.53</td><td>1</td><td>-999999500.0</td><td>5.9008455</td></tr>\n",
+       "<tr><td>5888400445298</td><td>1371</td><td>282482</td><td>202.515788888889</td><td>47.1018111111111</td><td>2.081668e-13</td><td>2.081668e-13</td><td>0.0</td><td>0.0</td><td>394.0</td><td>190.0</td><td>1975.3</td><td>20.84</td><td>0</td><td>-999999500.0</td><td>0</td><td>17.89</td><td>1</td><td>-999999500.0</td><td>17.89</td><td>2</td><td>-999999500.0</td><td>5.915474</td></tr>\n",
+       "<tr><td>5888400445142</td><td>1371</td><td>282326</td><td>202.342727777778</td><td>47.1468222222222</td><td>2.081668e-13</td><td>2.081668e-13</td><td>0.0</td><td>0.0</td><td>999.0</td><td>999.0</td><td>1995.6</td><td>-999999500.0</td><td>0</td><td>21.08</td><td>4</td><td>20.49</td><td>5</td><td>17.92</td><td>20.49</td><td>0</td><td>-999999500.0</td><td>5.934257</td></tr>\n",
+       "<tr><td>5888400445376</td><td>1371</td><td>282560</td><td>202.609608333333</td><td>47.167975</td><td>2.081668e-13</td><td>2.081668e-13</td><td>0.0</td><td>0.0</td><td>999.0</td><td>999.0</td><td>1996.8</td><td>-999999500.0</td><td>0</td><td>-999999500.0</td><td>0</td><td>20.82</td><td>3</td><td>19.06</td><td>20.82</td><td>0</td><td>-999999500.0</td><td>5.9406404</td></tr>\n",
+       "<tr><td>5888400445150</td><td>1371</td><td>282334</td><td>202.350063888889</td><td>47.1384194444444</td><td>2.081668e-13</td><td>2.081668e-13</td><td>0.0</td><td>0.0</td><td>999.0</td><td>999.0</td><td>1975.3</td><td>-999999500.0</td><td>3</td><td>20.53</td><td>1</td><td>-999999500.0</td><td>0</td><td>-999999500.0</td><td>-999999500.0</td><td>0</td><td>19.62</td><td>5.9495273</td></tr>\n",
+       "<tr><td>5888400445175</td><td>1371</td><td>282359</td><td>202.374458333333</td><td>47.1198861111111</td><td>-54.0</td><td>296.0</td><td>13.0</td><td>13.0</td><td>352.0</td><td>352.0</td><td>1981.7</td><td>-999999500.0</td><td>3</td><td>19.74</td><td>3</td><td>20.36</td><td>1</td><td>-999999500.0</td><td>20.36</td><td>0</td><td>19.55</td><td>5.959119</td></tr>\n",
+       "<tr><td>5892695420507</td><td>1372</td><td>290395</td><td>202.586555555556</td><td>47.2552055555556</td><td>2.081668e-13</td><td>2.081668e-13</td><td>0.0</td><td>0.0</td><td>783.0</td><td>999.0</td><td>1976.2</td><td>20.84</td><td>0</td><td>-999999500.0</td><td>0</td><td>-999999500.0</td><td>0</td><td>19.2</td><td>-999999500.0</td><td>2</td><td>-999999500.0</td><td>5.971418</td></tr>\n",
+       "<tr><td>5888400445176</td><td>1371</td><td>282360</td><td>202.374952777778</td><td>47.119275</td><td>2.081668e-13</td><td>2.081668e-13</td><td>0.0</td><td>0.0</td><td>200.0</td><td>76.0</td><td>1979.2</td><td>20.84</td><td>2</td><td>19.89</td><td>2</td><td>18.84</td><td>10</td><td>18.56</td><td>18.84</td><td>9</td><td>19.42</td><td>5.973951</td></tr>\n",
+       "<tr><td>5888400445139</td><td>1371</td><td>282323</td><td>202.340863888889</td><td>47.1474416666667</td><td>-34.0</td><td>-26.0</td><td>13.0</td><td>4.0</td><td>313.0</td><td>111.0</td><td>1985.0</td><td>-999999500.0</td><td>3</td><td>19.1</td><td>9</td><td>18.0</td><td>2</td><td>17.74</td><td>18.0</td><td>0</td><td>19.6</td><td>5.982719</td></tr>\n",
        "</table></div>"
       ],
       "text/plain": [
@@ -325,25 +325,25 @@
        "                                 deg        ...           mag        arcsec  \n",
        "    int64     int32 int32      float64      ... int32   float32     float32  \n",
        "------------- ----- ------ ---------------- ... ----- ------------ ----------\n",
-       "5888400445251  1371 282435 202.472919444444 ...     0         8.98 0.13680981\n",
-       "5892695420475  1372 290363       202.494625 ...     4        15.79   1.225397\n",
-       "5892695420458  1372 290346       202.436875 ...     0        13.27  1.5814886\n",
-       "5892695420468  1372 290356 202.469830555556 ...     0        17.78  1.6813676\n",
-       "5888400445256  1371 282440 202.480638888889 ...     1         15.4  1.6839039\n",
-       "5892695420469  1372 290357         202.4706 ...     1        17.68  1.6983492\n",
-       "5892695420470  1372 290358 202.474338888889 ...     1        18.74  1.8810501\n",
-       "5888400445204  1371 282388 202.423558333333 ...     1        15.22  1.8820878\n",
-       "5888400445231  1371 282415 202.459627777778 ...     0        10.02  2.0023563\n",
+       "5888400445251  1371 282435 202.472919444444 ...     0         8.98 0.13680966\n",
+       "5892695420475  1372 290363       202.494625 ...     4        15.79  1.2253959\n",
+       "5892695420458  1372 290346       202.436875 ...     0        13.27  1.5814877\n",
+       "5892695420468  1372 290356 202.469830555556 ...     0        17.78  1.6813658\n",
+       "5888400445256  1371 282440 202.480638888889 ...     1         15.4  1.6839056\n",
+       "5892695420469  1372 290357         202.4706 ...     1        17.68  1.6983474\n",
+       "5892695420470  1372 290358 202.474338888889 ...     1        18.74  1.8810483\n",
+       "5888400445204  1371 282388 202.423558333333 ...     1        15.22  1.8820877\n",
+       "5888400445231  1371 282415 202.459627777778 ...     0        10.02  2.0023582\n",
        "          ...   ...    ...              ... ...   ...          ...        ...\n",
-       "5888400445151  1371 282335 202.351194444444 ...     1 -999999500.0  5.9008446\n",
-       "5888400445298  1371 282482 202.515788888889 ...     2 -999999500.0   5.915472\n",
-       "5888400445142  1371 282326 202.342727777778 ...     0 -999999500.0   5.934256\n",
-       "5888400445376  1371 282560 202.609608333333 ...     0 -999999500.0  5.9406395\n",
-       "5888400445150  1371 282334 202.350063888889 ...     0        19.62  5.9495263\n",
-       "5888400445175  1371 282359 202.374458333333 ...     0        19.55  5.9591174\n",
-       "5892695420507  1372 290395 202.586555555556 ...     2 -999999500.0  5.9714193\n",
-       "5888400445176  1371 282360 202.374952777778 ...     9        19.42  5.9739494\n",
-       "5888400445139  1371 282323 202.340863888889 ...     0         19.6   5.982718"
+       "5888400445151  1371 282335 202.351194444444 ...     1 -999999500.0  5.9008455\n",
+       "5888400445298  1371 282482 202.515788888889 ...     2 -999999500.0   5.915474\n",
+       "5888400445142  1371 282326 202.342727777778 ...     0 -999999500.0   5.934257\n",
+       "5888400445376  1371 282560 202.609608333333 ...     0 -999999500.0  5.9406404\n",
+       "5888400445150  1371 282334 202.350063888889 ...     0        19.62  5.9495273\n",
+       "5888400445175  1371 282359 202.374458333333 ...     0        19.55   5.959119\n",
+       "5892695420507  1372 290395 202.586555555556 ...     2 -999999500.0   5.971418\n",
+       "5888400445176  1371 282360 202.374952777778 ...     9        19.42   5.973951\n",
+       "5888400445139  1371 282323 202.340863888889 ...     0         19.6   5.982719"
       ]
      },
      "execution_count": 6,
@@ -361,7 +361,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "36445d08",
+   "id": "f5da4d8e",
    "metadata": {},
    "source": [
     "### 2.3 Image search\n",
@@ -374,14 +374,14 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "id": "a6824eb1",
+   "id": "0dd87569",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
        "<div><i>Table length=3</i>\n",
-       "<table id=\"table140713667418224\" class=\"table-striped table-bordered table-condensed\">\n",
+       "<table id=\"table140077411268928\" class=\"table-striped table-bordered table-condensed\">\n",
        "<thead><tr><th>ivoid</th><th>short_name</th><th>res_title</th></tr></thead>\n",
        "<thead><tr><th>object</th><th>object</th><th>object</th></tr></thead>\n",
        "<tr><td>ivo://archive.stsci.edu/sia/galex</td><td>GALEX</td><td>Galaxy Evolution Explorer (GALEX)</td></tr>\n",
@@ -411,7 +411,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f47757b2",
+   "id": "6aeca16e",
    "metadata": {},
    "source": [
     "#### Search one of the services\n",
@@ -426,14 +426,14 @@
   {
    "cell_type": "code",
    "execution_count": 8,
-   "id": "88d0a6e1",
+   "id": "6aa9eedc",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
        "<div><i>Table length=2</i>\n",
-       "<table id=\"table140712742371824\" class=\"table-striped table-bordered table-condensed\">\n",
+       "<table id=\"table140077413138592\" class=\"table-striped table-bordered table-condensed\">\n",
        "<thead><tr><th>filename</th><th>id</th><th>ra_j2000</th><th>dec_j2000</th><th>url</th><th>filesize</th><th>mjdmean</th><th>naxes</th><th>naxis</th><th>scale</th><th>cd</th><th>format</th><th>ref_frame</th><th>equinox</th><th>coord_projection</th><th>crpix</th><th>crval</th><th>ctype</th><th>bandpass_id</th><th>bandpass_refvalue</th><th>bandpass_unit</th><th>bandpass_hilimit</th><th>bandpass_lolimit</th><th>processing</th><th>project</th><th>preview</th><th>representative</th><th>object_id</th></tr></thead>\n",
        "<thead><tr><th></th><th></th><th>deg</th><th>deg</th><th></th><th>byte</th><th>d</th><th></th><th>pix</th><th>deg / pix</th><th>deg / pix</th><th></th><th></th><th>yr</th><th></th><th>pix</th><th>pix</th><th></th><th></th><th>m</th><th>m</th><th>m</th><th>m</th><th></th><th></th><th></th><th></th><th></th></tr></thead>\n",
        "<thead><tr><th>object</th><th>object</th><th>float64</th><th>float64</th><th>object</th><th>int32</th><th>float64</th><th>int32</th><th>object</th><th>object</th><th>object</th><th>object</th><th>object</th><th>float32</th><th>str3</th><th>object</th><th>object</th><th>object</th><th>object</th><th>float64</th><th>object</th><th>float64</th><th>float64</th><th>object</th><th>object</th><th>object</th><th>object</th><th>object</th></tr></thead>\n",
@@ -466,7 +466,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "700fd37b",
+   "id": "1c4f44d9",
    "metadata": {},
    "source": [
     "#### Download an image\n",
@@ -479,7 +479,7 @@
   {
    "cell_type": "code",
    "execution_count": 9,
-   "id": "c25ae42e",
+   "id": "0ae21aee",
    "metadata": {},
    "outputs": [
     {
@@ -492,7 +492,7 @@
     {
      "data": {
       "text/plain": [
-       "'/tmp/astropy-download-1819-k031mz4l'"
+       "'/tmp/astropy-download-1806-77t04s8i'"
       ]
      },
      "execution_count": 9,
@@ -508,7 +508,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "84cf59cf",
+   "id": "74182929",
    "metadata": {},
    "source": [
     "### 2.4 Spectral search\n",
@@ -525,7 +525,7 @@
   {
    "cell_type": "code",
    "execution_count": 10,
-   "id": "7816c027",
+   "id": "c3c6c6a2",
    "metadata": {},
    "outputs": [
     {
@@ -538,7 +538,7 @@
     {
      "data": {
       "text/plain": [
-       "'/tmp/astropy-download-1819-lvood7_u'"
+       "'/tmp/astropy-download-1806-fisfrsot'"
       ]
      },
      "execution_count": 10,
@@ -562,7 +562,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "749b6458",
+   "id": "e099f5da",
    "metadata": {},
    "source": [
     "### 2.5 Table search\n",
@@ -573,7 +573,7 @@
   {
    "cell_type": "code",
    "execution_count": 11,
-   "id": "99e05233",
+   "id": "09eeba72",
    "metadata": {
     "tags": [
      "output_scroll"
@@ -1495,19 +1495,19 @@
       "uitmaster                      - Ultraviolet Imaging Telescope Master Catalog\n",
       "ulxngcat                       - Ultraluminous X-Ray Sources in Nearby Galaxies Catalog\n",
       "ulxrbcat                       - Ultraluminous X-Ray Sources in External Galaxies Catalog\n",
-      "upprscoxmm                     - Upper Sco XMM-Newton X-Ray Point Source Catalog\n",
-      "uvotbscat                      - UVOT Bright Star Catalog\n",
-      "uvqs                           - UV-Bright Quasar Survey (UVQS) DR1 Catalog\n",
-      "uzc                            - Updated Zwicky Catalog\n",
-      "vela5b                         - Vela 5B All-Sky Monitor Lightcurves\n",
-      "verimaster                     - VERITAS Source Catalog\n",
-      "veroncat                       - Veron Catalog of Quasars & AGN, 13th Edition\n"
+      "upprscoxmm                     - Upper Sco XMM-Newton X-Ray Point Source Catalog\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
+      "uvotbscat                      - UVOT Bright Star Catalog\n",
+      "uvqs                           - UV-Bright Quasar Survey (UVQS) DR1 Catalog\n",
+      "uzc                            - Updated Zwicky Catalog\n",
+      "vela5b                         - Vela 5B All-Sky Monitor Lightcurves\n",
+      "verimaster                     - VERITAS Source Catalog\n",
+      "veroncat                       - Veron Catalog of Quasars & AGN, 13th Edition\n",
       "vla23901p4                     - VLA A2390 Cluster of Galaxies 1.4-GHz Source Catalog\n",
       "vla3701p4                      - VLA A370 Cluster of Galaxies 1.4-GHz Source Catalog\n",
       "vla74mhzdp                     - VLA 74-MHz Deep High-Resolution Survey Source Catalog\n",
@@ -1655,7 +1655,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "dec16cff",
+   "id": "5e92c12c",
    "metadata": {},
    "source": [
     "#### Column Information\n",
@@ -1666,7 +1666,7 @@
   {
    "cell_type": "code",
    "execution_count": 12,
-   "id": "2baa26c8",
+   "id": "9dfcc876",
    "metadata": {},
    "outputs": [
     {
@@ -1712,7 +1712,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "3a6fb963",
+   "id": "fe0ae2e3",
    "metadata": {},
    "source": [
     "#### Perform a Query\n",
@@ -1723,14 +1723,14 @@
   {
    "cell_type": "code",
    "execution_count": 13,
-   "id": "19bd08ce",
+   "id": "67ccf9be",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
        "<div><i>Table length=13</i>\n",
-       "<table id=\"table140712743133216\" class=\"table-striped table-bordered table-condensed\">\n",
+       "<table id=\"table140078085934624\" class=\"table-striped table-bordered table-condensed\">\n",
        "<thead><tr><th>ra</th><th>dec</th><th>radial_velocity</th><th>radial_velocity_error</th><th>bmag</th><th>morph_type</th></tr></thead>\n",
        "<thead><tr><th>deg</th><th>deg</th><th>km / s</th><th>km / s</th><th></th><th></th></tr></thead>\n",
        "<thead><tr><th>float64</th><th>float64</th><th>int32</th><th>int16</th><th>float32</th><th>int16</th></tr></thead>\n",
@@ -1788,7 +1788,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "eba6a2c6",
+   "id": "2773682f",
    "metadata": {},
    "source": [
     "## 3. Astroquery\n",
@@ -1818,14 +1818,14 @@
   {
    "cell_type": "code",
    "execution_count": 14,
-   "id": "ebf7d7d2",
+   "id": "d2aecf8d",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
        "<div><i>Table length=41</i>\n",
-       "<table id=\"table140712741862272\" class=\"table-striped table-bordered table-condensed\">\n",
+       "<table id=\"table140077415298768\" class=\"table-striped table-bordered table-condensed\">\n",
        "<thead><tr><th>No.</th><th>Object Name</th><th>RA</th><th>DEC</th><th>Type</th><th>Velocity</th><th>Redshift</th><th>Redshift Flag</th><th>Magnitude and Filter</th><th>Separation</th><th>References</th><th>Notes</th><th>Photometry Points</th><th>Positions</th><th>Redshift Points</th><th>Diameter Points</th><th>Associations</th></tr></thead>\n",
        "<thead><tr><th></th><th></th><th>degrees</th><th>degrees</th><th></th><th>km / s</th><th></th><th></th><th></th><th>arcmin</th><th></th><th></th><th></th><th></th><th></th><th></th><th></th></tr></thead>\n",
        "<thead><tr><th>int32</th><th>str30</th><th>float64</th><th>float64</th><th>object</th><th>float64</th><th>float64</th><th>object</th><th>object</th><th>float64</th><th>int32</th><th>int32</th><th>int32</th><th>int32</th><th>int32</th><th>int32</th><th>int32</th></tr></thead>\n",
diff --git a/_sources/content/reference_notebooks/catalog_queries.ipynb b/_sources/content/reference_notebooks/catalog_queries.ipynb
index 487dfbb..50f5826 100644
--- a/_sources/content/reference_notebooks/catalog_queries.ipynb
+++ b/_sources/content/reference_notebooks/catalog_queries.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "6f18de94",
+   "id": "580eec82",
    "metadata": {},
    "source": [
     "# Catalog Queries\n",
@@ -29,7 +29,7 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "id": "10ccace7",
+   "id": "64b664b6",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -55,7 +55,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "3b07463b",
+   "id": "a65ec6d2",
    "metadata": {},
    "source": [
     "## 1. Simple cone search"
@@ -63,7 +63,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "6e5db69b",
+   "id": "8c7242ae",
    "metadata": {},
    "source": [
     "Starting with a single simple source first:"
@@ -72,7 +72,7 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "id": "bd66e45f",
+   "id": "98f250fe",
    "metadata": {},
    "outputs": [
     {
@@ -80,7 +80,7 @@
      "output_type": "stream",
      "text": [
       "<SkyCoord (ICRS): (ra, dec) in deg\n",
-      "    (202.469575, 47.1952583)>\n"
+      "    (202.469575, 47.19525833)>\n"
      ]
     }
    ],
@@ -91,7 +91,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "5603c673",
+   "id": "14b1844f",
    "metadata": {},
    "source": [
     "Below, we go through the exercise of how we can figure out the most relevant table. But for now, let's assume that we know that we want the CFA redshift catalog refered to as 'zcat'. VO services are listed in a central Registry that can be searched through a [web interface](http://vao.stsci.edu/keyword-search/) or using PyVO's `regsearch`.  We use the registry to find the corresponding cone service and then submit our cone search.\n",
@@ -109,14 +109,14 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "id": "be414610",
+   "id": "100eea62",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
        "<div><i>Table length=6</i>\n",
-       "<table id=\"table140714640481136\" class=\"table-striped table-bordered table-condensed\">\n",
+       "<table id=\"table139853117532352\" class=\"table-striped table-bordered table-condensed\">\n",
        "<thead><tr><th>ivoid</th><th>short_name</th><th>res_title</th></tr></thead>\n",
        "<thead><tr><th>object</th><th>object</th><th>object</th></tr></thead>\n",
        "<tr><td>ivo://cds.vizier/j/mnras/339/652</td><td>J/MNRAS/339/652</td><td>The FLASH Redshift Survey</td></tr>\n",
@@ -152,7 +152,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "9199b029",
+   "id": "5c9e6574",
    "metadata": {},
    "source": [
     "Supposing that we want the table with the short_name CFAZ, and we want to retrieve the data for all sources within an arcminute of our specified location:"
@@ -161,14 +161,14 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "id": "63e110ea",
+   "id": "b39e6b62",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
        "<div><i>Table length=2</i>\n",
-       "<table id=\"table140714641170656\" class=\"table-striped table-bordered table-condensed\">\n",
+       "<table id=\"table139853116398688\" class=\"table-striped table-bordered table-condensed\">\n",
        "<thead><tr><th>__row</th><th>name</th><th>ra</th><th>dec</th><th>bmag</th><th>radial_velocity</th><th>radial_velocity_error</th><th>redshift</th><th>class</th><th>Search_Offset</th></tr></thead>\n",
        "<thead><tr><th></th><th></th><th>deg</th><th>deg</th><th></th><th>km / s</th><th>km / s</th><th></th><th></th><th></th></tr></thead>\n",
        "<thead><tr><th>object</th><th>object</th><th>float64</th><th>float64</th><th>float32</th><th>int32</th><th>int16</th><th>float64</th><th>int16</th><th>float64</th></tr></thead>\n",
@@ -203,7 +203,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "23bd3163",
+   "id": "20d049bd",
    "metadata": {},
    "source": [
     "The SCS is quite straightforward and returns all of the columns of the given table (which can be anything) for the sources in the region queried."
@@ -211,7 +211,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "6dca5706",
+   "id": "401fc739",
    "metadata": {},
    "source": [
     "## 2. Table Access Protocol queries\n",
@@ -221,7 +221,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "556713a8",
+   "id": "36d86935",
    "metadata": {},
    "source": [
     "### 2.1 TAP services\n",
@@ -233,7 +233,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "222bcb63",
+   "id": "8d4895b6",
    "metadata": {},
    "source": [
     "As before, we use the `vo.regsearch()` for a servicetype 'tap'.  There are a lot of TAP services in the registry, but they are listed slightly differently than cone services.  The metadata on each catalog is usually published in the registry with its cone service, and then the full TAP service is listed as an \"auxiliary\" service.  So to find a TAP service for a given catalog, we need to add the option *includeaux=True*. Alternatively, you can start with a single TAP service and then ask it specifically which tables it serves, but for this use case, that is less efficient.\n",
@@ -244,14 +244,14 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "id": "a8ba0450",
+   "id": "e6281223",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
        "<div><i>Table length=20</i>\n",
-       "<table id=\"table140715758368464\" class=\"table-striped table-bordered table-condensed\">\n",
+       "<table id=\"table139854336932016\" class=\"table-striped table-bordered table-condensed\">\n",
        "<thead><tr><th>ivoid</th><th>short_name</th><th>res_title</th></tr></thead>\n",
        "<thead><tr><th>object</th><th>object</th><th>object</th></tr></thead>\n",
        "<tr><td>ivo://cds.vizier/j/a+a/408/905</td><td>J/A+A/408/905</td><td>Very Luminous Galaxies</td></tr>\n",
@@ -315,7 +315,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "6ac3617f",
+   "id": "a5e2e1b4",
    "metadata": {},
    "source": [
     "There are many tables that mention these keywords. Pick some likely looking ones and look at the descriptions:"
@@ -324,7 +324,7 @@
   {
    "cell_type": "code",
    "execution_count": 6,
-   "id": "507d8b3f",
+   "id": "61b8aafe",
    "metadata": {},
    "outputs": [
     {
@@ -354,7 +354,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "0a644ffa",
+   "id": "4a624744",
    "metadata": {},
    "source": [
     "From the above information, you can choose the table you want and then use the specified TAP service to query it as described below.\n",
@@ -364,7 +364,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "136173b8",
+   "id": "4f8f8812",
    "metadata": {},
    "source": [
     "You can find out which tables a TAP serves and then look at the tables descriptions. The last line here sends a query directly to the service to ask it for a list of tables.  (This can take a minute, since there may be a lot of tables.)"
@@ -373,7 +373,7 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "id": "be9ea620",
+   "id": "b2a43b3e",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -385,7 +385,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "c2224743",
+   "id": "91259ed0",
    "metadata": {},
    "source": [
     "Then let's look for tables matching the terms we're interested in as above."
@@ -394,7 +394,7 @@
   {
    "cell_type": "code",
    "execution_count": 8,
-   "id": "6d43bc21",
+   "id": "b953f78e",
    "metadata": {},
    "outputs": [
     {
@@ -506,7 +506,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f91b9b82",
+   "id": "84e976f8",
    "metadata": {},
    "source": [
     "There are a number of tables that appear to be useful table for our goal, including the ZCAT,  which contains columns with the information that we need to select a sample of the brightest nearby spiral galaxy candidates.\n",
@@ -516,7 +516,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "e40b167e",
+   "id": "fbbaa89c",
    "metadata": {},
    "source": [
     "### 2.2 Expressing queries in ADQL"
@@ -524,7 +524,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "3d8b5ed1",
+   "id": "c0efaa13",
    "metadata": {},
    "source": [
     "The basics of ADQL:\n",
@@ -566,7 +566,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "63de3d33",
+   "id": "95d5e18a",
    "metadata": {},
    "source": [
     "### 2.3 A use case\n",
@@ -577,7 +577,7 @@
   {
    "cell_type": "code",
    "execution_count": 9,
-   "id": "e9349cb7",
+   "id": "44e6d820",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -597,14 +597,14 @@
   {
    "cell_type": "code",
    "execution_count": 10,
-   "id": "b87a48e0",
+   "id": "f0d91198",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
        "<div><i>Table length=3</i>\n",
-       "<table id=\"table140714578456208\" class=\"table-striped table-bordered table-condensed\">\n",
+       "<table id=\"table139853113491072\" class=\"table-striped table-bordered table-condensed\">\n",
        "<thead><tr><th>ra</th><th>dec</th><th>radial_velocity</th><th>radial_velocity_error</th><th>bmag</th><th>morph_type</th></tr></thead>\n",
        "<thead><tr><th>deg</th><th>deg</th><th>km / s</th><th>km / s</th><th></th><th></th></tr></thead>\n",
        "<thead><tr><th>float64</th><th>float64</th><th>int32</th><th>int16</th><th>float32</th><th>int16</th></tr></thead>\n",
@@ -637,7 +637,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "aeef3a04",
+   "id": "0663f0d1",
    "metadata": {},
    "source": [
     "See the __[information on the zcat](https://heasarc.gsfc.nasa.gov/W3Browse/galaxy-catalog/zcat.html)__ for column information. (We will use the 'radial_velocity' column rather than the 'redshift' column.) We note that spiral galaxies have morph_type between 1 - 9."
@@ -645,7 +645,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "5f86b20b",
+   "id": "2c6746f9",
    "metadata": {},
    "source": [
     "Therefore, we can generalize the query above to complete our exercise and select the brightest (bmag < 14), nearby (radial velocity < 3000), spiral ( morph_type = 1 - 9) galaxies as follows:"
@@ -654,7 +654,7 @@
   {
    "cell_type": "code",
    "execution_count": 11,
-   "id": "e7a29d0f",
+   "id": "5de1a132",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -667,14 +667,14 @@
   {
    "cell_type": "code",
    "execution_count": 12,
-   "id": "5895aa18",
+   "id": "738427dd",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
        "<div><i>Table length=1120</i>\n",
-       "<table id=\"table140714636062496\" class=\"table-striped table-bordered table-condensed\">\n",
+       "<table id=\"table139854337205312\" class=\"table-striped table-bordered table-condensed\">\n",
        "<thead><tr><th>ra</th><th>dec</th><th>radial_velocity</th><th>radial_velocity_error</th><th>bmag</th><th>morph_type</th></tr></thead>\n",
        "<thead><tr><th>deg</th><th>deg</th><th>km / s</th><th>km / s</th><th></th><th></th></tr></thead>\n",
        "<thead><tr><th>float64</th><th>float64</th><th>int32</th><th>int16</th><th>float32</th><th>int16</th></tr></thead>\n",
@@ -739,7 +739,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ee736014",
+   "id": "cc88b888",
    "metadata": {},
    "source": [
     "### 2.4 TAP examples for a given service\n",
@@ -750,7 +750,7 @@
   {
    "cell_type": "code",
    "execution_count": 13,
-   "id": "0dbea767",
+   "id": "072d66ec",
    "metadata": {},
    "outputs": [
     {
@@ -772,7 +772,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f5d50232",
+   "id": "4e6fdf89",
    "metadata": {},
    "source": [
     "Above, these examples look like a list of dictionaries.  But they are actually a list of objects that can be executed:"
@@ -781,7 +781,7 @@
   {
    "cell_type": "code",
    "execution_count": 14,
-   "id": "c85b2aa7",
+   "id": "170baaf8",
    "metadata": {},
    "outputs": [
     {
@@ -795,7 +795,7 @@
      "data": {
       "text/html": [
        "<div><i>Table length=2</i>\n",
-       "<table id=\"table140714641172528\" class=\"table-striped table-bordered table-condensed\">\n",
+       "<table id=\"table139853057012208\" class=\"table-striped table-bordered table-condensed\">\n",
        "<thead><tr><th>__row</th><th>seq_id</th><th>ra</th><th>dec</th><th>lii</th><th>bii</th><th>instrument</th><th>filter</th><th>site</th><th>exposure</th><th>requested_exposure</th><th>fits_type</th><th>start_time</th><th>end_time</th><th>name</th><th>pi_lname</th><th>pi_fname</th><th>ror</th><th>index_id</th><th>subj_cat</th><th>proc_rev</th><th>title</th><th>qa_number</th><th>ao</th><th>proposal_number</th><th>roll</th><th>rday_begin</th><th>rday_end</th><th>class</th><th>__x_ra_dec</th><th>__y_ra_dec</th><th>__z_ra_dec</th></tr></thead>\n",
        "<thead><tr><th></th><th></th><th>deg</th><th>deg</th><th>deg</th><th>deg</th><th></th><th></th><th></th><th>s</th><th>s</th><th></th><th>d</th><th>d</th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th>deg</th><th>d</th><th>d</th><th></th><th></th><th></th><th></th></tr></thead>\n",
        "<thead><tr><th>object</th><th>object</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>object</th><th>object</th><th>object</th><th>int32</th><th>int32</th><th>object</th><th>float64</th><th>float64</th><th>object</th><th>object</th><th>object</th><th>int32</th><th>object</th><th>int16</th><th>int16</th><th>object</th><th>int32</th><th>int16</th><th>int32</th><th>int16</th><th>int32</th><th>int32</th><th>int16</th><th>float64</th><th>float64</th><th>float64</th></tr></thead>\n",
@@ -829,7 +829,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "9148403b",
+   "id": "6b49bbfa",
    "metadata": {},
    "source": [
     "## 3. Using the TAP to cross-correlate and combine"
@@ -837,7 +837,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "e3ea0641",
+   "id": "50bf8470",
    "metadata": {},
    "source": [
     "### 3.1 Cross-correlating to combine catalogs\n",
@@ -852,7 +852,7 @@
   {
    "cell_type": "code",
    "execution_count": 15,
-   "id": "1b38a4de",
+   "id": "6ceb8878",
    "metadata": {},
    "outputs": [
     {
@@ -873,7 +873,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "d2c23b9a",
+   "id": "60cec303",
    "metadata": {},
    "source": [
     "The inline method is what PyVO will use.  These take a while, i.e. half a minute."
@@ -882,14 +882,14 @@
   {
    "cell_type": "code",
    "execution_count": 16,
-   "id": "7be98a89",
+   "id": "b4c9077d",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
        "<div><i>Table length=14</i>\n",
-       "<table id=\"table140714578452992\" class=\"table-striped table-bordered table-condensed\">\n",
+       "<table id=\"table139853113669856\" class=\"table-striped table-bordered table-condensed\">\n",
        "<thead><tr><th>ra</th><th>dec</th><th>radial_velocity</th><th>bmag</th><th>morph_type</th></tr></thead>\n",
        "<thead><tr><th>deg</th><th>deg</th><th></th><th></th><th></th></tr></thead>\n",
        "<thead><tr><th>float64</th><th>float64</th><th>int32</th><th>float32</th><th>int16</th></tr></thead>\n",
@@ -952,7 +952,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "32ed94e6",
+   "id": "886b692d",
    "metadata": {},
    "source": [
     "Therefore we now have the Bmag, morphological type and radial velocities for all the sources in our list with a single TAP query."
@@ -960,7 +960,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "8ec1709c",
+   "id": "8270c1c7",
    "metadata": {},
    "source": [
     "### 3.2 Cross-correlating with user-defined columns\n",
@@ -975,14 +975,14 @@
   {
    "cell_type": "code",
    "execution_count": 17,
-   "id": "9037fe81",
+   "id": "e02ae288",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
        "<div><i>Table length=14</i>\n",
-       "<table id=\"table140714578452992\" class=\"table-striped table-bordered table-condensed\">\n",
+       "<table id=\"table139853113669856\" class=\"table-striped table-bordered table-condensed\">\n",
        "<thead><tr><th>ra</th><th>dec</th><th>radial_velocity</th><th>bmag</th><th>morph_type</th><th>redshift</th><th>angDdeg</th></tr></thead>\n",
        "<thead><tr><th>deg</th><th>deg</th><th></th><th></th><th></th><th></th><th>deg</th></tr></thead>\n",
        "<thead><tr><th>float64</th><th>float64</th><th>int32</th><th>float32</th><th>int16</th><th>float64</th><th>float64</th></tr></thead>\n",
@@ -1045,7 +1045,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "4086ec0c",
+   "id": "8b7e6693",
    "metadata": {},
    "source": [
     "Now we construct and run a query that uses the new angDdeg column in every row search. Note, we also don't want to list the original candidates since we know these are in the catalog and we want rather to find any companions. Therefore, we exclude the match if the radial velocities match exactly."
@@ -1054,14 +1054,14 @@
   {
    "cell_type": "code",
    "execution_count": 18,
-   "id": "0219436a",
+   "id": "06f7fa92",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
        "<div><i>Table length=9</i>\n",
-       "<table id=\"table140714579098832\" class=\"table-striped table-bordered table-condensed\">\n",
+       "<table id=\"table139853055473552\" class=\"table-striped table-bordered table-condensed\">\n",
        "<thead><tr><th>ra</th><th>dec</th><th>ra2</th><th>dec2</th><th>radial_velocity</th><th>morph_type</th><th>bmag</th></tr></thead>\n",
        "<thead><tr><th>deg</th><th>deg</th><th>deg</th><th>deg</th><th></th><th></th><th></th></tr></thead>\n",
        "<thead><tr><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>int32</th><th>int16</th><th>float32</th></tr></thead>\n",
@@ -1111,7 +1111,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "d56b1f8a",
+   "id": "cc807a02",
    "metadata": {},
    "source": [
     "Therefore, by adding new information to our original data table, we could cross-correlate with the TAP.  We find that, in our candidate list, there is one true pair of galaxies."
@@ -1119,7 +1119,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "574cd4c5",
+   "id": "35e3fe8c",
    "metadata": {},
    "source": [
     "## 4. Synchronous versus asynchronous queries\n",
diff --git a/_sources/content/reference_notebooks/image_access.ipynb b/_sources/content/reference_notebooks/image_access.ipynb
index 4fa2a82..07eb710 100644
--- a/_sources/content/reference_notebooks/image_access.ipynb
+++ b/_sources/content/reference_notebooks/image_access.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "c1c9315c",
+   "id": "b13a8e05",
    "metadata": {},
    "source": [
     "# Image Access\n",
@@ -19,7 +19,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "68ea7132",
+   "id": "5d48a7e6",
    "metadata": {},
    "source": [
     "**\\*Note:**  for all of these notebooks, the results depend on real-time queries.  Sometimes there are problems, either because a given service has changed, is undergoing maintenance, or the internet connectivity is having problems, etc.  Always retry a couple of times, come back later and try again, and only then send us the problem report to investigate."
@@ -28,7 +28,7 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "id": "360599f7",
+   "id": "41049977",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -56,7 +56,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "c4ad31ee",
+   "id": "b19e1e3a",
    "metadata": {},
    "source": [
     "## 1. Finding SIA resources from the Registry\n",
@@ -69,14 +69,14 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "id": "0ac6b39a",
+   "id": "315c5a73",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
        "<div><i>Table length=18</i>\n",
-       "<table id=\"table140520266452464\" class=\"table-striped table-bordered table-condensed\">\n",
+       "<table id=\"table140710842505856\" class=\"table-striped table-bordered table-condensed\">\n",
        "<thead><tr><th>ivoid</th><th>short_name</th><th>res_title</th></tr></thead>\n",
        "<thead><tr><th>object</th><th>object</th><th>object</th></tr></thead>\n",
        "<tr><td>ivo://archive.stsci.edu/sia/galex</td><td>GALEX</td><td>Galaxy Evolution Explorer (GALEX)</td></tr>\n",
@@ -136,7 +136,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "7eb60ad9",
+   "id": "cede5abf",
    "metadata": {},
    "source": [
     "This returns an astropy table containing information about the services available.  We can then specify the service we want by using the corresponding row.  We'll repeat the search with additional qualifiers to isolate the row we want (note that in the keyword search the \"%\" character can be used as a wild card):"
@@ -145,14 +145,14 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "id": "6b99046e",
+   "id": "47669cee",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
        "<div><i>Table length=1</i>\n",
-       "<table id=\"table140520264544368\" class=\"table-striped table-bordered table-condensed\">\n",
+       "<table id=\"table140710841149728\" class=\"table-striped table-bordered table-condensed\">\n",
        "<thead><tr><th>ivoid</th><th>short_name</th><th>res_title</th></tr></thead>\n",
        "<thead><tr><th>object</th><th>object</th><th>object</th></tr></thead>\n",
        "<tr><td>ivo://nasa.heasarc/skyview/swiftuvot</td><td>SWIFTUVOT</td><td>Swift UVOT Combined V Intensity Images</td></tr>\n",
@@ -178,7 +178,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "c3b1ef0b",
+   "id": "f50a9134",
    "metadata": {},
    "source": [
     "This shows us that the data we are interested in comes from the HEASARC's SkyView service, but the point of these VO tools is that you don't need to know that ahead of time or indeed to care where it comes from."
@@ -186,7 +186,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "e4036bc5",
+   "id": "9a138a6d",
    "metadata": {},
    "source": [
     "## 2. Using SIA to retrieve an image\n",
@@ -199,22 +199,22 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "id": "125ca910",
+   "id": "4ae2e695",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
        "<div><i>Table length=6</i>\n",
-       "<table id=\"table140521143286176\" class=\"table-striped table-bordered table-condensed\">\n",
+       "<table id=\"table140710949548768\" class=\"table-striped table-bordered table-condensed\">\n",
        "<thead><tr><th>Survey</th><th>Ra</th><th>Dec</th><th>Dim</th><th>Size</th><th>Scale</th><th>Format</th><th>PixFlags</th><th>URL</th><th>LogicalName</th></tr></thead>\n",
        "<thead><tr><th>object</th><th>float64</th><th>float64</th><th>int32</th><th>object</th><th>object</th><th>object</th><th>object</th><th>object</th><th>object</th></tr></thead>\n",
-       "<tr><td>swiftuvotvint</td><td>202.469575</td><td>47.1952583</td><td>2</td><td>[300 300]</td><td>[-0.0006666666666666668 0.0006666666666666668]</td><td>image/jpeg</td><td>F</td><td>https://skyview.gsfc.nasa.gov/cgi-bin/images?position=202.469575%2C47.1952583&amp;survey=swiftuvotvint&amp;pixels=300%2C300&amp;sampler=LI&amp;size=0.20000000000000004%2C0.20000000000000004&amp;projection=Tan&amp;coordinates=J2000.0&amp;requestID=skv1734385753936&amp;nofits=1&amp;quicklook=jpeg&amp;return=jpeg</td><td>1</td></tr>\n",
-       "<tr><td>swiftuvotbint</td><td>202.469575</td><td>47.1952583</td><td>2</td><td>[300 300]</td><td>[-0.0006666666666666668 0.0006666666666666668]</td><td>image/jpeg</td><td>F</td><td>https://skyview.gsfc.nasa.gov/cgi-bin/images?position=202.469575%2C47.1952583&amp;survey=swiftuvotbint&amp;pixels=300%2C300&amp;sampler=LI&amp;size=0.20000000000000004%2C0.20000000000000004&amp;projection=Tan&amp;coordinates=J2000.0&amp;requestID=skv1734385754201&amp;nofits=1&amp;quicklook=jpeg&amp;return=jpeg</td><td>2</td></tr>\n",
-       "<tr><td>swiftuvotuint</td><td>202.469575</td><td>47.1952583</td><td>2</td><td>[300 300]</td><td>[-0.0006666666666666668 0.0006666666666666668]</td><td>image/jpeg</td><td>F</td><td>https://skyview.gsfc.nasa.gov/cgi-bin/images?position=202.469575%2C47.1952583&amp;survey=swiftuvotuint&amp;pixels=300%2C300&amp;sampler=LI&amp;size=0.20000000000000004%2C0.20000000000000004&amp;projection=Tan&amp;coordinates=J2000.0&amp;requestID=skv1734385755295&amp;nofits=1&amp;quicklook=jpeg&amp;return=jpeg</td><td>3</td></tr>\n",
-       "<tr><td>swiftuvotuvw1int</td><td>202.469575</td><td>47.1952583</td><td>2</td><td>[300 300]</td><td>[-0.0006666666666666668 0.0006666666666666668]</td><td>image/jpeg</td><td>F</td><td>https://skyview.gsfc.nasa.gov/cgi-bin/images?position=202.469575%2C47.1952583&amp;survey=swiftuvotuvw1int&amp;pixels=300%2C300&amp;sampler=LI&amp;size=0.20000000000000004%2C0.20000000000000004&amp;projection=Tan&amp;coordinates=J2000.0&amp;requestID=skv1734385755771&amp;nofits=1&amp;quicklook=jpeg&amp;return=jpeg</td><td>4</td></tr>\n",
-       "<tr><td>swiftuvotuvw2int</td><td>202.469575</td><td>47.1952583</td><td>2</td><td>[300 300]</td><td>[-0.0006666666666666668 0.0006666666666666668]</td><td>image/jpeg</td><td>F</td><td>https://skyview.gsfc.nasa.gov/cgi-bin/images?position=202.469575%2C47.1952583&amp;survey=swiftuvotuvw2int&amp;pixels=300%2C300&amp;sampler=LI&amp;size=0.20000000000000004%2C0.20000000000000004&amp;projection=Tan&amp;coordinates=J2000.0&amp;requestID=skv1734385756228&amp;nofits=1&amp;quicklook=jpeg&amp;return=jpeg</td><td>5</td></tr>\n",
-       "<tr><td>swiftuvotuvm2int</td><td>202.469575</td><td>47.1952583</td><td>2</td><td>[300 300]</td><td>[-0.0006666666666666668 0.0006666666666666668]</td><td>image/jpeg</td><td>F</td><td>https://skyview.gsfc.nasa.gov/cgi-bin/images?position=202.469575%2C47.1952583&amp;survey=swiftuvotuvm2int&amp;pixels=300%2C300&amp;sampler=LI&amp;size=0.20000000000000004%2C0.20000000000000004&amp;projection=Tan&amp;coordinates=J2000.0&amp;requestID=skv1734385756659&amp;nofits=1&amp;quicklook=jpeg&amp;return=jpeg</td><td>6</td></tr>\n",
+       "<tr><td>swiftuvotvint</td><td>202.469575</td><td>47.19525833</td><td>2</td><td>[300 300]</td><td>[-0.0006666666666666668 0.0006666666666666668]</td><td>image/jpeg</td><td>F</td><td>https://skyview.gsfc.nasa.gov/cgi-bin/images?position=202.469575%2C47.19525833&amp;survey=swiftuvotvint&amp;pixels=300%2C300&amp;sampler=LI&amp;size=0.20000000000000004%2C0.20000000000000004&amp;projection=Tan&amp;coordinates=J2000.0&amp;requestID=skv1734402145351&amp;nofits=1&amp;quicklook=jpeg&amp;return=jpeg</td><td>1</td></tr>\n",
+       "<tr><td>swiftuvotbint</td><td>202.469575</td><td>47.19525833</td><td>2</td><td>[300 300]</td><td>[-0.0006666666666666668 0.0006666666666666668]</td><td>image/jpeg</td><td>F</td><td>https://skyview.gsfc.nasa.gov/cgi-bin/images?position=202.469575%2C47.19525833&amp;survey=swiftuvotbint&amp;pixels=300%2C300&amp;sampler=LI&amp;size=0.20000000000000004%2C0.20000000000000004&amp;projection=Tan&amp;coordinates=J2000.0&amp;requestID=skv1734402145614&amp;nofits=1&amp;quicklook=jpeg&amp;return=jpeg</td><td>2</td></tr>\n",
+       "<tr><td>swiftuvotuint</td><td>202.469575</td><td>47.19525833</td><td>2</td><td>[300 300]</td><td>[-0.0006666666666666668 0.0006666666666666668]</td><td>image/jpeg</td><td>F</td><td>https://skyview.gsfc.nasa.gov/cgi-bin/images?position=202.469575%2C47.19525833&amp;survey=swiftuvotuint&amp;pixels=300%2C300&amp;sampler=LI&amp;size=0.20000000000000004%2C0.20000000000000004&amp;projection=Tan&amp;coordinates=J2000.0&amp;requestID=skv1734402146764&amp;nofits=1&amp;quicklook=jpeg&amp;return=jpeg</td><td>3</td></tr>\n",
+       "<tr><td>swiftuvotuvw1int</td><td>202.469575</td><td>47.19525833</td><td>2</td><td>[300 300]</td><td>[-0.0006666666666666668 0.0006666666666666668]</td><td>image/jpeg</td><td>F</td><td>https://skyview.gsfc.nasa.gov/cgi-bin/images?position=202.469575%2C47.19525833&amp;survey=swiftuvotuvw1int&amp;pixels=300%2C300&amp;sampler=LI&amp;size=0.20000000000000004%2C0.20000000000000004&amp;projection=Tan&amp;coordinates=J2000.0&amp;requestID=skv1734402147249&amp;nofits=1&amp;quicklook=jpeg&amp;return=jpeg</td><td>4</td></tr>\n",
+       "<tr><td>swiftuvotuvw2int</td><td>202.469575</td><td>47.19525833</td><td>2</td><td>[300 300]</td><td>[-0.0006666666666666668 0.0006666666666666668]</td><td>image/jpeg</td><td>F</td><td>https://skyview.gsfc.nasa.gov/cgi-bin/images?position=202.469575%2C47.19525833&amp;survey=swiftuvotuvw2int&amp;pixels=300%2C300&amp;sampler=LI&amp;size=0.20000000000000004%2C0.20000000000000004&amp;projection=Tan&amp;coordinates=J2000.0&amp;requestID=skv1734402147720&amp;nofits=1&amp;quicklook=jpeg&amp;return=jpeg</td><td>5</td></tr>\n",
+       "<tr><td>swiftuvotuvm2int</td><td>202.469575</td><td>47.19525833</td><td>2</td><td>[300 300]</td><td>[-0.0006666666666666668 0.0006666666666666668]</td><td>image/jpeg</td><td>F</td><td>https://skyview.gsfc.nasa.gov/cgi-bin/images?position=202.469575%2C47.19525833&amp;survey=swiftuvotuvm2int&amp;pixels=300%2C300&amp;sampler=LI&amp;size=0.20000000000000004%2C0.20000000000000004&amp;projection=Tan&amp;coordinates=J2000.0&amp;requestID=skv1734402148194&amp;nofits=1&amp;quicklook=jpeg&amp;return=jpeg</td><td>6</td></tr>\n",
        "</table></div>"
       ],
       "text/plain": [
@@ -244,7 +244,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f316ec58",
+   "id": "97a7609b",
    "metadata": {},
    "source": [
     "Extract the fields you're interested in, e.g., the URLs of the images made by skyview.  Note that specifying as we did SwiftUVOT, we get a number of different images, e.g., UVOT U, V, B, W1, W2, etc.  For each survey, there are two URLs, first the FITS IMAGE and second the JPEG.\n",
@@ -255,14 +255,14 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "id": "70ca3de9",
+   "id": "ec6c7963",
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "https://skyview.gsfc.nasa.gov/cgi-bin/images?position=202.469575%2C47.1952583&survey=swiftuvotvint&pixels=300%2C300&sampler=LI&size=0.20000000000000004%2C0.20000000000000004&projection=Tan&coordinates=J2000.0&requestID=skv1734385753936&nofits=1&quicklook=jpeg&return=jpeg\n"
+      "https://skyview.gsfc.nasa.gov/cgi-bin/images?position=202.469575%2C47.19525833&survey=swiftuvotvint&pixels=300%2C300&sampler=LI&size=0.20000000000000004%2C0.20000000000000004&projection=Tan&coordinates=J2000.0&requestID=skv1734402145351&nofits=1&quicklook=jpeg&return=jpeg\n"
      ]
     }
    ],
@@ -273,7 +273,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f6472872",
+   "id": "c6842725",
    "metadata": {},
    "source": [
     "## 3. Viewing the resulting image"
@@ -281,7 +281,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "7db8430d",
+   "id": "bba7c8f0",
    "metadata": {},
    "source": [
     "### JPG images\n",
@@ -292,13 +292,13 @@
   {
    "cell_type": "code",
    "execution_count": 6,
-   "id": "bb7e9d38",
+   "id": "4283063b",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
-       "<img src=\"https://skyview.gsfc.nasa.gov/cgi-bin/images?position=202.469575%2C47.1952583&survey=swiftuvotvint&pixels=300%2C300&sampler=LI&size=0.20000000000000004%2C0.20000000000000004&projection=Tan&coordinates=J2000.0&requestID=skv1734385753936&nofits=1&quicklook=jpeg&return=jpeg\"/>"
+       "<img src=\"https://skyview.gsfc.nasa.gov/cgi-bin/images?position=202.469575%2C47.19525833&survey=swiftuvotvint&pixels=300%2C300&sampler=LI&size=0.20000000000000004%2C0.20000000000000004&projection=Tan&coordinates=J2000.0&requestID=skv1734402145351&nofits=1&quicklook=jpeg&return=jpeg\"/>"
       ],
       "text/plain": [
        "<IPython.core.display.Image object>"
@@ -315,7 +315,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "9cdd50aa",
+   "id": "431bf1c8",
    "metadata": {},
    "source": [
     "### Fits files\n",
@@ -328,14 +328,14 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "id": "89f70672",
+   "id": "f1dd7486",
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Filename: /home/runner/.astropy/cache/download/url/a34e6c66f0392cfbe38054abfa1340d5/contents\n",
+      "Filename: /home/runner/.astropy/cache/download/url/dbaa17f98770f79d75b56cdce2aa43eb/contents\n",
       "No.    Name      Ver    Type      Cards   Dimensions   Format\n",
       "  0  PRIMARY       1 PrimaryHDU     111   (300, 300)   float32   \n"
      ]
@@ -352,7 +352,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "7c5f9309",
+   "id": "c0072bfe",
    "metadata": {},
    "source": [
     "#### Using imshow"
@@ -361,13 +361,13 @@
   {
    "cell_type": "code",
    "execution_count": 8,
-   "id": "315ed73b",
+   "id": "9927f867",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<matplotlib.image.AxesImage at 0x7fcd6c656710>"
+       "<matplotlib.image.AxesImage at 0x7ff9cba4a050>"
       ]
      },
      "execution_count": 8,
@@ -376,7 +376,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
diff --git a/_sources/content/reference_notebooks/spectral_access.ipynb b/_sources/content/reference_notebooks/spectral_access.ipynb
index d7bdf82..7c1e353 100644
--- a/_sources/content/reference_notebooks/spectral_access.ipynb
+++ b/_sources/content/reference_notebooks/spectral_access.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "e1d2329e",
+   "id": "dd21a462",
    "metadata": {},
    "source": [
     "# Spectral Access\n",
@@ -15,7 +15,7 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "id": "8058d48e",
+   "id": "f2eab9a7",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -43,7 +43,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "3014f3f1",
+   "id": "fa64e176",
    "metadata": {},
    "source": [
     "## Finding available Spectral Access Services\n",
@@ -54,14 +54,14 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "id": "e5ecc4ef",
+   "id": "0adbd9b2",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
        "<div><i>Table length=7</i>\n",
-       "<table id=\"table140019074770752\" class=\"table-striped table-bordered table-condensed\">\n",
+       "<table id=\"table140056417968976\" class=\"table-striped table-bordered table-condensed\">\n",
        "<thead><tr><th>ivoid</th><th>short_name</th></tr></thead>\n",
        "<thead><tr><th>object</th><th>object</th></tr></thead>\n",
        "<tr><td>ivo://nasa.heasarc/chanmaster</td><td>Chandra</td></tr>\n",
@@ -99,7 +99,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "dd01623d",
+   "id": "82fbfd6f",
    "metadata": {},
    "source": [
     "We can look at only the Chandra entry:"
@@ -108,7 +108,7 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "id": "203d39ed",
+   "id": "a507e4f0",
    "metadata": {},
    "outputs": [
     {
@@ -129,7 +129,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f15cb56f",
+   "id": "2dd70901",
    "metadata": {},
    "source": [
     "## Chandra Spectrum of Delta Ori\n",
@@ -140,7 +140,7 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "id": "6e392104",
+   "id": "6e653b0f",
    "metadata": {},
    "outputs": [
     {
@@ -158,7 +158,7 @@
      "data": {
       "text/html": [
        "<i>Table length=6</i>\n",
-       "<table id=\"table140019075760624-358844\" class=\"table-striped table-bordered table-condensed\">\n",
+       "<table id=\"table140057343998320-562779\" class=\"table-striped table-bordered table-condensed\">\n",
        "<thead><tr><th>idx</th><th>obsid</th><th>status</th><th>name</th><th>ra</th><th>dec</th><th>time</th><th>detector</th><th>grating</th><th>exposure</th><th>type</th><th>pi</th><th>public_date</th><th>datalink</th><th>SSA_start_time</th><th>SSA_tmid</th><th>SSA_stop_time</th><th>SSA_duration</th><th>SSA_coord_obs</th><th>SSA_ra</th><th>SSA_dec</th><th>SSA_fov</th><th>SSA_title</th><th>SSA_reference</th><th>SSA_datalength</th><th>SSA_datamodel</th><th>SSA_instrument</th><th>SSA_publisher</th><th>SSA_format</th><th>SSA_wavelength_min</th><th>SSA_wavelength_max</th><th>SSA_bandwidth</th><th>SSA_bandpass</th><th>cloud_access</th></tr></thead>\n",
        "<thead><tr><th></th><th></th><th></th><th></th><th>deg</th><th>deg</th><th>d</th><th></th><th></th><th>s</th><th></th><th></th><th>d</th><th></th><th>d</th><th>d</th><th>d</th><th>s</th><th>deg</th><th>deg</th><th>deg</th><th>deg</th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th>m</th><th>m</th><th>m</th><th>m</th><th></th></tr></thead>\n",
        "<tr><td>0</td><td>639</td><td>archived</td><td>DELTA ORI</td><td>83.00125</td><td>-0.29917</td><td>51556.1364</td><td>ACIS-S</td><td>HETG</td><td>49680</td><td>GO</td><td>Cassinelli</td><td>52037</td><td>11743:chandra.obs.misc</td><td>51556.136400463</td><td>--</td><td>--</td><td>49680.0</td><td>--</td><td>83.00125</td><td>-0.29917</td><td>0.81</td><td>acisf00639N005_pha2.fits</td><td>https://heasarc.gsfc.nasa.gov/FTP/chandra/data/byobsid/9/639/primary/acisf00639N005_pha2.fits.gz</td><td>12</td><td>Spectrum-1.0</td><td>ACIS-S</td><td>HEASARC</td><td>application/fits</td><td>1.2398e-10</td><td>6.1992e-09</td><td>6.07522e-09</td><td>3.16159e-09</td><td>{&quot;aws&quot;:{&quot;bucket_name&quot;:&quot;nasa-heasarc&quot;,&quot;region&quot;:&quot;us-east-1&quot;,&quot;policy&quot;:&quot;open&quot;,&quot;key&quot;:&quot;chandra/data/byobsid/9/639/primary/acisf00639N005_pha2.fits.gz&quot;}}</td></tr>\n",
@@ -190,14 +190,14 @@
        "    datatables: 'https://cdn.datatables.net/1.10.12/js/jquery.dataTables.min'\n",
        "}});\n",
        "require([\"datatables\"], function(){\n",
-       "    console.log(\"$('#table140019075760624-358844').dataTable()\");\n",
+       "    console.log(\"$('#table140057343998320-562779').dataTable()\");\n",
        "    \n",
        "jQuery.extend( jQuery.fn.dataTableExt.oSort, {\n",
        "    \"optionalnum-asc\": astropy_sort_num,\n",
        "    \"optionalnum-desc\": function (a,b) { return -astropy_sort_num(a, b); }\n",
        "});\n",
        "\n",
-       "    $('#table140019075760624-358844').dataTable({\n",
+       "    $('#table140057343998320-562779').dataTable({\n",
        "        order: [],\n",
        "        pageLength: 50,\n",
        "        lengthMenu: [[10, 25, 50, 100, 500, 1000, -1], [10, 25, 50, 100, 500, 1000, 'All']],\n",
@@ -225,7 +225,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "10ff366f",
+   "id": "10ca9540",
    "metadata": {},
    "source": [
     "Accessing one of the spectra."
@@ -234,7 +234,7 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "id": "138e3b6a",
+   "id": "195672d0",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -249,7 +249,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "909cc0c3",
+   "id": "7b0ab3e3",
    "metadata": {},
    "source": [
     "## Simple example of plotting a spectrum"
@@ -258,14 +258,14 @@
   {
    "cell_type": "code",
    "execution_count": 6,
-   "id": "5b1a582e",
+   "id": "13e9f7ea",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
        "<div><i>Table length=12</i>\n",
-       "<table id=\"table140019034219584\" class=\"table-striped table-bordered table-condensed\">\n",
+       "<table id=\"table140056379989472\" class=\"table-striped table-bordered table-condensed\">\n",
        "<thead><tr><th>SPEC_NUM</th><th>TG_M</th><th>TG_PART</th><th>TG_SRCID</th><th>X</th><th>Y</th><th>CHANNEL</th><th>COUNTS</th><th>STAT_ERR</th><th>BACKGROUND_UP</th><th>BACKGROUND_DOWN</th><th>BIN_LO</th><th>BIN_HI</th></tr></thead>\n",
        "<thead><tr><th>int16</th><th>int16</th><th>int16</th><th>int16</th><th>float32</th><th>float32</th><th>int16[8192]</th><th>int16[8192]</th><th>float32[8192]</th><th>int16[8192]</th><th>int16[8192]</th><th>float64[8192]</th><th>float64[8192]</th></tr></thead>\n",
        "<tr><td>1</td><td>-3</td><td>1</td><td>1</td><td>4094.9138</td><td>4132.076</td><td>1 .. 8192</td><td>0 .. 0</td><td>1.8660254 .. 1.8660254</td><td>0 .. 0</td><td>0 .. 0</td><td>7.159166666667378 .. 0.3333333333333333</td><td>7.160000000000712 .. 0.33416666666666667</td></tr>\n",
@@ -314,7 +314,7 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "id": "a00df91b",
+   "id": "313c3b72",
    "metadata": {},
    "outputs": [
     {
@@ -351,7 +351,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "83fa3f0c",
+   "id": "044e07af",
    "metadata": {},
    "source": [
     "This can then be analyzed in your favorite spectral analysis tool, e.g., [pyXspec](https://heasarc.gsfc.nasa.gov/xanadu/xspec/python/html/index.html).  (For the winter 2018 AAS workshop, we demonstrated this in a [notebook](https://github.com/NASA-NAVO/aas_workshop_2018/blob/master/heasarc/heasarc_Spectral_Access.md) that you can consult for how to use pyXspec, but the pyXspec documentation will have more information.)"
@@ -360,7 +360,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "76aae1dc",
+   "id": "53689a93",
    "metadata": {},
    "outputs": [],
    "source": []
diff --git a/_sources/content/reference_notebooks/ucds_unified_content_descriptors.ipynb b/_sources/content/reference_notebooks/ucds_unified_content_descriptors.ipynb
index f99e092..20df6c5 100644
--- a/_sources/content/reference_notebooks/ucds_unified_content_descriptors.ipynb
+++ b/_sources/content/reference_notebooks/ucds_unified_content_descriptors.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "7827824f",
+   "id": "b96993b9",
    "metadata": {},
    "source": [
     "# UCDs (Unified Content Descriptors)\n",
@@ -21,7 +21,7 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "id": "19581e72",
+   "id": "056ed78e",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -35,7 +35,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "17cfb169",
+   "id": "2ec76840",
    "metadata": {},
    "source": [
     "Let's look at some tables in a little more detail.  Let's find the Hubble Source Catalog version 3 (HSCv3), assuming there's only one at MAST."
@@ -44,7 +44,7 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "id": "2b5a0ae1",
+   "id": "8b00aec1",
    "metadata": {},
    "outputs": [
     {
@@ -68,7 +68,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "e6f24191",
+   "id": "58fbb7e0",
    "metadata": {},
    "source": [
     "Now let's see what tables are provided by this service for HSCv3.  Note that this is another query to the service:"
@@ -77,7 +77,7 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "id": "01cc1cc8",
+   "id": "16ac5251",
    "metadata": {},
    "outputs": [
     {
@@ -94,6 +94,8 @@
       "tap_schema.schemas             - description of schemas in this dataset\n",
       "----\n",
       "tap_schema.tables              - description of tables in this dataset\n",
+      "----\n",
+      "tap_schema.columns             - description of columns in this dataset\n",
       "----\n"
      ]
     },
@@ -101,11 +103,11 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "tap_schema.columns             - description of columns in this dataset\n",
-      "----\n",
       "tap_schema.keys                - description of foreign keys in this dataset\n",
       "----\n",
       "tap_schema.key_columns         - description of foreign key columns in this dataset\n",
+      "----\n",
+      "dbo.detailedcatalog            - Detailed list of source catalog parameters\n",
       "----\n"
      ]
     },
@@ -113,9 +115,9 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "dbo.detailedcatalog            - Detailed list of source catalog parameters\n",
-      "----\n",
       "dbo.hcvdetailedview            - Detailed list of Hubble Catalog of Variables parameters\n",
+      "----\n",
+      "dbo.hcvsummaryview             - Summary list of Hubble Catalog of Variables parameters\n",
       "----\n"
      ]
     },
@@ -123,8 +125,6 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "dbo.hcvsummaryview             - Summary list of Hubble Catalog of Variables parameters\n",
-      "----\n",
       "dbo.propermotionsview          - List of proper motion information\n",
       "----\n",
       "dbo.sourcepositionsview        - List of source position information\n",
@@ -136,6 +136,8 @@
      "output_type": "stream",
      "text": [
       "dbo.summagaper2catview         - Summary list of source catalog with Aper2 magnitudes\n",
+      "----\n",
+      "dbo.summagautocatview          - Summary list of source catalog with MagAuto magnitudes\n",
       "----\n"
      ]
     },
@@ -143,8 +145,6 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "dbo.summagautocatview          - Summary list of source catalog with MagAuto magnitudes\n",
-      "----\n",
       "dbo.catalog_image_metadata     - Summary list of Image processing metadata\n",
       "----\n"
      ]
@@ -159,7 +159,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "cd151a37",
+   "id": "2b252f8c",
    "metadata": {},
    "source": [
     "Let's look at the first 10 columns of the DetailedCatalog table.  Again, note that calling the columns attribute sends another query to the service to ask for the columns."
@@ -168,7 +168,7 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "id": "e14b1322",
+   "id": "ef370e00",
    "metadata": {},
    "outputs": [
     {
@@ -221,7 +221,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "7359057d",
+   "id": "fd4264a4",
    "metadata": {},
    "source": [
     "The PyVO method to get the columns will automatically fetch all the meta-data about those columns.  It's up to the service provider to set them correctly, of course, but in this case, we see that the column named \"matchra\" is identified with the UCD \"pos.eq.ra\".\n",
@@ -232,7 +232,7 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "id": "404df660",
+   "id": "5935e80c",
    "metadata": {},
    "outputs": [
     {
@@ -250,7 +250,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "b77fdc01",
+   "id": "0a693ba5",
    "metadata": {},
    "source": [
     "Since that guessing doesn't give a unique answer, the more general and reliable approach is to check for the correct UCD.  It also has the further advantage that it can be used to label columns that should be used for certain purposes when there are multiple possibilities.  For instance, this table has MatchRA and SourceRA.  Let's check the UCD:\n",
@@ -261,7 +261,7 @@
   {
    "cell_type": "code",
    "execution_count": 6,
-   "id": "92a18faf",
+   "id": "1e313ef6",
    "metadata": {},
    "outputs": [
     {
@@ -283,7 +283,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "5dd2586a",
+   "id": "1feba46a",
    "metadata": {},
    "source": [
     "What that shows you is that though there are two columns in this table that give RA information, only one has the 'pos.eq.ra' UCD. The documentation for this ought to explain the usage of these columns, and the UCD should not be used as a substitute for understanding the table. But it can be a useful tool."
@@ -291,7 +291,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a8ea26d2",
+   "id": "6f6a9335",
    "metadata": {},
    "source": [
     "In particular, you can use the UCDs to look for catalogs that might have the information you're interested in. Then you can code the same query to work for different tables (with different column names) in a loop.  This sends a bunch of queries but doesn't take too long, a minute maybe. (One is particularly slow.)"
@@ -300,7 +300,7 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "id": "1ddfd414",
+   "id": "f0e80151",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -344,7 +344,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "b7a2dd4b",
+   "id": "7f1db0c8",
    "metadata": {},
    "source": [
     "You can also use UCDs to look at the results.  Above, we collected just the first 10 rows of the four columns we're interested in from every catalog that had them.  But these tables still have their original column names.  So the UCDs will still be useful, and PyVO provides a simple routine to convert from UCD to column (field) name.\n",
@@ -357,7 +357,7 @@
   {
    "cell_type": "code",
    "execution_count": 8,
-   "id": "45e9ad8c",
+   "id": "95f8598d",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -378,7 +378,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ad179b99",
+   "id": "171441d4",
    "metadata": {},
    "source": [
     "Lastly, if you have a table of results from a TAP query (and if that service includes the UCDs), then you can get data based on UCDs with the getbyucd() method, which simply gets the corresponding element using fieldname_with_ucd():"
@@ -387,7 +387,7 @@
   {
    "cell_type": "code",
    "execution_count": 9,
-   "id": "5cfb85eb",
+   "id": "164489a7",
    "metadata": {},
    "outputs": [
     {
@@ -417,7 +417,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "eaf19905",
+   "id": "ed0d1e9e",
    "metadata": {},
    "source": [
     "Note that we can see earlier in this notebook, when we looked at this table's contents, that there are two phot.mag fields in this table, MagAper2 and MagAuto.  The getbyucd() and fieldname_with_ucd() routines do not currently allow you to handle multiple columns with the same UCD.  The code can help you find what you want, but it depends on the meta data the service defines, and you still must look at the detailed information for each catalog you use to understand what it contains."
@@ -426,7 +426,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "afc7e479",
+   "id": "e0ef2172",
    "metadata": {},
    "outputs": [],
    "source": []
diff --git a/_sources/content/reference_notebooks/votables.ipynb b/_sources/content/reference_notebooks/votables.ipynb
index 4228c51..a73625c 100644
--- a/_sources/content/reference_notebooks/votables.ipynb
+++ b/_sources/content/reference_notebooks/votables.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "6e4f3685",
+   "id": "fbcbe004",
    "metadata": {},
    "source": [
     "# VO Tables\n",
@@ -12,7 +12,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "82e90453",
+   "id": "3e33764c",
    "metadata": {},
    "source": [
     "There are several ways of doing this, and there are a few object layers here, which can be confusing:\n",
@@ -29,7 +29,7 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "id": "100a9ea7",
+   "id": "88977f9e",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -41,7 +41,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "507f4a18",
+   "id": "eb8bbc5f",
    "metadata": {},
    "source": [
     "## Create a table with only two columns starting from an astropy Table"
@@ -50,7 +50,7 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "id": "5060d11f",
+   "id": "e966f5d1",
    "metadata": {},
    "outputs": [
     {
@@ -118,7 +118,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "288bbec7",
+   "id": "6dbf3724",
    "metadata": {},
    "source": [
     "## Then convert this to a VOTableFile object which contains a nested set of *resources* and *tables* (in this case, only one of each)"
@@ -127,7 +127,7 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "id": "fff50795",
+   "id": "a60f9785",
    "metadata": {},
    "outputs": [
     {
@@ -175,7 +175,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "b13b2c3f",
+   "id": "727fb266",
    "metadata": {},
    "outputs": [],
    "source": []
diff --git a/_sources/content/use_case_notebooks/candidate_list_exercise.ipynb b/_sources/content/use_case_notebooks/candidate_list_exercise.ipynb
index 51583ed..53e5f2e 100644
--- a/_sources/content/use_case_notebooks/candidate_list_exercise.ipynb
+++ b/_sources/content/use_case_notebooks/candidate_list_exercise.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "4c8e8ba1",
+   "id": "5a0064d1",
    "metadata": {},
    "source": [
     "# Candidate List Exercise\n",
@@ -16,7 +16,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "c8cde890",
+   "id": "006cc0ac",
    "metadata": {},
    "source": [
     "## 1. Import the Python modules we'll be using"
@@ -25,7 +25,7 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "id": "09d2fbda",
+   "id": "85808acd",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -53,7 +53,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "66b117fd",
+   "id": "e932ccf4",
    "metadata": {},
    "source": [
     "The next cell prepares the notebook to display our visualizations."
@@ -62,7 +62,7 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "id": "6215d870",
+   "id": "2557e3c0",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -71,7 +71,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "43effa76",
+   "id": "a32655ab",
    "metadata": {},
    "source": [
     "## 2. Search NED for objects in this paper\n",
@@ -82,7 +82,7 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "id": "1b184ba5",
+   "id": "ba5656dd",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -92,7 +92,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "549af14f",
+   "id": "f9743c10",
    "metadata": {},
    "source": [
     "## 3. Filter the NED results\n",
@@ -103,14 +103,14 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "a698741d",
+   "id": "ca3c99b6",
    "metadata": {},
    "outputs": [],
    "source": []
   },
   {
    "cell_type": "markdown",
-   "id": "01ebd64f",
+   "id": "aa48d69d",
    "metadata": {},
    "source": [
     "## 4. Search the NAVO Registry for image resources\n",
@@ -121,7 +121,7 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "id": "a4af14a5",
+   "id": "63d19d80",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -131,7 +131,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "9deb0d98",
+   "id": "5b6c2061",
    "metadata": {},
    "source": [
     "## 5. Search the NAVO Registry for image resources that will allow you to search for AllWISE images\n",
@@ -142,7 +142,7 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "id": "c4741b6f",
+   "id": "8daa1613",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -152,7 +152,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "68495989",
+   "id": "9ceab8cd",
    "metadata": {},
    "source": [
     "## 6. Choose the AllWISE image service that you are interested in"
@@ -161,14 +161,14 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "8516f9c3",
+   "id": "15e54a9b",
    "metadata": {},
    "outputs": [],
    "source": []
   },
   {
    "cell_type": "markdown",
-   "id": "ff77f04d",
+   "id": "2dd64f2f",
    "metadata": {},
    "source": [
     "## 7. Choose one of the galaxies in the NED list\n",
@@ -179,7 +179,7 @@
   {
    "cell_type": "code",
    "execution_count": 6,
-   "id": "37274b66",
+   "id": "8485029e",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -189,7 +189,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "064ceea9",
+   "id": "1749a9ae",
    "metadata": {},
    "source": [
     "## 8. Search for a list of AllWISE images that cover this galaxy\n",
@@ -200,7 +200,7 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "id": "88f40850",
+   "id": "a3986873",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -210,7 +210,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "b4ae6bef",
+   "id": "9904b26e",
    "metadata": {},
    "source": [
     "## 9. Use the .to_table() method to view the results as an Astropy table"
@@ -219,14 +219,14 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "4d2226fe",
+   "id": "35445580",
    "metadata": {},
    "outputs": [],
    "source": []
   },
   {
    "cell_type": "markdown",
-   "id": "ea59ee7c",
+   "id": "96e4b317",
    "metadata": {},
    "source": [
     "## 10. From the result in 8., select the first record for an image taken in WISE band W1 (3.6 micron)\n",
@@ -240,14 +240,14 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "99921f8c",
+   "id": "8bf0e4a8",
    "metadata": {},
    "outputs": [],
    "source": []
   },
   {
    "cell_type": "markdown",
-   "id": "dfb3b6c6",
+   "id": "59bf3b08",
    "metadata": {},
    "source": [
     "## 11. Visualize this AllWISE image\n",
@@ -258,7 +258,7 @@
   {
    "cell_type": "code",
    "execution_count": 8,
-   "id": "61369548",
+   "id": "789ab68d",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -270,7 +270,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "4ecc33d9",
+   "id": "e077cc6c",
    "metadata": {},
    "source": [
     "## 12. Plot a cutout of the AllWISE image, centered on your position\n",
@@ -281,7 +281,7 @@
   {
    "cell_type": "code",
    "execution_count": 9,
-   "id": "666f47dc",
+   "id": "dab2ce39",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -290,7 +290,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "abb51948",
+   "id": "11ea877c",
    "metadata": {},
    "source": [
     "## 13. Try visualizing a cutout of a GALEX image that covers your position\n",
@@ -301,7 +301,7 @@
   {
    "cell_type": "code",
    "execution_count": 10,
-   "id": "8e2fa5b7",
+   "id": "405712c1",
    "metadata": {
     "tags": [
      "output_scroll"
@@ -316,7 +316,7 @@
   {
    "cell_type": "code",
    "execution_count": 11,
-   "id": "e7d99140",
+   "id": "0e4fd1a9",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -327,7 +327,7 @@
   {
    "cell_type": "code",
    "execution_count": 12,
-   "id": "732af83f",
+   "id": "0c5d23b1",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -338,7 +338,7 @@
   {
    "cell_type": "code",
    "execution_count": 13,
-   "id": "2b17a42d",
+   "id": "13cca6dc",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -349,7 +349,7 @@
   {
    "cell_type": "code",
    "execution_count": 14,
-   "id": "02c764e4",
+   "id": "15b2e209",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -359,7 +359,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "c2a47ad8",
+   "id": "6f5ab272",
    "metadata": {},
    "source": [
     "## 14. Try visualizing a cutout of an SDSS image that covers your position\n",
@@ -374,7 +374,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "7383ff18",
+   "id": "57117d0a",
    "metadata": {},
    "source": [
     "(As a workaround to a bug in the SDSS service, pass `format=''` as an argument to the search() function when using the SDSS service.)"
@@ -383,7 +383,7 @@
   {
    "cell_type": "code",
    "execution_count": 15,
-   "id": "dd48b315",
+   "id": "609d2f3a",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -393,7 +393,7 @@
   {
    "cell_type": "code",
    "execution_count": 16,
-   "id": "fc8d6f21",
+   "id": "2a3cf97c",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -403,7 +403,7 @@
   {
    "cell_type": "code",
    "execution_count": 17,
-   "id": "bdd3d70b",
+   "id": "d4fb9ea7",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -413,7 +413,7 @@
   {
    "cell_type": "code",
    "execution_count": 18,
-   "id": "21a0ec7b",
+   "id": "15eeec0e",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -424,7 +424,7 @@
   {
    "cell_type": "code",
    "execution_count": 19,
-   "id": "3df4bbbf",
+   "id": "76719d7a",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -433,7 +433,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "5e587e44",
+   "id": "e4b8b858",
    "metadata": {},
    "source": [
     "## 15. Try looping over all positions and plotting multiwavelength cutouts\n",
@@ -443,7 +443,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ea993765",
+   "id": "15d26c07",
    "metadata": {},
    "source": [
     "Warning: this takes a long time to run!  You can limit it to the first three galaxies only, for example, for testing."
@@ -452,7 +452,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "d3fd0607",
+   "id": "adc71195",
    "metadata": {},
    "outputs": [],
    "source": []
diff --git a/_sources/content/use_case_notebooks/candidate_list_solution.ipynb b/_sources/content/use_case_notebooks/candidate_list_solution.ipynb
index 1558377..7f863f7 100644
--- a/_sources/content/use_case_notebooks/candidate_list_solution.ipynb
+++ b/_sources/content/use_case_notebooks/candidate_list_solution.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "56ce867a",
+   "id": "00e410ed",
    "metadata": {},
    "source": [
     "# Candidate List Solution\n",
@@ -14,7 +14,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "76c16fa1",
+   "id": "264ef8bd",
    "metadata": {},
    "source": [
     "## 1. Import the Python modules we'll be using"
@@ -23,7 +23,7 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "id": "28604ff3",
+   "id": "cc103b85",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -51,7 +51,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "28826b73",
+   "id": "1004430f",
    "metadata": {},
    "source": [
     "The next cell prepares the notebook to display our visualizations."
@@ -60,7 +60,7 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "id": "57a1d226",
+   "id": "9dd71661",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -69,7 +69,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "22b2b665",
+   "id": "2d5af247",
    "metadata": {},
    "source": [
     "## 2. Search NED for objects in this paper\n",
@@ -80,7 +80,7 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "id": "01f309a3",
+   "id": "5fde7e72",
    "metadata": {
     "tags": [
      "output_scroll"
@@ -102,7 +102,7 @@
      "data": {
       "text/html": [
        "<i>Table length=62</i>\n",
-       "<table id=\"table140616360887008-313595\" class=\"table-striped table-bordered table-condensed\">\n",
+       "<table id=\"table139897424905120-953511\" class=\"table-striped table-bordered table-condensed\">\n",
        "<thead><tr><th>idx</th><th>No.</th><th>Object Name</th><th>RA</th><th>DEC</th><th>Type</th><th>Velocity</th><th>Redshift</th><th>Redshift Flag</th><th>Magnitude and Filter</th><th>Separation</th><th>References</th><th>Notes</th><th>Photometry Points</th><th>Positions</th><th>Redshift Points</th><th>Diameter Points</th><th>Associations</th></tr></thead>\n",
        "<thead><tr><th></th><th></th><th></th><th>degrees</th><th>degrees</th><th></th><th>km / s</th><th></th><th></th><th></th><th>arcmin</th><th></th><th></th><th></th><th></th><th></th><th></th><th></th></tr></thead>\n",
        "<tr><td>0</td><td>1</td><td>WISEA J001550.14-100242.3</td><td>3.95892</td><td>-10.04511</td><td>G</td><td>52766.0</td><td>0.17601</td><td>SLS</td><td>17.5g</td><td>--</td><td>15</td><td>0</td><td>63</td><td>8</td><td>9</td><td>10</td><td>0</td></tr>\n",
@@ -190,14 +190,14 @@
        "    datatables: 'https://cdn.datatables.net/1.10.12/js/jquery.dataTables.min'\n",
        "}});\n",
        "require([\"datatables\"], function(){\n",
-       "    console.log(\"$('#table140616360887008-313595').dataTable()\");\n",
+       "    console.log(\"$('#table139897424905120-953511').dataTable()\");\n",
        "    \n",
        "jQuery.extend( jQuery.fn.dataTableExt.oSort, {\n",
        "    \"optionalnum-asc\": astropy_sort_num,\n",
        "    \"optionalnum-desc\": function (a,b) { return -astropy_sort_num(a, b); }\n",
        "});\n",
        "\n",
-       "    $('#table140616360887008-313595').dataTable({\n",
+       "    $('#table139897424905120-953511').dataTable({\n",
        "        order: [],\n",
        "        pageLength: 50,\n",
        "        lengthMenu: [[10, 25, 50, 100, 500, 1000, -1], [10, 25, 50, 100, 500, 1000, 'All']],\n",
@@ -223,7 +223,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "eb6d24f6",
+   "id": "aa3c4927",
    "metadata": {},
    "source": [
     "## 3. Filter the NED results\n",
@@ -234,7 +234,7 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "id": "8bdd02e6",
+   "id": "27a2a193",
    "metadata": {},
    "outputs": [
     {
@@ -308,7 +308,7 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "id": "bb5b3343",
+   "id": "c89cd579",
    "metadata": {
     "tags": [
      "output_scroll"
@@ -330,7 +330,7 @@
      "data": {
       "text/html": [
        "<i>Table length=53</i>\n",
-       "<table id=\"table140615424395584-268780\" class=\"table-striped table-bordered table-condensed\">\n",
+       "<table id=\"table139896471553360-93962\" class=\"table-striped table-bordered table-condensed\">\n",
        "<thead><tr><th>idx</th><th>No.</th><th>Object Name</th><th>RA</th><th>DEC</th><th>Type</th><th>Velocity</th><th>Redshift</th><th>Redshift Flag</th><th>Magnitude and Filter</th><th>Separation</th><th>References</th><th>Notes</th><th>Photometry Points</th><th>Positions</th><th>Redshift Points</th><th>Diameter Points</th><th>Associations</th></tr></thead>\n",
        "<thead><tr><th></th><th></th><th></th><th>degrees</th><th>degrees</th><th></th><th>km / s</th><th></th><th></th><th></th><th>arcmin</th><th></th><th></th><th></th><th></th><th></th><th></th><th></th></tr></thead>\n",
        "<tr><td>0</td><td>1</td><td>WISEA J001550.14-100242.3</td><td>3.95892</td><td>-10.04511</td><td>G</td><td>52766.0</td><td>0.17601</td><td>SLS</td><td>17.5g</td><td>--</td><td>15</td><td>0</td><td>63</td><td>8</td><td>9</td><td>10</td><td>0</td></tr>\n",
@@ -409,14 +409,14 @@
        "    datatables: 'https://cdn.datatables.net/1.10.12/js/jquery.dataTables.min'\n",
        "}});\n",
        "require([\"datatables\"], function(){\n",
-       "    console.log(\"$('#table140615424395584-268780').dataTable()\");\n",
+       "    console.log(\"$('#table139896471553360-93962').dataTable()\");\n",
        "    \n",
        "jQuery.extend( jQuery.fn.dataTableExt.oSort, {\n",
        "    \"optionalnum-asc\": astropy_sort_num,\n",
        "    \"optionalnum-desc\": function (a,b) { return -astropy_sort_num(a, b); }\n",
        "});\n",
        "\n",
-       "    $('#table140615424395584-268780').dataTable({\n",
+       "    $('#table139896471553360-93962').dataTable({\n",
        "        order: [],\n",
        "        pageLength: 50,\n",
        "        lengthMenu: [[10, 25, 50, 100, 500, 1000, -1], [10, 25, 50, 100, 500, 1000, 'All']],\n",
@@ -444,7 +444,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "503f1276",
+   "id": "e0a51f84",
    "metadata": {},
    "source": [
     "## 4. Search the NAVO Registry for image resources\n",
@@ -455,7 +455,7 @@
   {
    "cell_type": "code",
    "execution_count": 6,
-   "id": "5ed6fecc",
+   "id": "a51dc419",
    "metadata": {},
    "outputs": [
     {
@@ -469,7 +469,7 @@
      "data": {
       "text/html": [
        "<div><i>Table length=322</i>\n",
-       "<table id=\"table140615424398848\" class=\"table-striped table-bordered table-condensed\">\n",
+       "<table id=\"table139896471556672\" class=\"table-striped table-bordered table-condensed\">\n",
        "<thead><tr><th>ivoid</th><th>short_name</th><th>res_title</th></tr></thead>\n",
        "<thead><tr><th>object</th><th>object</th><th>object</th></tr></thead>\n",
        "<tr><td>ivo://3crsnapshots/sia</td><td>3CRSnap.sia</td><td>3CRSnapshots Simple Image Access Service</td></tr>\n",
@@ -536,7 +536,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f86bb692",
+   "id": "23df17bd",
    "metadata": {},
    "source": [
     "## 5. Search the NAVO Registry for image resources that will allow you to search for AllWISE images\n",
@@ -547,7 +547,7 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "id": "6e6c60d9",
+   "id": "6d643c99",
    "metadata": {},
    "outputs": [
     {
@@ -561,7 +561,7 @@
      "data": {
       "text/html": [
        "<div><i>Table length=1</i>\n",
-       "<table id=\"table140615419760016\" class=\"table-striped table-bordered table-condensed\">\n",
+       "<table id=\"table139896467564736\" class=\"table-striped table-bordered table-condensed\">\n",
        "<thead><tr><th>ivoid</th><th>short_name</th><th>res_title</th></tr></thead>\n",
        "<thead><tr><th>object</th><th>object</th><th>object</th></tr></thead>\n",
        "<tr><td>ivo://irsa.ipac/wise/images/allwise/l3a</td><td>AllWISE L3a</td><td>AllWISE Atlas (L3a) Coadd Images</td></tr>\n",
@@ -590,7 +590,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "d5e9962f",
+   "id": "fe0efe52",
    "metadata": {},
    "source": [
     "## 6. Choose the AllWISE image service that you are interested in"
@@ -599,7 +599,7 @@
   {
    "cell_type": "code",
    "execution_count": 8,
-   "id": "e39c08e4",
+   "id": "441375bb",
    "metadata": {},
    "outputs": [
     {
@@ -620,7 +620,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "427d1b44",
+   "id": "42061ddd",
    "metadata": {},
    "source": [
     "## 7. Choose one of the galaxies in the NED list"
@@ -629,7 +629,7 @@
   {
    "cell_type": "code",
    "execution_count": 9,
-   "id": "0381c7a9",
+   "id": "e9425a4b",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -641,7 +641,7 @@
   {
    "cell_type": "code",
    "execution_count": 10,
-   "id": "1a42204c",
+   "id": "8d4f674b",
    "metadata": {},
    "outputs": [
     {
@@ -661,7 +661,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "48e639d6",
+   "id": "97e72063",
    "metadata": {},
    "source": [
     "## 8. Search for a list of AllWISE images that cover this galaxy\n",
@@ -672,7 +672,7 @@
   {
    "cell_type": "code",
    "execution_count": 11,
-   "id": "723709de",
+   "id": "e40a3343",
    "metadata": {},
    "outputs": [
     {
@@ -701,7 +701,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ff1b0650",
+   "id": "286c10b5",
    "metadata": {},
    "source": [
     "## 9. Use the .to_table() method to view the results as an Astropy table"
@@ -710,14 +710,14 @@
   {
    "cell_type": "code",
    "execution_count": 12,
-   "id": "d1c78ba3",
+   "id": "cd97cb19",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
        "<div><i>Table length=4</i>\n",
-       "<table id=\"table140615420394752\" class=\"table-striped table-bordered table-condensed\">\n",
+       "<table id=\"table139896467668320\" class=\"table-striped table-bordered table-condensed\">\n",
        "<thead><tr><th>sia_title</th><th>sia_url</th><th>cloud_access</th><th>sia_naxes</th><th>sia_fmt</th><th>sia_ra</th><th>sia_dec</th><th>sia_naxis</th><th>sia_crpix</th><th>sia_crval</th><th>sia_proj</th><th>sia_scale</th><th>sia_cd</th><th>sia_bp_id</th><th>sia_bp_ref</th><th>sia_bp_hi</th><th>sia_bp_lo</th><th>sia_bp_unit</th><th>magzp</th><th>magzpunc</th><th>unc_url</th><th>cov_url</th><th>coadd_id</th></tr></thead>\n",
        "<thead><tr><th></th><th></th><th></th><th></th><th></th><th>deg</th><th>deg</th><th></th><th>pix</th><th>deg</th><th></th><th>deg / pix</th><th>deg / pix</th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th></tr></thead>\n",
        "<thead><tr><th>object</th><th>object</th><th>object</th><th>int32</th><th>object</th><th>float64</th><th>float64</th><th>int32[2]</th><th>float64[2]</th><th>float64[2]</th><th>object</th><th>float64[2]</th><th>float64[4]</th><th>object</th><th>float64</th><th>float64</th><th>float64</th><th>object</th><th>float64</th><th>float64</th><th>object</th><th>object</th><th>object</th></tr></thead>\n",
@@ -751,7 +751,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "fcdb494b",
+   "id": "ed0bf403",
    "metadata": {},
    "source": [
     "## 10. From the result in 8., select the first record for an image taken in WISE band W1 (3.6 micron)\n",
@@ -765,7 +765,7 @@
   {
    "cell_type": "code",
    "execution_count": 13,
-   "id": "df5b423f",
+   "id": "138252d2",
    "metadata": {},
    "outputs": [
     {
@@ -785,7 +785,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "9f69f083",
+   "id": "8a63dd27",
    "metadata": {},
    "source": [
     "## 11. Visualize this AllWISE image"
@@ -794,7 +794,7 @@
   {
    "cell_type": "code",
    "execution_count": 14,
-   "id": "ec68c96c",
+   "id": "a7918768",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -810,13 +810,13 @@
   {
    "cell_type": "code",
    "execution_count": 15,
-   "id": "b1104ecf",
+   "id": "f575e265",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<matplotlib.collections.PathCollection at 0x7fe393efe5f0>"
+       "<matplotlib.collections.PathCollection at 0x7f3c2f02df60>"
       ]
      },
      "execution_count": 15,
@@ -845,7 +845,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ea8d1585",
+   "id": "ba3889b8",
    "metadata": {},
    "source": [
     "## 12. Plot a cutout of the AllWISE image, centered on your position\n",
@@ -856,13 +856,13 @@
   {
    "cell_type": "code",
    "execution_count": 16,
-   "id": "acb51dcb",
+   "id": "6f66af69",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<matplotlib.collections.PathCollection at 0x7fe38bc7cc40>"
+       "<matplotlib.collections.PathCollection at 0x7f3c26d74220>"
       ]
      },
      "execution_count": 16,
@@ -894,7 +894,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "285b55f6",
+   "id": "e13993ab",
    "metadata": {},
    "source": [
     "## 13. Try visualizing a cutout of a GALEX image that covers your position\n",
@@ -905,7 +905,7 @@
   {
    "cell_type": "code",
    "execution_count": 17,
-   "id": "f805575b",
+   "id": "d1c3cb6d",
    "metadata": {},
    "outputs": [
     {
@@ -919,7 +919,7 @@
      "data": {
       "text/html": [
        "<div><i>Table length=3</i>\n",
-       "<table id=\"table140615279605264\" class=\"table-striped table-bordered table-condensed\">\n",
+       "<table id=\"table139896326421328\" class=\"table-striped table-bordered table-condensed\">\n",
        "<thead><tr><th>ivoid</th><th>short_name</th><th>res_title</th></tr></thead>\n",
        "<thead><tr><th>object</th><th>object</th><th>object</th></tr></thead>\n",
        "<tr><td>ivo://archive.stsci.edu/sia/galex</td><td>GALEX</td><td>Galaxy Evolution Explorer (GALEX)</td></tr>\n",
@@ -951,7 +951,7 @@
   {
    "cell_type": "code",
    "execution_count": 18,
-   "id": "9ad0326f",
+   "id": "6ea71e13",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -961,7 +961,7 @@
   {
    "cell_type": "code",
    "execution_count": 19,
-   "id": "bd0cad79",
+   "id": "84210ffa",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -971,14 +971,14 @@
   {
    "cell_type": "code",
    "execution_count": 20,
-   "id": "268fccd6",
+   "id": "febd5c93",
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "AIS_270_0004_sg14-nd-int.fits.gz NUV\n"
+      "AIS_270_sg14-nd-int.fits.gz NUV\n"
      ]
     }
    ],
@@ -995,7 +995,7 @@
   {
    "cell_type": "code",
    "execution_count": 21,
-   "id": "da8e6467",
+   "id": "42b07732",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1008,7 +1008,7 @@
   {
    "cell_type": "code",
    "execution_count": 22,
-   "id": "a79f460b",
+   "id": "b6d730e8",
    "metadata": {},
    "outputs": [
     {
@@ -1016,9 +1016,9 @@
      "output_type": "stream",
      "text": [
       "Min: 0.0\n",
-      "Max: 8.866534\n",
-      "Mean: 0.0014750387\n",
-      "Stdev: 0.013614772\n"
+      "Max: 7.1870303\n",
+      "Mean: 0.0014934327\n",
+      "Stdev: 0.012639926\n"
      ]
     }
    ],
@@ -1033,13 +1033,13 @@
   {
    "cell_type": "code",
    "execution_count": 23,
-   "id": "5e33e64f",
+   "id": "00ea5e58",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<matplotlib.collections.PathCollection at 0x7fe388a944c0>"
+       "<matplotlib.collections.PathCollection at 0x7f3c24b0efb0>"
       ]
      },
      "execution_count": 23,
@@ -1048,7 +1048,7 @@
     },
     {
      "data": {
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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -1067,13 +1067,13 @@
   {
    "cell_type": "code",
    "execution_count": 24,
-   "id": "c298bad3",
+   "id": "0f32a983",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<matplotlib.collections.PathCollection at 0x7fe38890cb50>"
+       "<matplotlib.collections.PathCollection at 0x7f3c24b90eb0>"
       ]
      },
      "execution_count": 24,
@@ -1082,7 +1082,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -1103,7 +1103,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a8a18b41",
+   "id": "6832fe52",
    "metadata": {},
    "source": [
     "## 14. Try visualizing a cutout of an SDSS image that covers your position\n",
@@ -1118,14 +1118,14 @@
   {
    "cell_type": "code",
    "execution_count": 25,
-   "id": "e2e295bb",
+   "id": "b162aab5",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
        "<div><i>Table length=21</i>\n",
-       "<table id=\"table140615227112848\" class=\"table-striped table-bordered table-condensed\">\n",
+       "<table id=\"table139896326417824\" class=\"table-striped table-bordered table-condensed\">\n",
        "<thead><tr><th>ivoid</th><th>short_name</th><th>res_title</th><th>source_value</th></tr></thead>\n",
        "<thead><tr><th>object</th><th>object</th><th>object</th><th>object</th></tr></thead>\n",
        "<tr><td>ivo://mast.stsci/siap/al218</td><td>VLA.AL218</td><td>VLA-A Array AL218 Texas Survey Source Snapshots (AL218)</td><td></td></tr>\n",
@@ -1192,7 +1192,7 @@
   {
    "cell_type": "code",
    "execution_count": 26,
-   "id": "d700bfe3",
+   "id": "cbe42804",
    "metadata": {},
    "outputs": [
     {
@@ -1216,7 +1216,7 @@
   {
    "cell_type": "code",
    "execution_count": 27,
-   "id": "e56e554c",
+   "id": "e37cebdf",
    "metadata": {},
    "outputs": [
     {
@@ -1238,7 +1238,7 @@
   {
    "cell_type": "code",
    "execution_count": 28,
-   "id": "b63db100",
+   "id": "09dbe9d4",
    "metadata": {},
    "outputs": [
     {
@@ -1259,7 +1259,7 @@
   {
    "cell_type": "code",
    "execution_count": 29,
-   "id": "3e549cb5",
+   "id": "740c6598",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1272,7 +1272,7 @@
   {
    "cell_type": "code",
    "execution_count": 30,
-   "id": "a58bf36a",
+   "id": "86870fb2",
    "metadata": {},
    "outputs": [
     {
@@ -1285,7 +1285,7 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.collections.PathCollection at 0x7fe3889e3e80>"
+       "<matplotlib.collections.PathCollection at 0x7f3c24abb3d0>"
       ]
      },
      "execution_count": 30,
@@ -1318,7 +1318,7 @@
   {
    "cell_type": "code",
    "execution_count": 31,
-   "id": "582660a8",
+   "id": "6adace5d",
    "metadata": {},
    "outputs": [
     {
@@ -1331,7 +1331,7 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.collections.PathCollection at 0x7fe388864580>"
+       "<matplotlib.collections.PathCollection at 0x7f3c24ae89a0>"
       ]
      },
      "execution_count": 31,
@@ -1361,7 +1361,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a996c0ff",
+   "id": "213d7952",
    "metadata": {},
    "source": [
     "## 15. Try looping over all positions and plotting multiwavelength cutouts"
@@ -1369,7 +1369,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "bb2d47a0",
+   "id": "b56057d1",
    "metadata": {},
    "source": [
     "Warning: this cell takes a long time to run! We limit it to the first three galaxies only."
@@ -1378,7 +1378,7 @@
   {
    "cell_type": "code",
    "execution_count": 32,
-   "id": "24653bf6",
+   "id": "72539ac1",
    "metadata": {},
    "outputs": [
     {
@@ -1404,7 +1404,7 @@
     },
     {
      "data": {
-      "image/png": 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",
       "text/plain": [
        "<Figure size 2000x600 with 3 Axes>"
       ]
diff --git a/_sources/content/use_case_notebooks/hr_diagram_exercise.ipynb b/_sources/content/use_case_notebooks/hr_diagram_exercise.ipynb
index 8ff9159..0c713de 100644
--- a/_sources/content/use_case_notebooks/hr_diagram_exercise.ipynb
+++ b/_sources/content/use_case_notebooks/hr_diagram_exercise.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "ffb85a5d",
+   "id": "4c52077e",
    "metadata": {},
    "source": [
     "# HR (Hertzsprung-Russell) Diagram Exercise\n",
@@ -15,7 +15,7 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "id": "87fe162c",
+   "id": "8dbeda98",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -41,7 +41,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "3e249f0d",
+   "id": "efd72612",
    "metadata": {},
    "source": [
     "## Step 1: Find appropriate catalogs\n",
@@ -53,7 +53,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "96203748",
+   "id": "729fccb7",
    "metadata": {},
    "source": [
     "### DATA DISCOVERY STEPS\n",
@@ -64,7 +64,7 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "id": "6231e40d",
+   "id": "7b8b0053",
    "metadata": {
     "tags": [
      "output_scroll"
@@ -83,7 +83,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "6190961d",
+   "id": "e6bd1040",
    "metadata": {},
    "source": [
     "Note: The includeaux=True includes auxiliary services.\n",
@@ -93,7 +93,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "57c930df",
+   "id": "12e0edc9",
    "metadata": {},
    "source": [
     "#### Next, we need to find which of these has the columns of interest, i.e. magnitudes in two bands to create the color-magnitude diagram\n",
@@ -104,7 +104,7 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "id": "91e03cbb",
+   "id": "4bf69326",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -117,7 +117,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ff9b0909",
+   "id": "e5717d4e",
    "metadata": {},
    "source": [
     "Note: the '%' serves as a wild card when searching by UCD\n",
@@ -127,7 +127,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "5ac3da1a",
+   "id": "2bd0aefa",
    "metadata": {},
    "source": [
     "So using this we can reduce the matched tables to ones that are a bit more catered to our experiment. Note, that there is redundancy in some resources since these are available via multiple services and/or publishers. Therefore a bit more cleaning can be done to provide only the unique matches."
@@ -136,7 +136,7 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "id": "8caa1abd",
+   "id": "bebc629e",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -146,7 +146,7 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "id": "6f546b5f",
+   "id": "12890f91",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -156,7 +156,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "8dc8c745",
+   "id": "be77d5dc",
    "metadata": {},
    "source": [
     "We can read more information about the results we found.  For each resource element (i.e. row in the table above), there are useful attributes, which are [described here]( https://pyvo.readthedocs.io/en/latest/api/pyvo.registry.regtap.RegistryResource.html#pyvo.registry.regtap.RegistryResource)"
@@ -165,7 +165,7 @@
   {
    "cell_type": "code",
    "execution_count": 6,
-   "id": "038b1b6b",
+   "id": "c3348372",
    "metadata": {
     "tags": [
      "output_scroll"
@@ -178,7 +178,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "3ea3e656",
+   "id": "c756a995",
    "metadata": {},
    "source": [
     "<i> RESULT: Based on these, the second one (by Eichhorn et al) looks like a good start. </i>\n",
@@ -192,7 +192,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "56fa05bc",
+   "id": "1fa84001",
    "metadata": {
     "tags": [
      "output_scroll"
@@ -219,7 +219,7 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "id": "b3ac643d",
+   "id": "4f527521",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -228,7 +228,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "68a2b8d5",
+   "id": "08f8cba4",
    "metadata": {},
    "source": [
     "First, Try using bibcode:"
@@ -237,7 +237,7 @@
   {
    "cell_type": "code",
    "execution_count": 8,
-   "id": "4c1be898",
+   "id": "9f49da63",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -255,7 +255,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "51f0ce98",
+   "id": "5bab100f",
    "metadata": {},
    "source": [
     "Note that the URL is a generic TAP url for Vizier.  All of its tables can be accessed by that same TAP services.  It'll be in the ADQL query itself that you specify the table name.  We'll see this below."
@@ -263,7 +263,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "52bc0de6",
+   "id": "886226d6",
    "metadata": {},
    "source": [
     "Next, try using Author name:"
@@ -272,7 +272,7 @@
   {
    "cell_type": "code",
    "execution_count": 9,
-   "id": "cf7febb0",
+   "id": "98ee4b4f",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -288,7 +288,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "873c2e58",
+   "id": "9934658a",
    "metadata": {},
    "source": [
     "These examples provide a few ways to access the information of interest.\n",
@@ -303,7 +303,7 @@
   {
    "cell_type": "code",
    "execution_count": 10,
-   "id": "73df8d26",
+   "id": "05ab2e76",
    "metadata": {
     "tags": [
      "output_scroll"
@@ -316,7 +316,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "bb78bb24",
+   "id": "83ea8678",
    "metadata": {},
    "source": [
     "## Step 2: Acquire the relevant data and make a plot\n",
@@ -327,7 +327,7 @@
   {
    "cell_type": "code",
    "execution_count": 11,
-   "id": "ab60a294",
+   "id": "f169cab5",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -337,7 +337,7 @@
   {
    "cell_type": "code",
    "execution_count": 12,
-   "id": "1927e869",
+   "id": "5269ace1",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -347,7 +347,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "e14773dd",
+   "id": "9d2af0b0",
    "metadata": {},
    "source": [
     "We can access the column data as array using the .getcolumn(colname) attribute, where the colname is given in the table above. In particular the \"CI\" is the color index and \"Ptm\" is the photovisual magnitude. See [here](https://vizier.u-strasbg.fr/viz-bin/VizieR?-source=I/90) for details about the columns."
@@ -356,7 +356,7 @@
   {
    "cell_type": "code",
    "execution_count": 13,
-   "id": "25cec826",
+   "id": "020c45b1",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -366,7 +366,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "acb5765e",
+   "id": "c10473bb",
    "metadata": {},
    "source": [
     "### Plotting\n",
@@ -377,7 +377,7 @@
   {
    "cell_type": "code",
    "execution_count": 14,
-   "id": "c6270742",
+   "id": "eb936a5e",
    "metadata": {},
    "outputs": [
     {
@@ -411,7 +411,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "09e13dfd",
+   "id": "df552705",
    "metadata": {},
    "source": [
     "## Step 3. Compare with other color-magnitude diagrams for Pleiades\n",
@@ -426,7 +426,7 @@
   {
    "cell_type": "code",
    "execution_count": 15,
-   "id": "e909ccaa",
+   "id": "5d078b14",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -439,7 +439,7 @@
   {
    "cell_type": "code",
    "execution_count": 16,
-   "id": "5df62167",
+   "id": "6866b1f7",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -450,7 +450,7 @@
   {
    "cell_type": "code",
    "execution_count": 17,
-   "id": "089c37d6",
+   "id": "a565244b",
    "metadata": {},
    "outputs": [
     {
@@ -487,7 +487,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "16e55925",
+   "id": "83e5087f",
    "metadata": {},
    "source": [
     "## BONUS: Step 4: The CMD as a distance indicator\n",
@@ -498,7 +498,7 @@
   {
    "cell_type": "code",
    "execution_count": 18,
-   "id": "42f6d959",
+   "id": "7ac1f123",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -516,7 +516,7 @@
   {
    "cell_type": "code",
    "execution_count": 19,
-   "id": "cb9f1637",
+   "id": "7420d14c",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -530,7 +530,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "52810bce",
+   "id": "dca0e32b",
    "metadata": {},
    "source": [
     "True distance to Pleaides is 136.2 pc  (<https://en.wikipedia.org/wiki/Pleiades> ). Not bad!"
diff --git a/_sources/content/use_case_notebooks/hr_diagram_solution.ipynb b/_sources/content/use_case_notebooks/hr_diagram_solution.ipynb
index 269d7e0..2d14a08 100644
--- a/_sources/content/use_case_notebooks/hr_diagram_solution.ipynb
+++ b/_sources/content/use_case_notebooks/hr_diagram_solution.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "d160a48d",
+   "id": "fc8da283",
    "metadata": {},
    "source": [
     "# HR (Hertzsprung-Russell) Diagram Solution\n",
@@ -15,7 +15,7 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "id": "7c1d8da1",
+   "id": "e050273e",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -41,7 +41,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "cad2b1dc",
+   "id": "d6d17918",
    "metadata": {},
    "source": [
     "## Step 1: Find appropriate catalogs\n",
@@ -53,7 +53,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "624dfe68",
+   "id": "ff971109",
    "metadata": {},
    "source": [
     "### DATA DISCOVERY STEPS\n",
@@ -64,7 +64,7 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "id": "832ccbae",
+   "id": "95a8012e",
    "metadata": {
     "tags": [
      "output_scroll"
@@ -82,7 +82,7 @@
      "data": {
       "text/html": [
        "<div><i>Table length=145</i>\n",
-       "<table id=\"table140501670873648\" class=\"table-striped table-bordered table-condensed\">\n",
+       "<table id=\"table139869975185968\" class=\"table-striped table-bordered table-condensed\">\n",
        "<thead><tr><th>index</th><th>short_name</th><th>title</th><th>description</th><th>interfaces</th></tr></thead>\n",
        "<thead><tr><th>int64</th><th>str16</th><th>str55</th><th>str4800</th><th>str7</th></tr></thead>\n",
        "<tr><td>0</td><td>I/163</td><td>US Naval Observatory Pleiades Catalog</td><td>This catalog is a special subset of the Eichhorn et al. (1970) Pleiades catalog (see &lt;I/90&gt;) updated to B1950.0 positions and with proper motions added. It was prepared for the purpose of predicting occultations of Pleiades stars by the Moon, but is useful for general applications because it contains many faint stars not present in the current series of large astrometric catalogs.</td><td>tap#aux</td></tr>\n",
@@ -147,7 +147,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "86131ce0",
+   "id": "b4bf9954",
    "metadata": {},
    "source": [
     "Note: The includeaux=True includes auxiliary services.\n",
@@ -157,7 +157,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "b71a0cc5",
+   "id": "b0daedfa",
    "metadata": {},
    "source": [
     "#### Next, we need to find which of these has the columns of interest, i.e. magnitudes in two bands to create the color-magnitude diagram\n",
@@ -168,7 +168,7 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "id": "c85be7e2",
+   "id": "4fc72402",
    "metadata": {
     "tags": [
      "output_scroll"
@@ -191,7 +191,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "af2c196e",
+   "id": "72a921b2",
    "metadata": {},
    "source": [
     "Note: the '%' serves as a wild card when searching by UCD\n",
@@ -201,7 +201,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "fbb3d0f3",
+   "id": "fcb17c63",
    "metadata": {
     "tags": [
      "output_scroll"
@@ -214,7 +214,7 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "id": "04630bce",
+   "id": "553ba3ba",
    "metadata": {
     "tags": [
      "output_scroll"
@@ -292,7 +292,7 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "id": "aefe5e31",
+   "id": "fe0df9b8",
    "metadata": {
     "tags": [
      "output_scroll"
@@ -317,7 +317,7 @@
   {
    "cell_type": "code",
    "execution_count": 6,
-   "id": "23fb0e06",
+   "id": "da755d65",
    "metadata": {
     "tags": [
      "output_scroll"
@@ -340,7 +340,7 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "id": "c3ce41b1",
+   "id": "e23992a5",
    "metadata": {
     "tags": [
      "output_scroll"
@@ -417,7 +417,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "c116031c",
+   "id": "ed171ef0",
    "metadata": {
     "tags": [
      "output_scroll"
@@ -429,7 +429,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "218e69f2",
+   "id": "ddc4b68b",
    "metadata": {},
    "source": [
     "We can read more information about the results we found.  For each resource element (i.e. row in the table above), there are useful attributes, which are [described here]( https://pyvo.readthedocs.io/en/latest/api/pyvo.registry.regtap.RegistryResource.html#pyvo.registry.regtap.RegistryResource)"
@@ -438,7 +438,7 @@
   {
    "cell_type": "code",
    "execution_count": 8,
-   "id": "b58ce868",
+   "id": "b647cdf3",
    "metadata": {
     "tags": [
      "output_scroll"
@@ -843,7 +843,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "7174ce74",
+   "id": "9de638b9",
    "metadata": {
     "tags": [
      "output_scroll"
@@ -861,7 +861,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "4c6f534f",
+   "id": "360550d8",
    "metadata": {
     "tags": [
      "output_scroll"
@@ -888,7 +888,7 @@
   {
    "cell_type": "code",
    "execution_count": 9,
-   "id": "75dbafce",
+   "id": "4ee23a63",
    "metadata": {},
    "outputs": [
     {
@@ -908,7 +908,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "354f3f0e",
+   "id": "40814299",
    "metadata": {},
    "source": [
     "First, Try using bibcode:"
@@ -917,7 +917,7 @@
   {
    "cell_type": "code",
    "execution_count": 10,
-   "id": "875c7c88",
+   "id": "7f5abdba",
    "metadata": {},
    "outputs": [
     {
@@ -946,7 +946,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "0c3f487b",
+   "id": "0d38d35e",
    "metadata": {},
    "source": [
     "Note that the URL is a generic TAP url for Vizier.  All of its tables can be accessed by that same TAP services.  It'll be in the ADQL query itself that you specify the table name.  We'll see this below."
@@ -954,7 +954,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "7bb25c69",
+   "id": "9ed902bd",
    "metadata": {},
    "source": [
     "Next, try using Author name:"
@@ -963,7 +963,7 @@
   {
    "cell_type": "code",
    "execution_count": 11,
-   "id": "26f7742a",
+   "id": "c0120890",
    "metadata": {
     "tags": [
      "output_scroll"
@@ -993,7 +993,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "46834c70",
+   "id": "b974132f",
    "metadata": {},
    "source": [
     "In the code above, the record is a Registry Resource. You can access the attribute, \"creators\", from the resource, which is relevant for our example here since this is a direct way to get the author names. The other attributes, \"access_url\" and \"reference_url\", provides two types of URLs. The former can be used to access the service resource (as described above) and the latter points to a human-readable document describing this resource.\n",
@@ -1007,7 +1007,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "09a94249",
+   "id": "0cf453f6",
    "metadata": {},
    "source": [
     "These examples provide a few ways to access the information of interest.\n",
@@ -1022,7 +1022,7 @@
   {
    "cell_type": "code",
    "execution_count": 12,
-   "id": "5e1b5efd",
+   "id": "4fe9a977",
    "metadata": {
     "tags": [
      "output_scroll"
@@ -1044,7 +1044,7 @@
   {
    "cell_type": "code",
    "execution_count": 13,
-   "id": "aec81455",
+   "id": "aef749fe",
    "metadata": {
     "tags": [
      "output_scroll"
@@ -1085,7 +1085,7 @@
   {
    "cell_type": "code",
    "execution_count": 14,
-   "id": "b13d5fcc",
+   "id": "44be7544",
    "metadata": {
     "tags": [
      "output_scroll"
@@ -3878,7 +3878,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "d4501c93",
+   "id": "3214fe0a",
    "metadata": {
     "tags": [
      "output_scroll"
@@ -3893,7 +3893,7 @@
   {
    "cell_type": "code",
    "execution_count": 15,
-   "id": "9defa61d",
+   "id": "d5ffc00c",
    "metadata": {
     "tags": [
      "output_scroll"
@@ -3926,7 +3926,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "d93cdefb",
+   "id": "c0a2e47f",
    "metadata": {
     "tags": [
      "output_scroll"
@@ -3941,7 +3941,7 @@
   {
    "cell_type": "code",
    "execution_count": 16,
-   "id": "6124163c",
+   "id": "aa2edfb0",
    "metadata": {
     "tags": [
      "output_scroll"
@@ -3967,7 +3967,7 @@
   {
    "cell_type": "code",
    "execution_count": 17,
-   "id": "b419eb5d",
+   "id": "053f6783",
    "metadata": {
     "tags": [
      "output_scroll"
@@ -3985,7 +3985,7 @@
      "data": {
       "text/html": [
        "<div><i>Table length=502</i>\n",
-       "<table id=\"table140501618972448\" class=\"table-striped table-bordered table-condensed\">\n",
+       "<table id=\"table139869420331088\" class=\"table-striped table-bordered table-condensed\">\n",
        "<thead><tr><th>recno</th><th>Hertzsprung</th><th>CI</th><th>Ptm</th><th>RAB1900</th><th>e_RAB1900</th><th>DEB1900</th><th>e_DEB1900</th><th>rmsRA</th><th>rmsDE</th><th>rpmRA</th><th>rpmDE</th><th>DrpmRA</th><th>DrpmDE</th><th>DRA</th><th>DDE</th><th>_RA_icrs</th><th>_DE_icrs</th></tr></thead>\n",
        "<thead><tr><th></th><th></th><th>mag</th><th>mag</th><th>deg</th><th>ms</th><th>deg</th><th>mas</th><th></th><th></th><th>mas / yr</th><th>mas / yr</th><th>mas / yr</th><th>mas / yr</th><th>arcsec</th><th>arcsec</th><th>deg</th><th>deg</th></tr></thead>\n",
        "<thead><tr><th>int32</th><th>int16</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>int16</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th></tr></thead>\n",
@@ -4051,7 +4051,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "92a18b66",
+   "id": "9c92d67b",
    "metadata": {},
    "source": [
     "We can access the column data as array using the .getcolumn(colname) attribute, where the colname is given in the table above. In particular the \"CI\" is the color index and \"Ptm\" is the photovisual magnitude. See [here](https://vizier.u-strasbg.fr/viz-bin/VizieR?-source=I/90) for details about the columns."
@@ -4060,7 +4060,7 @@
   {
    "cell_type": "code",
    "execution_count": 18,
-   "id": "3a53485b",
+   "id": "37efea2e",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -4070,7 +4070,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "92e14153",
+   "id": "45488aec",
    "metadata": {},
    "source": [
     "### Plotting\n",
@@ -4081,13 +4081,13 @@
   {
    "cell_type": "code",
    "execution_count": 19,
-   "id": "b72adc0c",
+   "id": "e00e363b",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "[<matplotlib.lines.Line2D at 0x7fc909d17850>]"
+       "[<matplotlib.lines.Line2D at 0x7f35e2d33850>]"
       ]
      },
      "execution_count": 19,
@@ -4115,7 +4115,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "26f3deac",
+   "id": "b62d2926",
    "metadata": {},
    "source": [
     "## Step 3. Compare with other color-magnitude diagrams for Pleiades\n",
@@ -4130,7 +4130,7 @@
   {
    "cell_type": "code",
    "execution_count": 20,
-   "id": "39ef5fb0",
+   "id": "6effa2d4",
    "metadata": {},
    "outputs": [
     {
@@ -4168,7 +4168,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/tmp/ipykernel_2183/2733767379.py:11: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n",
+      "/tmp/ipykernel_2098/2733767379.py:11: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n",
       "  ind = int(match[0])\n"
      ]
     }
@@ -4192,7 +4192,7 @@
   {
    "cell_type": "code",
    "execution_count": 21,
-   "id": "26e2874b",
+   "id": "d1ec2cb6",
    "metadata": {
     "tags": [
      "output_scroll"
@@ -4210,7 +4210,7 @@
      "data": {
       "text/html": [
        "<div><i>Table length=270</i>\n",
-       "<table id=\"table140501499757472\" class=\"table-striped table-bordered table-condensed\">\n",
+       "<table id=\"table139869585245808\" class=\"table-striped table-bordered table-condensed\">\n",
        "<thead><tr><th>recno</th><th>HII</th><th>Vmag</th><th>B-V</th><th>xpos</th><th>ypos</th><th>Dist</th><th>Mult</th><th>Rem</th><th>Mass</th><th>MassA</th><th>MassB</th><th>MassC</th><th>MassD</th></tr></thead>\n",
        "<thead><tr><th></th><th></th><th>mag</th><th>mag</th><th>arcmin</th><th>arcmin</th><th>arcmin</th><th></th><th></th><th>Msun</th><th>Msun</th><th>Msun</th><th>Msun</th><th>Msun</th></tr></thead>\n",
        "<thead><tr><th>int32</th><th>int32</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>int16</th><th>object</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th></tr></thead>\n",
@@ -4294,13 +4294,13 @@
   {
    "cell_type": "code",
    "execution_count": 22,
-   "id": "904bf59d",
+   "id": "2eb5df49",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "[<matplotlib.lines.Line2D at 0x7fc9152fa8c0>]"
+       "[<matplotlib.lines.Line2D at 0x7f35ee1203d0>]"
       ]
      },
      "execution_count": 22,
@@ -4331,7 +4331,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "cce17a05",
+   "id": "4f75e703",
    "metadata": {},
    "source": [
     "## BONUS: Step 4: The CMD as a distance indicator\n",
@@ -4342,13 +4342,13 @@
   {
    "cell_type": "code",
    "execution_count": 23,
-   "id": "60e73cc1",
+   "id": "691a5db6",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "[<matplotlib.lines.Line2D at 0x7fc9151fcc10>]"
+       "[<matplotlib.lines.Line2D at 0x7f35e3110d60>]"
       ]
      },
      "execution_count": 23,
@@ -4384,7 +4384,7 @@
   {
    "cell_type": "code",
    "execution_count": 24,
-   "id": "f449b6d6",
+   "id": "62667990",
    "metadata": {},
    "outputs": [
     {
@@ -4407,7 +4407,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "8fd86191",
+   "id": "306a9920",
    "metadata": {},
    "source": [
     "True distance to Pleaides is 136.2 pc ( <https://en.wikipedia.org/wiki/Pleiades> ). Not bad!"
diff --git a/_sources/content/use_case_notebooks/proposal_prep_exercise.ipynb b/_sources/content/use_case_notebooks/proposal_prep_exercise.ipynb
index 516e526..abc7ca5 100644
--- a/_sources/content/use_case_notebooks/proposal_prep_exercise.ipynb
+++ b/_sources/content/use_case_notebooks/proposal_prep_exercise.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "98b232c6",
+   "id": "5ce79e0f",
    "metadata": {},
    "source": [
     "# Proposal Preparation Exercise\n",
@@ -15,7 +15,7 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "id": "4b9afd69",
+   "id": "8942a8d2",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -40,7 +40,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "487bb61a",
+   "id": "3a61b7bd",
    "metadata": {},
    "source": [
     "## Step 1: Find out what the previously quoted Chandra 2-10 keV flux of the central source is for NGC 1365\n",
@@ -51,7 +51,7 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "id": "482e5cfa",
+   "id": "27c86e84",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -69,7 +69,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "2ff14e44",
+   "id": "ed480559",
    "metadata": {},
    "source": [
     "Hint: The Chansngcat ( <https://heasarc.gsfc.nasa.gov/W3Browse/chandra/chansngcat.html> ) table is likely the best table.  Create a table with ra, dec, exposure time, and flux (and flux errors) from the public.chansngcat catalog for Chandra observations matched within 0.1 degree."
@@ -78,7 +78,7 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "id": "a571909f",
+   "id": "8114bc93",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -88,7 +88,7 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "id": "0f6a77d8",
+   "id": "32143022",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -106,7 +106,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "8388c224",
+   "id": "d628b117",
    "metadata": {},
    "source": [
     "## Step 2: Make Images\n",
@@ -119,7 +119,7 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "id": "05cae2c0",
+   "id": "6f948734",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -128,7 +128,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "9e314355",
+   "id": "b7fe0589",
    "metadata": {},
    "source": [
     "The keyword search for 'galex' returned a bunch of things that may have mentioned it, but let's just use the ones that have GALEX as their short name:"
@@ -137,7 +137,7 @@
   {
    "cell_type": "code",
    "execution_count": 6,
-   "id": "beb2787b",
+   "id": "10f9c62f",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -146,7 +146,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ccaa10de",
+   "id": "578c76b3",
    "metadata": {},
    "source": [
     "Though using the result as an Astropy Table makes it easier to look at the contents, to call the service itself, we cannot use the row of that table.  You have to use the entry in the service result list itself.  So use the table to browse, but select the list of services itself using the properties that have been defined as attributes such as short_name and ivoid:"
@@ -155,7 +155,7 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "id": "cbddac00",
+   "id": "457e3948",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -164,7 +164,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "cc425a73",
+   "id": "58945d2e",
    "metadata": {},
    "source": [
     "Hint: Next create a UV image for the source"
@@ -173,7 +173,7 @@
   {
    "cell_type": "code",
    "execution_count": 8,
-   "id": "dd6d8dae",
+   "id": "94679a12",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -186,7 +186,7 @@
   {
    "cell_type": "code",
    "execution_count": 9,
-   "id": "ac07e9d5",
+   "id": "bd1cdac0",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -198,7 +198,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a0d3a855",
+   "id": "923a06ef",
    "metadata": {},
    "source": [
     "Hint: Repeat steps for X-ray image. (Note: Ideally, we would find an image in the Chandra 'cxc' catalog)"
@@ -207,14 +207,14 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "5fcb8c3f",
+   "id": "26076694",
    "metadata": {},
    "outputs": [],
    "source": []
   },
   {
    "cell_type": "markdown",
-   "id": "bb5fd28f",
+   "id": "7e776f1a",
    "metadata": {},
    "source": [
     "## Step 3: Make a spectrum\n",
@@ -227,7 +227,7 @@
   {
    "cell_type": "code",
    "execution_count": 10,
-   "id": "973fa270",
+   "id": "52ec55cb",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -236,7 +236,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "e314fdfc",
+   "id": "f0797e10",
    "metadata": {},
    "source": [
     "Hint 2: Take a look at what data exist for our candidate, NGC 1365."
@@ -245,14 +245,14 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "99c8a628",
+   "id": "b0514490",
    "metadata": {},
    "outputs": [],
    "source": []
   },
   {
    "cell_type": "markdown",
-   "id": "71b6e752",
+   "id": "134ed0f1",
    "metadata": {},
    "source": [
     "Hint 3: Download the data to make a spectrum. Note: you might end here and use Xspec to plot and model the spectrum. Or ... you can also try to take a quick look at the spectrum."
@@ -261,7 +261,7 @@
   {
    "cell_type": "code",
    "execution_count": 11,
-   "id": "f81c4fba",
+   "id": "7184dfbb",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -271,7 +271,7 @@
   {
    "cell_type": "code",
    "execution_count": 12,
-   "id": "ebfd6040",
+   "id": "9e8b936f",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -280,7 +280,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f1c669ab",
+   "id": "7f2b3add",
    "metadata": {},
    "source": [
     "Extension: Making a \"quick look\" spectrum. For our purposes, the 1st order of the HEG grating data would be sufficient."
@@ -289,7 +289,7 @@
   {
    "cell_type": "code",
    "execution_count": 13,
-   "id": "22ad2545",
+   "id": "6320a9cf",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -298,7 +298,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "8b179f45",
+   "id": "a5e87afc",
    "metadata": {},
    "source": [
     "This can then be analyzed in your favorite spectral analysis tool, e.g., [pyXspec](https://heasarc.gsfc.nasa.gov/xanadu/xspec/python/html/index.html).  (For the winter 2018 AAS workshop, we demonstrated this in a [notebook](https://github.com/NASA-NAVO/aas_workshop_2018/blob/master/heasarc/heasarc_Spectral_Access.md) that you can consult for how to use pyXspec, but the pyXspec documentation will have more information.)"
@@ -306,7 +306,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "022b46fa",
+   "id": "2df8381a",
    "metadata": {},
    "source": [
     "Congratulations! You have completed this notebook exercise."
diff --git a/_sources/content/use_case_notebooks/proposal_prep_solution.ipynb b/_sources/content/use_case_notebooks/proposal_prep_solution.ipynb
index 7db539f..ff6ee1e 100644
--- a/_sources/content/use_case_notebooks/proposal_prep_solution.ipynb
+++ b/_sources/content/use_case_notebooks/proposal_prep_solution.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "3771579d",
+   "id": "1990e058",
    "metadata": {},
    "source": [
     "# Proposal Preparation Solution\n",
@@ -15,7 +15,7 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "id": "6e7e46c5",
+   "id": "6ef7e88e",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -40,7 +40,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "579c960d",
+   "id": "fcd54f27",
    "metadata": {},
    "source": [
     "## Step 1: Find out what the previously quoted Chandra 2-10 keV flux of the central source is for NGC 1365\n",
@@ -51,7 +51,7 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "id": "d7c469c6",
+   "id": "e8bbef1c",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -63,7 +63,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "6e6b6ee1",
+   "id": "ad5a7164",
    "metadata": {},
    "source": [
     "Hint: The [Chansngcat](https://heasarc.gsfc.nasa.gov/W3Browse/chandra/chansngcat.html) table is likely the best table.  Create a table with ra, dec, exposure time, and flux (and flux errors) from the public.chansngcat catalog for Chandra observations matched within 0.1 degree."
@@ -72,7 +72,7 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "id": "b7321cb4",
+   "id": "f1e9e6ec",
    "metadata": {},
    "outputs": [
     {
@@ -95,7 +95,7 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "id": "4186ae26",
+   "id": "ad878e9c",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -107,14 +107,14 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "id": "4f123cdc",
+   "id": "833c78f0",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
        "<div><i>Table length=1</i>\n",
-       "<table id=\"table140562959449488\" class=\"table-striped table-bordered table-condensed\">\n",
+       "<table id=\"table140186459581328\" class=\"table-striped table-bordered table-condensed\">\n",
        "<thead><tr><th>ra</th><th>dec</th><th>exposure</th><th>flux</th><th>flux_lower</th><th>flux_upper</th></tr></thead>\n",
        "<thead><tr><th>deg</th><th>deg</th><th>s</th><th>erg/s/cm^2</th><th>erg/s/cm^2</th><th>erg/s/cm^2</th></tr></thead>\n",
        "<thead><tr><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th></tr></thead>\n",
@@ -151,7 +151,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "de3df276",
+   "id": "b6241419",
    "metadata": {},
    "source": [
     "## Step 2: Make Images\n",
@@ -164,14 +164,14 @@
   {
    "cell_type": "code",
    "execution_count": 6,
-   "id": "8896402c",
+   "id": "06c76883",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
        "<div><i>Table length=3</i>\n",
-       "<table id=\"table140562901582416\" class=\"table-striped table-bordered table-condensed\">\n",
+       "<table id=\"table140186403157664\" class=\"table-striped table-bordered table-condensed\">\n",
        "<thead><tr><th>ivoid</th><th>short_name</th></tr></thead>\n",
        "<thead><tr><th>object</th><th>object</th></tr></thead>\n",
        "<tr><td>ivo://archive.stsci.edu/sia/galex</td><td>GALEX</td></tr>\n",
@@ -202,7 +202,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "9813db86",
+   "id": "16e809cb",
    "metadata": {},
    "source": [
     "The keyword search for 'galex' returned a bunch of things that may have mentioned it, but let's just use the ones that have GALEX as their short name:"
@@ -211,14 +211,14 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "id": "99263057",
+   "id": "d9594fd5",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
        "<div><i>Table length=3</i>\n",
-       "<table id=\"table140562998488768\" class=\"table-striped table-bordered table-condensed\">\n",
+       "<table id=\"table140186403334672\" class=\"table-striped table-bordered table-condensed\">\n",
        "<thead><tr><th>ivoid</th><th>short_name</th></tr></thead>\n",
        "<thead><tr><th>object</th><th>object</th></tr></thead>\n",
        "<tr><td>ivo://archive.stsci.edu/sia/galex</td><td>GALEX</td></tr>\n",
@@ -249,7 +249,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f0cec99c",
+   "id": "f32c751d",
    "metadata": {},
    "source": [
     "Though using the result as an Astropy Table makes it easier to look at the contents, to call the service itself, we cannot use the row of that table.  You have to use the entry in the service result list itself.  So use the table to browse, but select the list of services itself using the properties that have been defined as attributes such as short_name and ivoid:"
@@ -258,7 +258,7 @@
   {
    "cell_type": "code",
    "execution_count": 8,
-   "id": "e1049204",
+   "id": "61d283b6",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -268,7 +268,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ecb02bad",
+   "id": "a6097044",
    "metadata": {},
    "source": [
     "Hint: Next create a UV image for the source"
@@ -277,14 +277,14 @@
   {
    "cell_type": "code",
    "execution_count": 9,
-   "id": "cb664c57",
+   "id": "40925064",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
        "<div><i>Table length=809</i>\n",
-       "<table id=\"table140562958053968\" class=\"table-striped table-bordered table-condensed\">\n",
+       "<table id=\"table140186403159488\" class=\"table-striped table-bordered table-condensed\">\n",
        "<thead><tr><th>productType</th><th>imageFormat</th><th>contentLength</th><th>name</th><th>collection</th><th>insname</th><th>metaRelease</th><th>dataRelease</th><th>trgposRA</th><th>trgPosDec</th><th>s_region</th><th>position_naxes</th><th>position_naxis</th><th>position_scale</th><th>crpix</th><th>crval</th><th>cdmatrix</th><th>coordFrame</th><th>projection</th><th>position_ctype1</th><th>position_ctype2</th><th>position_cunit1</th><th>position_cunit2</th><th>timBoundsSTCS</th><th>time_bounds_cval1</th><th>time_bounds_cval2</th><th>time_bounds_center</th><th>timExposure</th><th>energy_bandpassName</th><th>energy_bounds_cval1</th><th>energy_bounds_cval2</th><th>energy_bounds_center</th><th>energy_units</th><th>publisherDID</th><th>accessURL</th><th>cloud_access</th></tr></thead>\n",
        "<thead><tr><th>object</th><th>object</th><th>int32</th><th>object</th><th>object</th><th>object</th><th>object</th><th>object</th><th>float64</th><th>float64</th><th>object</th><th>int32</th><th>object</th><th>object</th><th>object</th><th>object</th><th>object</th><th>object</th><th>str3</th><th>object</th><th>object</th><th>object</th><th>object</th><th>object</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>object</th><th>float64</th><th>float64</th><th>float64</th><th>object</th><th>object</th><th>object</th><th>object</th></tr></thead>\n",
        "<tr><td>science</td><td>image/fits</td><td>12544983</td><td>FORNAX_MOS06-xd-mcat.fits.gz</td><td>GALEX</td><td>GALEX</td><td>5/11/2010 12:15:31 AM</td><td>5/11/2010 12:15:31 AM</td><td>53.0653359237686</td><td>-36.3609134371405</td><td>CIRCLE ICRS  53.06533592 -36.36091344 0.625</td><td>2</td><td>[3840 3840]</td><td>[-0.00041666667 0.00041666667]</td><td>[1920.5 1920.5]</td><td>[53.0653 -36.3609]</td><td>[-0.000416667 -0.0 -0.0 0.000416667]</td><td>ICRS</td><td>TAN</td><td>RA---TAN</td><td>DEC--TAN</td><td>deg</td><td>deg</td><td>RANGE 54106.382801 54117.283171</td><td>54106.3828009259</td><td>54117.2831712963</td><td>54111.8329861111</td><td>3445.05</td><td>NUV</td><td>1.693e-07</td><td>3.007e-07</td><td>2.35e-07</td><td>meters</td><td>ivo://archive.stsci.edu/GALEX?2555302543848636416</td><td>https://mast.stsci.edu/api/v0.1/Download/file?uri=mast:GALEX/url/data/GR6/pipe/01-vsn/07090-FORNAX_MOS06/d/01-main/0001-img/07-try/FORNAX_MOS06-xd-mcat.fits.gz</td><td>{&quot;aws&quot;: {&quot;bucket_name&quot;:&quot;stpubdata&quot;,&quot;region&quot;:&quot;us-east-1&quot;,&quot;access&quot;:&quot;open&quot;,&quot;key&quot;:&quot;galex/GR6/pipe/01-vsn/07090-FORNAX_MOS06/d/01-main/0001-img/07-try/FORNAX_MOS06-xd-mcat.fits.gz&quot;}}</td></tr>\n",
@@ -297,16 +297,16 @@
        "<tr><td>SCIENCE</td><td>image/fits</td><td>17443052</td><td>FORNAX_MOS06-nd-int.fits.gz</td><td>GALEX</td><td>GALEX</td><td>5/11/2010 12:15:31 AM</td><td>5/11/2010 12:15:31 AM</td><td>53.0653359237686</td><td>-36.3609134371405</td><td>CIRCLE ICRS  53.06533592 -36.36091344 0.625</td><td>2</td><td>[3840 3840]</td><td>[-0.00041666667 0.00041666667]</td><td>[1920.5 1920.5]</td><td>[53.0653 -36.3609]</td><td>[-0.000416667 -0.0 -0.0 0.000416667]</td><td>ICRS</td><td>TAN</td><td>RA---TAN</td><td>DEC--TAN</td><td>deg</td><td>deg</td><td>RANGE 54106.382801 54117.283171</td><td>54106.3828009259</td><td>54117.2831712963</td><td>54111.8329861111</td><td>3445.05</td><td>NUV</td><td>1.693e-07</td><td>3.007e-07</td><td>2.35e-07</td><td>meters</td><td>ivo://archive.stsci.edu/GALEX?2555302543848636416</td><td>https://mast.stsci.edu/api/v0.1/Download/file?uri=mast:GALEX/url/data/GR6/pipe/01-vsn/07090-FORNAX_MOS06/d/01-main/0001-img/07-try/FORNAX_MOS06-nd-int.fits.gz</td><td>{&quot;aws&quot;: {&quot;bucket_name&quot;:&quot;stpubdata&quot;,&quot;region&quot;:&quot;us-east-1&quot;,&quot;access&quot;:&quot;open&quot;,&quot;key&quot;:&quot;galex/GR6/pipe/01-vsn/07090-FORNAX_MOS06/d/01-main/0001-img/07-try/FORNAX_MOS06-nd-int.fits.gz&quot;}}</td></tr>\n",
        "<tr><td>AUXILIARY</td><td>image/fits</td><td>5756688</td><td>FORNAX_MOS06-nd-cnt.fits.gz</td><td>GALEX</td><td>GALEX</td><td>5/11/2010 12:15:31 AM</td><td>5/11/2010 12:15:31 AM</td><td>53.0653359237686</td><td>-36.3609134371405</td><td>CIRCLE ICRS  53.06533592 -36.36091344 0.625</td><td>2</td><td>[3840 3840]</td><td>[-0.00041666667 0.00041666667]</td><td>[1920.5 1920.5]</td><td>[53.0653 -36.3609]</td><td>[-0.000416667 -0.0 -0.0 0.000416667]</td><td>ICRS</td><td>TAN</td><td>RA---TAN</td><td>DEC--TAN</td><td>deg</td><td>deg</td><td>RANGE 54106.382801 54117.283171</td><td>54106.3828009259</td><td>54117.2831712963</td><td>54111.8329861111</td><td>3445.05</td><td>NUV</td><td>1.693e-07</td><td>3.007e-07</td><td>2.35e-07</td><td>meters</td><td>ivo://archive.stsci.edu/GALEX?2555302543848636416</td><td>https://mast.stsci.edu/api/v0.1/Download/file?uri=mast:GALEX/url/data/GR6/pipe/01-vsn/07090-FORNAX_MOS06/d/01-main/0001-img/07-try/FORNAX_MOS06-nd-cnt.fits.gz</td><td>{&quot;aws&quot;: {&quot;bucket_name&quot;:&quot;stpubdata&quot;,&quot;region&quot;:&quot;us-east-1&quot;,&quot;access&quot;:&quot;open&quot;,&quot;key&quot;:&quot;galex/GR6/pipe/01-vsn/07090-FORNAX_MOS06/d/01-main/0001-img/07-try/FORNAX_MOS06-nd-cnt.fits.gz&quot;}}</td></tr>\n",
        "<tr><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td></tr>\n",
-       "<tr><td>AUXILIARY</td><td>image/fits</td><td>3967636</td><td>AIS_423_0002_sg49-fd-intbgsub.fits.gz</td><td>GALEX</td><td>GALEX</td><td>6/16/2010 2:52:42 AM</td><td>6/16/2010 2:52:42 AM</td><td>53.9452301043047</td><td>-36.1117650864775</td><td>CIRCLE ICRS  53.94523010 -36.11176509 0.625</td><td>2</td><td>[3840 3840]</td><td>[-0.00041666667 0.00041666667]</td><td>[1920.5 1920.5]</td><td>[53.9452 -36.1118]</td><td>[-0.000416667 -0.0 -0.0 0.000416667]</td><td>ICRS</td><td>TAN</td><td>RA---TAN</td><td>DEC--TAN</td><td>deg</td><td>deg</td><td>RANGE 54460.401042 54460.402153</td><td>54460.4010416667</td><td>54460.4021527778</td><td>54460.4015972222</td><td>96.0</td><td>FUV</td><td>1.34e-07</td><td>1.806e-07</td><td>1.573e-07</td><td>meters</td><td>ivo://archive.stsci.edu/GALEX?6385798660088659968</td><td>https://mast.stsci.edu/api/v0.1/Download/file?uri=mast:GALEX/url/data/GR6/pipe/02-vsn/50423-AIS_423/d/00-visits/0002-img/07-try/AIS_423_0002_sg49-fd-intbgsub.fits.gz</td><td>{&quot;aws&quot;: {&quot;bucket_name&quot;:&quot;stpubdata&quot;,&quot;region&quot;:&quot;us-east-1&quot;,&quot;access&quot;:&quot;open&quot;,&quot;key&quot;:&quot;galex/GR6/pipe/02-vsn/50423-AIS_423/d/00-visits/0002-img/07-try/AIS_423_0002_sg49-fd-intbgsub.fits.gz&quot;}}</td></tr>\n",
-       "<tr><td>AUXILIARY</td><td>image/fits</td><td>11794</td><td>AIS_423_0002_sg49-fd-flags.fits.gz</td><td>GALEX</td><td>GALEX</td><td>6/16/2010 2:52:42 AM</td><td>6/16/2010 2:52:42 AM</td><td>53.9452301043047</td><td>-36.1117650864775</td><td>CIRCLE ICRS  53.94523010 -36.11176509 0.625</td><td>2</td><td>[3840 3840]</td><td>[-0.00041666667 0.00041666667]</td><td>[1920.5 1920.5]</td><td>[53.9452 -36.1118]</td><td>[-0.000416667 -0.0 -0.0 0.000416667]</td><td>ICRS</td><td>TAN</td><td>RA---TAN</td><td>DEC--TAN</td><td>deg</td><td>deg</td><td>RANGE 54460.401042 54460.402153</td><td>54460.4010416667</td><td>54460.4021527778</td><td>54460.4015972222</td><td>96.0</td><td>FUV</td><td>1.34e-07</td><td>1.806e-07</td><td>1.573e-07</td><td>meters</td><td>ivo://archive.stsci.edu/GALEX?6385798660088659968</td><td>https://mast.stsci.edu/api/v0.1/Download/file?uri=mast:GALEX/url/data/GR6/pipe/02-vsn/50423-AIS_423/d/00-visits/0002-img/07-try/AIS_423_0002_sg49-fd-flags.fits.gz</td><td>{&quot;aws&quot;: {&quot;bucket_name&quot;:&quot;stpubdata&quot;,&quot;region&quot;:&quot;us-east-1&quot;,&quot;access&quot;:&quot;open&quot;,&quot;key&quot;:&quot;galex/GR6/pipe/02-vsn/50423-AIS_423/d/00-visits/0002-img/07-try/AIS_423_0002_sg49-fd-flags.fits.gz&quot;}}</td></tr>\n",
-       "<tr><td>INFO</td><td>image/fits</td><td>13483</td><td>AIS_423_0002_sg49-rtastar.fits.gz</td><td>GALEX</td><td>GALEX</td><td>6/16/2010 2:52:42 AM</td><td>6/16/2010 2:52:42 AM</td><td>53.9452301043047</td><td>-36.1117650864775</td><td>CIRCLE ICRS  53.94523010 -36.11176509 0.625</td><td>2</td><td>[3840 3840]</td><td>[-0.00041666667 0.00041666667]</td><td>[1920.5 1920.5]</td><td>[53.9452 -36.1118]</td><td>[-0.000416667 -0.0 -0.0 0.000416667]</td><td>ICRS</td><td>TAN</td><td>RA---TAN</td><td>DEC--TAN</td><td>deg</td><td>deg</td><td>RANGE 54460.401042 54460.402153</td><td>54460.4010416667</td><td>54460.4021527778</td><td>54460.4015972222</td><td>96.0</td><td>FUV</td><td>1.34e-07</td><td>1.806e-07</td><td>1.573e-07</td><td>meters</td><td>ivo://archive.stsci.edu/GALEX?6385798660088659968</td><td>https://mast.stsci.edu/api/v0.1/Download/file?uri=mast:GALEX/url/data/GR6/pipe/02-vsn/50423-AIS_423/d/00-visits/0002-img/07-try/AIS_423_0002_sg49-rtastar.fits.gz</td><td>{&quot;aws&quot;: {&quot;bucket_name&quot;:&quot;stpubdata&quot;,&quot;region&quot;:&quot;us-east-1&quot;,&quot;access&quot;:&quot;open&quot;,&quot;key&quot;:&quot;galex/GR6/pipe/02-vsn/50423-AIS_423/d/00-visits/0002-img/07-try/AIS_423_0002_sg49-rtastar.fits.gz&quot;}}</td></tr>\n",
-       "<tr><td>INFO</td><td>image/fits</td><td>8757</td><td>AIS_423_0002_sg49-aspraw.fits.gz</td><td>GALEX</td><td>GALEX</td><td>6/16/2010 2:52:42 AM</td><td>6/16/2010 2:52:42 AM</td><td>53.9452301043047</td><td>-36.1117650864775</td><td>CIRCLE ICRS  53.94523010 -36.11176509 0.625</td><td>2</td><td>[3840 3840]</td><td>[-0.00041666667 0.00041666667]</td><td>[1920.5 1920.5]</td><td>[53.9452 -36.1118]</td><td>[-0.000416667 -0.0 -0.0 0.000416667]</td><td>ICRS</td><td>TAN</td><td>RA---TAN</td><td>DEC--TAN</td><td>deg</td><td>deg</td><td>RANGE 54460.401042 54460.402153</td><td>54460.4010416667</td><td>54460.4021527778</td><td>54460.4015972222</td><td>96.0</td><td>FUV</td><td>1.34e-07</td><td>1.806e-07</td><td>1.573e-07</td><td>meters</td><td>ivo://archive.stsci.edu/GALEX?6385798660088659968</td><td>https://mast.stsci.edu/api/v0.1/Download/file?uri=mast:GALEX/url/data/GR6/pipe/02-vsn/50423-AIS_423/d/00-visits/0002-img/07-try/AIS_423_0002_sg49-aspraw.fits.gz</td><td>{&quot;aws&quot;: {&quot;bucket_name&quot;:&quot;stpubdata&quot;,&quot;region&quot;:&quot;us-east-1&quot;,&quot;access&quot;:&quot;open&quot;,&quot;key&quot;:&quot;galex/GR6/pipe/02-vsn/50423-AIS_423/d/00-visits/0002-img/07-try/AIS_423_0002_sg49-aspraw.fits.gz&quot;}}</td></tr>\n",
-       "<tr><td>SCIENCE</td><td>image/fits</td><td>1970004</td><td>AIS_423_sg49-fd-int.fits.gz</td><td>GALEX</td><td>GALEX</td><td>8/18/2010 1:25:11 AM</td><td>8/18/2010 1:25:11 AM</td><td>53.9552232357184</td><td>-36.108680599578</td><td>CIRCLE ICRS  53.95522324 -36.10868060 0.625</td><td>2</td><td>[3840 3840]</td><td>[-0.00041666667 0.00041666667]</td><td>[1920.5 1920.5]</td><td>[53.9552 -36.1087]</td><td>[-0.000416667 -0.0 -0.0 0.000416667]</td><td>ICRS</td><td>TAN</td><td>RA---TAN</td><td>DEC--TAN</td><td>deg</td><td>deg</td><td>RANGE 54385.423877 54460.402153</td><td>54385.4238773148</td><td>54460.4021527778</td><td>54422.9130150463</td><td>200.0</td><td>FUV</td><td>1.34e-07</td><td>1.806e-07</td><td>1.573e-07</td><td>meters</td><td>ivo://archive.stsci.edu/GALEX?6385798797494059008</td><td>https://mast.stsci.edu/api/v0.1/Download/file?uri=mast:GALEX/url/data/GR6/pipe/02-vsn/50423-AIS_423/d/01-main/0001-img/07-try/AIS_423_sg49-fd-int.fits.gz</td><td>{&quot;aws&quot;: {&quot;bucket_name&quot;:&quot;stpubdata&quot;,&quot;region&quot;:&quot;us-east-1&quot;,&quot;access&quot;:&quot;open&quot;,&quot;key&quot;:&quot;galex/GR6/pipe/02-vsn/50423-AIS_423/d/01-main/0001-img/07-try/AIS_423_sg49-fd-int.fits.gz&quot;}}</td></tr>\n",
-       "<tr><td>AUXILIARY</td><td>image/fits</td><td>10548360</td><td>AIS_423_sg49-fd-rrhr.fits.gz</td><td>GALEX</td><td>GALEX</td><td>8/18/2010 1:25:11 AM</td><td>8/18/2010 1:25:11 AM</td><td>53.9552232357184</td><td>-36.108680599578</td><td>CIRCLE ICRS  53.95522324 -36.10868060 0.625</td><td>2</td><td>[3840 3840]</td><td>[-0.00041666667 0.00041666667]</td><td>[1920.5 1920.5]</td><td>[53.9552 -36.1087]</td><td>[-0.000416667 -0.0 -0.0 0.000416667]</td><td>ICRS</td><td>TAN</td><td>RA---TAN</td><td>DEC--TAN</td><td>deg</td><td>deg</td><td>RANGE 54385.423877 54460.402153</td><td>54385.4238773148</td><td>54460.4021527778</td><td>54422.9130150463</td><td>200.0</td><td>FUV</td><td>1.34e-07</td><td>1.806e-07</td><td>1.573e-07</td><td>meters</td><td>ivo://archive.stsci.edu/GALEX?6385798797494059008</td><td>https://mast.stsci.edu/api/v0.1/Download/file?uri=mast:GALEX/url/data/GR6/pipe/02-vsn/50423-AIS_423/d/01-main/0001-img/07-try/AIS_423_sg49-fd-rrhr.fits.gz</td><td>{&quot;aws&quot;: {&quot;bucket_name&quot;:&quot;stpubdata&quot;,&quot;region&quot;:&quot;us-east-1&quot;,&quot;access&quot;:&quot;open&quot;,&quot;key&quot;:&quot;galex/GR6/pipe/02-vsn/50423-AIS_423/d/01-main/0001-img/07-try/AIS_423_sg49-fd-rrhr.fits.gz&quot;}}</td></tr>\n",
-       "<tr><td>AUXILIARY</td><td>image/fits</td><td>2797390</td><td>AIS_423_sg49-fd-skybg.fits.gz</td><td>GALEX</td><td>GALEX</td><td>8/18/2010 1:25:11 AM</td><td>8/18/2010 1:25:11 AM</td><td>53.9552232357184</td><td>-36.108680599578</td><td>CIRCLE ICRS  53.95522324 -36.10868060 0.625</td><td>2</td><td>[3840 3840]</td><td>[-0.00041666667 0.00041666667]</td><td>[1920.5 1920.5]</td><td>[53.9552 -36.1087]</td><td>[-0.000416667 -0.0 -0.0 0.000416667]</td><td>ICRS</td><td>TAN</td><td>RA---TAN</td><td>DEC--TAN</td><td>deg</td><td>deg</td><td>RANGE 54385.423877 54460.402153</td><td>54385.4238773148</td><td>54460.4021527778</td><td>54422.9130150463</td><td>200.0</td><td>FUV</td><td>1.34e-07</td><td>1.806e-07</td><td>1.573e-07</td><td>meters</td><td>ivo://archive.stsci.edu/GALEX?6385798797494059008</td><td>https://mast.stsci.edu/api/v0.1/Download/file?uri=mast:GALEX/url/data/GR6/pipe/02-vsn/50423-AIS_423/d/01-main/0001-img/07-try/AIS_423_sg49-fd-skybg.fits.gz</td><td>{&quot;aws&quot;: {&quot;bucket_name&quot;:&quot;stpubdata&quot;,&quot;region&quot;:&quot;us-east-1&quot;,&quot;access&quot;:&quot;open&quot;,&quot;key&quot;:&quot;galex/GR6/pipe/02-vsn/50423-AIS_423/d/01-main/0001-img/07-try/AIS_423_sg49-fd-skybg.fits.gz&quot;}}</td></tr>\n",
-       "<tr><td>AUXILIARY</td><td>image/fits</td><td>14254446</td><td>AIS_423_sg49-fd-wt.fits.gz</td><td>GALEX</td><td>GALEX</td><td>8/18/2010 1:25:11 AM</td><td>8/18/2010 1:25:11 AM</td><td>53.9552232357184</td><td>-36.108680599578</td><td>CIRCLE ICRS  53.95522324 -36.10868060 0.625</td><td>2</td><td>[3840 3840]</td><td>[-0.00041666667 0.00041666667]</td><td>[1920.5 1920.5]</td><td>[53.9552 -36.1087]</td><td>[-0.000416667 -0.0 -0.0 0.000416667]</td><td>ICRS</td><td>TAN</td><td>RA---TAN</td><td>DEC--TAN</td><td>deg</td><td>deg</td><td>RANGE 54385.423877 54460.402153</td><td>54385.4238773148</td><td>54460.4021527778</td><td>54422.9130150463</td><td>200.0</td><td>FUV</td><td>1.34e-07</td><td>1.806e-07</td><td>1.573e-07</td><td>meters</td><td>ivo://archive.stsci.edu/GALEX?6385798797494059008</td><td>https://mast.stsci.edu/api/v0.1/Download/file?uri=mast:GALEX/url/data/GR6/pipe/02-vsn/50423-AIS_423/d/01-main/0001-img/07-try/AIS_423_sg49-fd-wt.fits.gz</td><td>{&quot;aws&quot;: {&quot;bucket_name&quot;:&quot;stpubdata&quot;,&quot;region&quot;:&quot;us-east-1&quot;,&quot;access&quot;:&quot;open&quot;,&quot;key&quot;:&quot;galex/GR6/pipe/02-vsn/50423-AIS_423/d/01-main/0001-img/07-try/AIS_423_sg49-fd-wt.fits.gz&quot;}}</td></tr>\n",
-       "<tr><td>THUMBNAIL</td><td>image/jpeg</td><td>9914</td><td>AIS_423_sg49-xd-int_2color_thumb.jpg</td><td>GALEX</td><td>GALEX</td><td>8/18/2010 1:25:11 AM</td><td>8/18/2010 1:25:11 AM</td><td>53.9552232357184</td><td>-36.108680599578</td><td>CIRCLE ICRS  53.95522324 -36.10868060 0.625</td><td>2</td><td>[3840 3840]</td><td>[-0.00041666667 0.00041666667]</td><td>[1920.5 1920.5]</td><td>[53.9552 -36.1087]</td><td>[-0.000416667 -0.0 -0.0 0.000416667]</td><td>ICRS</td><td>TAN</td><td>RA---TAN</td><td>DEC--TAN</td><td>deg</td><td>deg</td><td>RANGE 54385.423877 54460.402153</td><td>54385.4238773148</td><td>54460.4021527778</td><td>54422.9130150463</td><td>200.0</td><td>FUV</td><td>1.34e-07</td><td>1.806e-07</td><td>1.573e-07</td><td>meters</td><td>ivo://archive.stsci.edu/GALEX?6385798797494059008</td><td>https://mast.stsci.edu/api/v0.1/Download/file?uri=mast:GALEX/url/data/GR6/pipe/02-vsn/50423-AIS_423/d/01-main/0001-img/07-try/qa/AIS_423_sg49-xd-int_2color_thumb.jpg</td><td>{&quot;aws&quot;: {&quot;bucket_name&quot;:&quot;stpubdata&quot;,&quot;region&quot;:&quot;us-east-1&quot;,&quot;access&quot;:&quot;open&quot;,&quot;key&quot;:&quot;galex/GR6/pipe/02-vsn/50423-AIS_423/d/01-main/0001-img/07-try/qa/AIS_423_sg49-xd-int_2color_thumb.jpg&quot;}}</td></tr>\n",
-       "<tr><td>PREVIEW</td><td>image/jpeg</td><td>576442</td><td>AIS_423_sg49-xd-int_2color_medium_annot.jpg</td><td>GALEX</td><td>GALEX</td><td>8/18/2010 1:25:11 AM</td><td>8/18/2010 1:25:11 AM</td><td>53.9552232357184</td><td>-36.108680599578</td><td>CIRCLE ICRS  53.95522324 -36.10868060 0.625</td><td>2</td><td>[3840 3840]</td><td>[-0.00041666667 0.00041666667]</td><td>[1920.5 1920.5]</td><td>[53.9552 -36.1087]</td><td>[-0.000416667 -0.0 -0.0 0.000416667]</td><td>ICRS</td><td>TAN</td><td>RA---TAN</td><td>DEC--TAN</td><td>deg</td><td>deg</td><td>RANGE 54385.423877 54460.402153</td><td>54385.4238773148</td><td>54460.4021527778</td><td>54422.9130150463</td><td>200.0</td><td>FUV</td><td>1.34e-07</td><td>1.806e-07</td><td>1.573e-07</td><td>meters</td><td>ivo://archive.stsci.edu/GALEX?6385798797494059008</td><td>https://mast.stsci.edu/api/v0.1/Download/file?uri=mast:GALEX/url/data/GR6/pipe/02-vsn/50423-AIS_423/d/01-main/0001-img/07-try/qa/AIS_423_sg49-xd-int_2color_medium_annot.jpg</td><td>{&quot;aws&quot;: {&quot;bucket_name&quot;:&quot;stpubdata&quot;,&quot;region&quot;:&quot;us-east-1&quot;,&quot;access&quot;:&quot;open&quot;,&quot;key&quot;:&quot;galex/GR6/pipe/02-vsn/50423-AIS_423/d/01-main/0001-img/07-try/qa/AIS_423_sg49-xd-int_2color_medium_annot.jpg&quot;}}</td></tr>\n",
+       "<tr><td>science</td><td>image/fits</td><td>269663</td><td>AIS_423_0002_sg49_asprefine-nd-cat.fits.gz</td><td>GALEX</td><td>GALEX</td><td>6/16/2010 2:52:42 AM</td><td>6/16/2010 2:52:42 AM</td><td>53.9452301043047</td><td>-36.1117650864775</td><td>CIRCLE ICRS  53.94523010 -36.11176509 0.625</td><td>2</td><td>[3840 3840]</td><td>[-0.00041666667 0.00041666667]</td><td>[1920.5 1920.5]</td><td>[53.9452 -36.1118]</td><td>[-0.000416667 -0.0 -0.0 0.000416667]</td><td>ICRS</td><td>TAN</td><td>RA---TAN</td><td>DEC--TAN</td><td>deg</td><td>deg</td><td>RANGE 54460.401030 54460.402222</td><td>54460.4010300926</td><td>54460.4022222222</td><td>54460.4016261574</td><td>103.0</td><td>NUV</td><td>1.693e-07</td><td>3.007e-07</td><td>2.35e-07</td><td>meters</td><td>ivo://archive.stsci.edu/GALEX?6385798660088659968</td><td>https://mast.stsci.edu/api/v0.1/Download/file?uri=mast:GALEX/url/data/GR6/pipe/02-vsn/50423-AIS_423/d/00-visits/0002-img/07-try/qa/AIS_423_0002_sg49_asprefine-nd-cat.fits.gz</td><td>{&quot;aws&quot;: {&quot;bucket_name&quot;:&quot;stpubdata&quot;,&quot;region&quot;:&quot;us-east-1&quot;,&quot;access&quot;:&quot;open&quot;,&quot;key&quot;:&quot;galex/GR6/pipe/02-vsn/50423-AIS_423/d/00-visits/0002-img/07-try/qa/AIS_423_0002_sg49_asprefine-nd-cat.fits.gz&quot;}}</td></tr>\n",
+       "<tr><td>AUXILIARY</td><td>image/fits</td><td>339243</td><td>AIS_423_0002_sg49-nd-fcat.fits.gz</td><td>GALEX</td><td>GALEX</td><td>6/16/2010 2:52:42 AM</td><td>6/16/2010 2:52:42 AM</td><td>53.9452301043047</td><td>-36.1117650864775</td><td>CIRCLE ICRS  53.94523010 -36.11176509 0.625</td><td>2</td><td>[3840 3840]</td><td>[-0.00041666667 0.00041666667]</td><td>[1920.5 1920.5]</td><td>[53.9452 -36.1118]</td><td>[-0.000416667 -0.0 -0.0 0.000416667]</td><td>ICRS</td><td>TAN</td><td>RA---TAN</td><td>DEC--TAN</td><td>deg</td><td>deg</td><td>RANGE 54460.401030 54460.402222</td><td>54460.4010300926</td><td>54460.4022222222</td><td>54460.4016261574</td><td>103.0</td><td>NUV</td><td>1.693e-07</td><td>3.007e-07</td><td>2.35e-07</td><td>meters</td><td>ivo://archive.stsci.edu/GALEX?6385798660088659968</td><td>https://mast.stsci.edu/api/v0.1/Download/file?uri=mast:GALEX/url/data/GR6/pipe/02-vsn/50423-AIS_423/d/00-visits/0002-img/07-try/AIS_423_0002_sg49-nd-fcat.fits.gz</td><td>{&quot;aws&quot;: {&quot;bucket_name&quot;:&quot;stpubdata&quot;,&quot;region&quot;:&quot;us-east-1&quot;,&quot;access&quot;:&quot;open&quot;,&quot;key&quot;:&quot;galex/GR6/pipe/02-vsn/50423-AIS_423/d/00-visits/0002-img/07-try/AIS_423_0002_sg49-nd-fcat.fits.gz&quot;}}</td></tr>\n",
+       "<tr><td>PREVIEW</td><td>image/jpeg</td><td>3487526</td><td>AIS_423_0002_sg49-xd-int_2color.jpg</td><td>GALEX</td><td>GALEX</td><td>6/16/2010 2:52:42 AM</td><td>6/16/2010 2:52:42 AM</td><td>53.9452301043047</td><td>-36.1117650864775</td><td>CIRCLE ICRS  53.94523010 -36.11176509 0.625</td><td>2</td><td>[3840 3840]</td><td>[-0.00041666667 0.00041666667]</td><td>[1920.5 1920.5]</td><td>[53.9452 -36.1118]</td><td>[-0.000416667 -0.0 -0.0 0.000416667]</td><td>ICRS</td><td>TAN</td><td>RA---TAN</td><td>DEC--TAN</td><td>deg</td><td>deg</td><td>RANGE 54460.401030 54460.402222</td><td>54460.4010300926</td><td>54460.4022222222</td><td>54460.4016261574</td><td>103.0</td><td>NUV</td><td>1.693e-07</td><td>3.007e-07</td><td>2.35e-07</td><td>meters</td><td>ivo://archive.stsci.edu/GALEX?6385798660088659968</td><td>https://mast.stsci.edu/api/v0.1/Download/file?uri=mast:GALEX/url/data/GR6/pipe/02-vsn/50423-AIS_423/d/00-visits/0002-img/07-try/qa/AIS_423_0002_sg49-xd-int_2color.jpg</td><td>{&quot;aws&quot;: {&quot;bucket_name&quot;:&quot;stpubdata&quot;,&quot;region&quot;:&quot;us-east-1&quot;,&quot;access&quot;:&quot;open&quot;,&quot;key&quot;:&quot;galex/GR6/pipe/02-vsn/50423-AIS_423/d/00-visits/0002-img/07-try/qa/AIS_423_0002_sg49-xd-int_2color.jpg&quot;}}</td></tr>\n",
+       "<tr><td>PREVIEW</td><td>image/jpeg</td><td>663752</td><td>AIS_423_0002_sg49-xd-int_2color_large.jpg</td><td>GALEX</td><td>GALEX</td><td>6/16/2010 2:52:42 AM</td><td>6/16/2010 2:52:42 AM</td><td>53.9452301043047</td><td>-36.1117650864775</td><td>CIRCLE ICRS  53.94523010 -36.11176509 0.625</td><td>2</td><td>[3840 3840]</td><td>[-0.00041666667 0.00041666667]</td><td>[1920.5 1920.5]</td><td>[53.9452 -36.1118]</td><td>[-0.000416667 -0.0 -0.0 0.000416667]</td><td>ICRS</td><td>TAN</td><td>RA---TAN</td><td>DEC--TAN</td><td>deg</td><td>deg</td><td>RANGE 54460.401030 54460.402222</td><td>54460.4010300926</td><td>54460.4022222222</td><td>54460.4016261574</td><td>103.0</td><td>NUV</td><td>1.693e-07</td><td>3.007e-07</td><td>2.35e-07</td><td>meters</td><td>ivo://archive.stsci.edu/GALEX?6385798660088659968</td><td>https://mast.stsci.edu/api/v0.1/Download/file?uri=mast:GALEX/url/data/GR6/pipe/02-vsn/50423-AIS_423/d/00-visits/0002-img/07-try/qa/AIS_423_0002_sg49-xd-int_2color_large.jpg</td><td>{&quot;aws&quot;: {&quot;bucket_name&quot;:&quot;stpubdata&quot;,&quot;region&quot;:&quot;us-east-1&quot;,&quot;access&quot;:&quot;open&quot;,&quot;key&quot;:&quot;galex/GR6/pipe/02-vsn/50423-AIS_423/d/00-visits/0002-img/07-try/qa/AIS_423_0002_sg49-xd-int_2color_large.jpg&quot;}}</td></tr>\n",
+       "<tr><td>PREVIEW</td><td>image/jpeg</td><td>575892</td><td>AIS_423_0002_sg49-xd-int_2color_medium.jpg</td><td>GALEX</td><td>GALEX</td><td>6/16/2010 2:52:42 AM</td><td>6/16/2010 2:52:42 AM</td><td>53.9452301043047</td><td>-36.1117650864775</td><td>CIRCLE ICRS  53.94523010 -36.11176509 0.625</td><td>2</td><td>[3840 3840]</td><td>[-0.00041666667 0.00041666667]</td><td>[1920.5 1920.5]</td><td>[53.9452 -36.1118]</td><td>[-0.000416667 -0.0 -0.0 0.000416667]</td><td>ICRS</td><td>TAN</td><td>RA---TAN</td><td>DEC--TAN</td><td>deg</td><td>deg</td><td>RANGE 54460.401030 54460.402222</td><td>54460.4010300926</td><td>54460.4022222222</td><td>54460.4016261574</td><td>103.0</td><td>NUV</td><td>1.693e-07</td><td>3.007e-07</td><td>2.35e-07</td><td>meters</td><td>ivo://archive.stsci.edu/GALEX?6385798660088659968</td><td>https://mast.stsci.edu/api/v0.1/Download/file?uri=mast:GALEX/url/data/GR6/pipe/02-vsn/50423-AIS_423/d/00-visits/0002-img/07-try/qa/AIS_423_0002_sg49-xd-int_2color_medium.jpg</td><td>{&quot;aws&quot;: {&quot;bucket_name&quot;:&quot;stpubdata&quot;,&quot;region&quot;:&quot;us-east-1&quot;,&quot;access&quot;:&quot;open&quot;,&quot;key&quot;:&quot;galex/GR6/pipe/02-vsn/50423-AIS_423/d/00-visits/0002-img/07-try/qa/AIS_423_0002_sg49-xd-int_2color_medium.jpg&quot;}}</td></tr>\n",
+       "<tr><td>PREVIEW</td><td>image/jpeg</td><td>134331</td><td>AIS_423_0002_sg49-xd-int_2color_small.jpg</td><td>GALEX</td><td>GALEX</td><td>6/16/2010 2:52:42 AM</td><td>6/16/2010 2:52:42 AM</td><td>53.9452301043047</td><td>-36.1117650864775</td><td>CIRCLE ICRS  53.94523010 -36.11176509 0.625</td><td>2</td><td>[3840 3840]</td><td>[-0.00041666667 0.00041666667]</td><td>[1920.5 1920.5]</td><td>[53.9452 -36.1118]</td><td>[-0.000416667 -0.0 -0.0 0.000416667]</td><td>ICRS</td><td>TAN</td><td>RA---TAN</td><td>DEC--TAN</td><td>deg</td><td>deg</td><td>RANGE 54460.401030 54460.402222</td><td>54460.4010300926</td><td>54460.4022222222</td><td>54460.4016261574</td><td>103.0</td><td>NUV</td><td>1.693e-07</td><td>3.007e-07</td><td>2.35e-07</td><td>meters</td><td>ivo://archive.stsci.edu/GALEX?6385798660088659968</td><td>https://mast.stsci.edu/api/v0.1/Download/file?uri=mast:GALEX/url/data/GR6/pipe/02-vsn/50423-AIS_423/d/00-visits/0002-img/07-try/qa/AIS_423_0002_sg49-xd-int_2color_small.jpg</td><td>{&quot;aws&quot;: {&quot;bucket_name&quot;:&quot;stpubdata&quot;,&quot;region&quot;:&quot;us-east-1&quot;,&quot;access&quot;:&quot;open&quot;,&quot;key&quot;:&quot;galex/GR6/pipe/02-vsn/50423-AIS_423/d/00-visits/0002-img/07-try/qa/AIS_423_0002_sg49-xd-int_2color_small.jpg&quot;}}</td></tr>\n",
+       "<tr><td>INFO</td><td>image/fits</td><td>8737</td><td>AIS_423_0002_sg49-asp.fits.gz</td><td>GALEX</td><td>GALEX</td><td>6/16/2010 2:52:42 AM</td><td>6/16/2010 2:52:42 AM</td><td>53.9452301043047</td><td>-36.1117650864775</td><td>CIRCLE ICRS  53.94523010 -36.11176509 0.625</td><td>2</td><td>[3840 3840]</td><td>[-0.00041666667 0.00041666667]</td><td>[1920.5 1920.5]</td><td>[53.9452 -36.1118]</td><td>[-0.000416667 -0.0 -0.0 0.000416667]</td><td>ICRS</td><td>TAN</td><td>RA---TAN</td><td>DEC--TAN</td><td>deg</td><td>deg</td><td>RANGE 54460.401030 54460.402222</td><td>54460.4010300926</td><td>54460.4022222222</td><td>54460.4016261574</td><td>103.0</td><td>NUV</td><td>1.693e-07</td><td>3.007e-07</td><td>2.35e-07</td><td>meters</td><td>ivo://archive.stsci.edu/GALEX?6385798660088659968</td><td>https://mast.stsci.edu/api/v0.1/Download/file?uri=mast:GALEX/url/data/GR6/pipe/02-vsn/50423-AIS_423/d/00-visits/0002-img/07-try/AIS_423_0002_sg49-asp.fits.gz</td><td>{&quot;aws&quot;: {&quot;bucket_name&quot;:&quot;stpubdata&quot;,&quot;region&quot;:&quot;us-east-1&quot;,&quot;access&quot;:&quot;open&quot;,&quot;key&quot;:&quot;galex/GR6/pipe/02-vsn/50423-AIS_423/d/00-visits/0002-img/07-try/AIS_423_0002_sg49-asp.fits.gz&quot;}}</td></tr>\n",
+       "<tr><td>AUXILIARY</td><td>image/fits</td><td>64456</td><td>AIS_423_0002_sg49-nd-cat_mch_flagstar.fits.gz</td><td>GALEX</td><td>GALEX</td><td>6/16/2010 2:52:42 AM</td><td>6/16/2010 2:52:42 AM</td><td>53.9452301043047</td><td>-36.1117650864775</td><td>CIRCLE ICRS  53.94523010 -36.11176509 0.625</td><td>2</td><td>[3840 3840]</td><td>[-0.00041666667 0.00041666667]</td><td>[1920.5 1920.5]</td><td>[53.9452 -36.1118]</td><td>[-0.000416667 -0.0 -0.0 0.000416667]</td><td>ICRS</td><td>TAN</td><td>RA---TAN</td><td>DEC--TAN</td><td>deg</td><td>deg</td><td>RANGE 54460.401030 54460.402222</td><td>54460.4010300926</td><td>54460.4022222222</td><td>54460.4016261574</td><td>103.0</td><td>NUV</td><td>1.693e-07</td><td>3.007e-07</td><td>2.35e-07</td><td>meters</td><td>ivo://archive.stsci.edu/GALEX?6385798660088659968</td><td>https://mast.stsci.edu/api/v0.1/Download/file?uri=mast:GALEX/url/data/GR6/pipe/02-vsn/50423-AIS_423/d/00-visits/0002-img/07-try/AIS_423_0002_sg49-nd-cat_mch_flagstar.fits.gz</td><td>{&quot;aws&quot;: {&quot;bucket_name&quot;:&quot;stpubdata&quot;,&quot;region&quot;:&quot;us-east-1&quot;,&quot;access&quot;:&quot;open&quot;,&quot;key&quot;:&quot;galex/GR6/pipe/02-vsn/50423-AIS_423/d/00-visits/0002-img/07-try/AIS_423_0002_sg49-nd-cat_mch_flagstar.fits.gz&quot;}}</td></tr>\n",
+       "<tr><td>AUXILIARY</td><td>image/fits</td><td>25691</td><td>AIS_423_0002_sg49-nd-flag_tbl.fits.gz</td><td>GALEX</td><td>GALEX</td><td>6/16/2010 2:52:42 AM</td><td>6/16/2010 2:52:42 AM</td><td>53.9452301043047</td><td>-36.1117650864775</td><td>CIRCLE ICRS  53.94523010 -36.11176509 0.625</td><td>2</td><td>[3840 3840]</td><td>[-0.00041666667 0.00041666667]</td><td>[1920.5 1920.5]</td><td>[53.9452 -36.1118]</td><td>[-0.000416667 -0.0 -0.0 0.000416667]</td><td>ICRS</td><td>TAN</td><td>RA---TAN</td><td>DEC--TAN</td><td>deg</td><td>deg</td><td>RANGE 54460.401030 54460.402222</td><td>54460.4010300926</td><td>54460.4022222222</td><td>54460.4016261574</td><td>103.0</td><td>NUV</td><td>1.693e-07</td><td>3.007e-07</td><td>2.35e-07</td><td>meters</td><td>ivo://archive.stsci.edu/GALEX?6385798660088659968</td><td>https://mast.stsci.edu/api/v0.1/Download/file?uri=mast:GALEX/url/data/GR6/pipe/02-vsn/50423-AIS_423/d/00-visits/0002-img/07-try/AIS_423_0002_sg49-nd-flag_tbl.fits.gz</td><td>{&quot;aws&quot;: {&quot;bucket_name&quot;:&quot;stpubdata&quot;,&quot;region&quot;:&quot;us-east-1&quot;,&quot;access&quot;:&quot;open&quot;,&quot;key&quot;:&quot;galex/GR6/pipe/02-vsn/50423-AIS_423/d/00-visits/0002-img/07-try/AIS_423_0002_sg49-nd-flag_tbl.fits.gz&quot;}}</td></tr>\n",
+       "<tr><td>AUXILIARY</td><td>image/fits</td><td>9113</td><td>FORNAX_MOS07_0002-fd-cat_mch_flagstar.fits.gz</td><td>GALEX</td><td>GALEX</td><td>4/28/2010 3:21:44 PM</td><td>4/28/2010 3:21:44 PM</td><td>54.0359149055626</td><td>-36.3362710522186</td><td>CIRCLE ICRS  54.03591491 -36.33627105 0.625</td><td>2</td><td>[3840 3840]</td><td>[-0.00041666667 0.00041666667]</td><td>[1920.5 1920.5]</td><td>[54.0359 -36.3363]</td><td>[-0.000416667 -0.0 -0.0 0.000416667]</td><td>ICRS</td><td>TAN</td><td>RA---TAN</td><td>DEC--TAN</td><td>deg</td><td>deg</td><td>RANGE 54110.286030 54110.296377</td><td>54110.2860300926</td><td>54110.2963773148</td><td>54110.2912037037</td><td>894.45</td><td>FUV</td><td>1.34e-07</td><td>1.806e-07</td><td>1.573e-07</td><td>meters</td><td>ivo://archive.stsci.edu/GALEX?2555337590815326208</td><td>https://mast.stsci.edu/api/v0.1/Download/file?uri=mast:GALEX/url/data/GR6/pipe/01-vsn/07091-FORNAX_MOS07/d/00-visits/0002-img/07-try/FORNAX_MOS07_0002-fd-cat_mch_flagstar.fits.gz</td><td>{&quot;aws&quot;: {&quot;bucket_name&quot;:&quot;stpubdata&quot;,&quot;region&quot;:&quot;us-east-1&quot;,&quot;access&quot;:&quot;open&quot;,&quot;key&quot;:&quot;galex/GR6/pipe/01-vsn/07091-FORNAX_MOS07/d/00-visits/0002-img/07-try/FORNAX_MOS07_0002-fd-cat_mch_flagstar.fits.gz&quot;}}</td></tr>\n",
        "</table></div>"
       ],
       "text/plain": [
@@ -324,16 +324,16 @@
        "    SCIENCE ...\n",
        "  AUXILIARY ...\n",
        "        ... ...\n",
+       "    science ...\n",
        "  AUXILIARY ...\n",
-       "  AUXILIARY ...\n",
-       "       INFO ...\n",
+       "    PREVIEW ...\n",
+       "    PREVIEW ...\n",
+       "    PREVIEW ...\n",
+       "    PREVIEW ...\n",
        "       INFO ...\n",
-       "    SCIENCE ...\n",
        "  AUXILIARY ...\n",
        "  AUXILIARY ...\n",
-       "  AUXILIARY ...\n",
-       "  THUMBNAIL ...\n",
-       "    PREVIEW ..."
+       "  AUXILIARY ..."
       ]
      },
      "execution_count": 9,
@@ -350,27 +350,27 @@
   {
    "cell_type": "code",
    "execution_count": 10,
-   "id": "aecba920",
+   "id": "30c288db",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
        "<div><i>Table length=2</i>\n",
-       "<table id=\"table140562901717232\" class=\"table-striped table-bordered table-condensed\">\n",
+       "<table id=\"table140186403329392\" class=\"table-striped table-bordered table-condensed\">\n",
        "<thead><tr><th>Survey</th><th>Ra</th><th>Dec</th><th>Dim</th><th>Size</th><th>Scale</th><th>Format</th><th>PixFlags</th><th>URL</th><th>LogicalName</th></tr></thead>\n",
        "<thead><tr><th>object</th><th>float64</th><th>float64</th><th>int32</th><th>object</th><th>object</th><th>object</th><th>object</th><th>object</th><th>object</th></tr></thead>\n",
-       "<tr><td>galexnear</td><td>53.4019083</td><td>-36.1406583</td><td>2</td><td>[300 300]</td><td>[-0.0003333333333333334 0.0003333333333333334]</td><td>image/fits</td><td>F</td><td>https://skyview.gsfc.nasa.gov/cgi-bin/images?position=53.4019083%2C-36.1406583&amp;survey=galexnear&amp;pixels=300%2C300&amp;sampler=LI&amp;size=0.10000000000000002%2C0.10000000000000002&amp;projection=Tan&amp;coordinates=J2000.0&amp;requestID=skv1734385870169&amp;return=FITS</td><td>1</td></tr>\n",
-       "<tr><td>galexfar</td><td>53.4019083</td><td>-36.1406583</td><td>2</td><td>[300 300]</td><td>[-0.0003333333333333334 0.0003333333333333334]</td><td>image/fits</td><td>F</td><td>https://skyview.gsfc.nasa.gov/cgi-bin/images?position=53.4019083%2C-36.1406583&amp;survey=galexfar&amp;pixels=300%2C300&amp;sampler=LI&amp;size=0.10000000000000002%2C0.10000000000000002&amp;projection=Tan&amp;coordinates=J2000.0&amp;requestID=skv1734385870381&amp;return=FITS</td><td>2</td></tr>\n",
+       "<tr><td>galexnear</td><td>53.40190833</td><td>-36.14065833</td><td>2</td><td>[300 300]</td><td>[-0.0003333333333333334 0.0003333333333333334]</td><td>image/fits</td><td>F</td><td>https://skyview.gsfc.nasa.gov/cgi-bin/images?position=53.40190833%2C-36.14065833&amp;survey=galexnear&amp;pixels=300%2C300&amp;sampler=LI&amp;size=0.10000000000000002%2C0.10000000000000002&amp;projection=Tan&amp;coordinates=J2000.0&amp;requestID=skv1734402283226&amp;return=FITS</td><td>1</td></tr>\n",
+       "<tr><td>galexfar</td><td>53.40190833</td><td>-36.14065833</td><td>2</td><td>[300 300]</td><td>[-0.0003333333333333334 0.0003333333333333334]</td><td>image/fits</td><td>F</td><td>https://skyview.gsfc.nasa.gov/cgi-bin/images?position=53.40190833%2C-36.14065833&amp;survey=galexfar&amp;pixels=300%2C300&amp;sampler=LI&amp;size=0.10000000000000002%2C0.10000000000000002&amp;projection=Tan&amp;coordinates=J2000.0&amp;requestID=skv1734402283432&amp;return=FITS</td><td>2</td></tr>\n",
        "</table></div>"
       ],
       "text/plain": [
        "<Table length=2>\n",
-       "  Survey      Ra     ... LogicalName\n",
-       "  object   float64   ...    object  \n",
-       "--------- ---------- ... -----------\n",
-       "galexnear 53.4019083 ...           1\n",
-       " galexfar 53.4019083 ...           2"
+       "  Survey       Ra     ... LogicalName\n",
+       "  object    float64   ...    object  \n",
+       "--------- ----------- ... -----------\n",
+       "galexnear 53.40190833 ...           1\n",
+       " galexfar 53.40190833 ...           2"
       ]
      },
      "execution_count": 10,
@@ -388,7 +388,7 @@
   {
    "cell_type": "code",
    "execution_count": 11,
-   "id": "7b096580",
+   "id": "f894f218",
    "metadata": {},
    "outputs": [
     {
@@ -413,13 +413,13 @@
   {
    "cell_type": "code",
    "execution_count": 12,
-   "id": "0ad80bb2",
+   "id": "8d113738",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<matplotlib.image.AxesImage at 0x7fd759670340>"
+       "<matplotlib.image.AxesImage at 0x7f7fb027fc40>"
       ]
      },
      "execution_count": 12,
@@ -428,7 +428,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 480x480 with 1 Axes>"
       ]
@@ -446,7 +446,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "103429a0",
+   "id": "e282bbf9",
    "metadata": {},
    "source": [
     "Hint: Repeat steps for X-ray image. (Note: Ideally, we would find an image in the Chandra 'cxc' catalog)"
@@ -455,7 +455,7 @@
   {
    "cell_type": "code",
    "execution_count": 13,
-   "id": "7f459d96",
+   "id": "3e1ff6c2",
    "metadata": {},
    "outputs": [
     {
@@ -482,7 +482,7 @@
   {
    "cell_type": "code",
    "execution_count": 14,
-   "id": "1b19d4c4",
+   "id": "528384f0",
    "metadata": {},
    "outputs": [
     {
@@ -504,7 +504,7 @@
   {
    "cell_type": "code",
    "execution_count": 15,
-   "id": "c369fc49",
+   "id": "81590d58",
    "metadata": {},
    "outputs": [
     {
@@ -543,7 +543,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "3cf03871",
+   "id": "910cdd11",
    "metadata": {},
    "source": [
     "## Step 3: Make a spectrum\n",
@@ -556,14 +556,14 @@
   {
    "cell_type": "code",
    "execution_count": 16,
-   "id": "bc4a130f",
+   "id": "0d9132be",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
        "<div><i>Table length=7</i>\n",
-       "<table id=\"table140562767840544\" class=\"table-striped table-bordered table-condensed\">\n",
+       "<table id=\"table140186336908224\" class=\"table-striped table-bordered table-condensed\">\n",
        "<thead><tr><th>short_name</th><th>ivoid</th><th>waveband</th></tr></thead>\n",
        "<thead><tr><th>object</th><th>object</th><th>object</th></tr></thead>\n",
        "<tr><td>Chandra</td><td>ivo://nasa.heasarc/chanmaster</td><td>x-ray</td></tr>\n",
@@ -602,7 +602,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f1e92177",
+   "id": "1d3f29d8",
    "metadata": {},
    "source": [
     "Hint 2: Take a look at what data exist for our candidate, NGC 1365."
@@ -611,14 +611,14 @@
   {
    "cell_type": "code",
    "execution_count": 17,
-   "id": "c830bd52",
+   "id": "fd7890b0",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
        "<div><i>Table length=15</i>\n",
-       "<table id=\"table140562889916128\" class=\"table-striped table-bordered table-condensed\">\n",
+       "<table id=\"table140186391394816\" class=\"table-striped table-bordered table-condensed\">\n",
        "<thead><tr><th>obsid</th><th>status</th><th>name</th><th>ra</th><th>dec</th><th>time</th><th>detector</th><th>grating</th><th>exposure</th><th>type</th><th>pi</th><th>public_date</th><th>datalink</th><th>SSA_start_time</th><th>SSA_tmid</th><th>SSA_stop_time</th><th>SSA_duration</th><th>SSA_coord_obs</th><th>SSA_ra</th><th>SSA_dec</th><th>SSA_fov</th><th>SSA_title</th><th>SSA_reference</th><th>SSA_datalength</th><th>SSA_datamodel</th><th>SSA_instrument</th><th>SSA_publisher</th><th>SSA_format</th><th>SSA_wavelength_min</th><th>SSA_wavelength_max</th><th>SSA_bandwidth</th><th>SSA_bandpass</th><th>cloud_access</th></tr></thead>\n",
        "<thead><tr><th></th><th></th><th></th><th>deg</th><th>deg</th><th>d</th><th></th><th></th><th>s</th><th></th><th></th><th>d</th><th></th><th>d</th><th>d</th><th>d</th><th>s</th><th>deg</th><th>deg</th><th>deg</th><th>deg</th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th>m</th><th>m</th><th>m</th><th>m</th><th></th></tr></thead>\n",
        "<thead><tr><th>object</th><th>object</th><th>object</th><th>float64</th><th>float64</th><th>float64</th><th>object</th><th>object</th><th>float64</th><th>object</th><th>object</th><th>int32</th><th>object</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>object</th><th>object</th><th>object</th><th>object</th><th>object</th><th>object</th><th>object</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>object</th></tr></thead>\n",
@@ -674,7 +674,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a0c6ca20",
+   "id": "92d376d1",
    "metadata": {},
    "source": [
     "Hint 3: Download the data to make a spectrum. Note: you might end here and use Xspec to plot and model the spectrum. Or ... you can also try to take a quick look at the spectrum."
@@ -683,7 +683,7 @@
   {
    "cell_type": "code",
    "execution_count": 18,
-   "id": "cb22807a",
+   "id": "4413515f",
    "metadata": {},
    "outputs": [
     {
@@ -723,7 +723,7 @@
   {
    "cell_type": "code",
    "execution_count": 19,
-   "id": "ebb39060",
+   "id": "03daa095",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -740,7 +740,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "c57049e9",
+   "id": "9b3bb211",
    "metadata": {},
    "source": [
     "Extension: Making a \"quick look\" spectrum. For our purposes, the 1st order of the HEG grating data would be sufficient."
@@ -749,7 +749,7 @@
   {
    "cell_type": "code",
    "execution_count": 20,
-   "id": "e2529192",
+   "id": "c9830f2e",
    "metadata": {},
    "outputs": [
     {
@@ -780,7 +780,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "554e1565",
+   "id": "cf8235d9",
    "metadata": {},
    "source": [
     "This can then be analyzed in your favorite spectral analysis tool, e.g., [pyXspec](https://heasarc.gsfc.nasa.gov/xanadu/xspec/python/html/index.html).  (For the winter 2018 AAS workshop, we demonstrated this in a [notebook](https://github.com/NASA-NAVO/aas_workshop_2018/blob/master/heasarc/heasarc_Spectral_Access.md) that you can consult for how to use pyXspec, but the pyXspec documentation will have more information.)"
@@ -788,7 +788,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "0a5dcd59",
+   "id": "e6a622b6",
    "metadata": {},
    "source": [
     "Congratulations! You have completed this notebook exercise."
diff --git a/content/reference_notebooks/basic_reference.html b/content/reference_notebooks/basic_reference.html
index 85322d3..6c00ce6 100644
--- a/content/reference_notebooks/basic_reference.html
+++ b/content/reference_notebooks/basic_reference.html
@@ -693,7 +693,7 @@ <h5>Using astropy<a class="headerlink" href="#using-astropy" title="Link to this
 </pre></div>
 </div>
 <div class="output text_html"><div><i>Table length=3</i>
-<table id="table140712745793664" class="table-striped table-bordered table-condensed">
+<table id="table140077415297232" class="table-striped table-bordered table-condensed">
 <thead><tr><th>short_name</th><th>res_title</th><th>res_description</th></tr></thead>
 <thead><tr><th>object</th><th>object</th><th>object</th></tr></thead>
 <tr><td>MAST CS</td><td>MAST ConeSearch</td><td>All MAST catalog holdings are available via a ConeSearch endpoint. \nThis service provides access to all, with an optional non-standard parameter for an individual catalog to query. \nThe available missions are listed at http://archive.stsci.edu/vo/mast_services.html, \nand include Hubble (HST) data, Kepler, K2, IUE, HUT, EUVE, FUSE, UIT, WUPPE, BEFS, TUES, IMAPS, High Level Science Products (HLSP), Copernicus, HPOL, VLA First, XMM-OM, and SWIFT.</td></tr>
@@ -721,29 +721,29 @@ <h3>2.2 Cone search<a class="headerlink" href="#cone-search" title="Link to this
 </div>
 <div class="cell_output docutils container">
 <div class="output text_html"><div><i>Table length=316</i>
-<table id="table140713667413568" class="table-striped table-bordered table-condensed">
+<table id="table140077415295216" class="table-striped table-bordered table-condensed">
 <thead><tr><th>ObjID</th><th>Zone</th><th>SeqNo</th><th>RA</th><th>DEC</th><th>pmRA</th><th>pmDEC</th><th>e_pmRA</th><th>e_pmDEC</th><th>e_RA</th><th>e_DEC</th><th>Epoch</th><th>B1Mag</th><th>R1s_g</th><th>B2Mag</th><th>B2s_g</th><th>R2Mag</th><th>R2s_g</th><th>NMag</th><th>mag</th><th>B1s_g</th><th>R1Mag</th><th>distance</th></tr></thead>
 <thead><tr><th></th><th></th><th></th><th>deg</th><th>deg</th><th>mas / yr</th><th>mas / yr</th><th>mas / yr</th><th>mas / yr</th><th>arcsec</th><th>arcsec</th><th>yr</th><th>mag</th><th></th><th>mag</th><th></th><th>mag</th><th></th><th>mag</th><th>mag</th><th></th><th>mag</th><th>arcsec</th></tr></thead>
 <thead><tr><th>int64</th><th>int32</th><th>int32</th><th>float64</th><th>float64</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>int32</th><th>float32</th><th>int32</th><th>float32</th><th>int32</th><th>float32</th><th>float32</th><th>int32</th><th>float32</th><th>float32</th></tr></thead>
-<tr><td>5888400445251</td><td>1371</td><td>282435</td><td>202.472919444444</td><td>47.1954444444444</td><td>2.081668e-13</td><td>2.081668e-13</td><td>0.0</td><td>0.0</td><td>999.0</td><td>999.0</td><td>1981.8</td><td>-999999500.0</td><td>1</td><td>9.4</td><td>9</td><td>-999999500.0</td><td>0</td><td>7.86</td><td>-999999500.0</td><td>0</td><td>8.98</td><td>0.13680981</td></tr>
-<tr><td>5892695420475</td><td>1372</td><td>290363</td><td>202.494625</td><td>47.2065472222222</td><td>2.081668e-13</td><td>2.081668e-13</td><td>0.0</td><td>0.0</td><td>332.0</td><td>999.0</td><td>1956.2</td><td>20.13</td><td>3</td><td>-999999500.0</td><td>0</td><td>-999999500.0</td><td>0</td><td>-999999500.0</td><td>-999999500.0</td><td>4</td><td>15.79</td><td>1.225397</td></tr>
-<tr><td>5892695420458</td><td>1372</td><td>290346</td><td>202.436875</td><td>47.2094416666667</td><td>2.081668e-13</td><td>2.081668e-13</td><td>0.0</td><td>0.0</td><td>999.0</td><td>359.0</td><td>1976.2</td><td>-999999500.0</td><td>1</td><td>-999999500.0</td><td>0</td><td>-999999500.0</td><td>0</td><td>10.89</td><td>-999999500.0</td><td>0</td><td>13.27</td><td>1.5814886</td></tr>
-<tr><td>5892695420468</td><td>1372</td><td>290356</td><td>202.469830555556</td><td>47.2232805555556</td><td>2.081668e-13</td><td>2.081668e-13</td><td>0.0</td><td>0.0</td><td>560.0</td><td>934.0</td><td>1976.2</td><td>-999999500.0</td><td>3</td><td>-999999500.0</td><td>0</td><td>-999999500.0</td><td>0</td><td>18.4</td><td>-999999500.0</td><td>0</td><td>17.78</td><td>1.6813676</td></tr>
-<tr><td>5888400445256</td><td>1371</td><td>282440</td><td>202.480638888889</td><td>47.1682194444444</td><td>-20.0</td><td>-6.0</td><td>5.0</td><td>5.0</td><td>205.0</td><td>201.0</td><td>1969.5</td><td>12.79</td><td>8</td><td>-999999500.0</td><td>0</td><td>-999999500.0</td><td>0</td><td>14.87</td><td>-999999500.0</td><td>1</td><td>15.4</td><td>1.6839039</td></tr>
-<tr><td>5892695420469</td><td>1372</td><td>290357</td><td>202.4706</td><td>47.2235555555556</td><td>2.081668e-13</td><td>2.081668e-13</td><td>0.0</td><td>0.0</td><td>709.0</td><td>130.0</td><td>1956.2</td><td>15.89</td><td>3</td><td>-999999500.0</td><td>0</td><td>-999999500.0</td><td>0</td><td>-999999500.0</td><td>-999999500.0</td><td>1</td><td>17.68</td><td>1.6983492</td></tr>
-<tr><td>5892695420470</td><td>1372</td><td>290358</td><td>202.474338888889</td><td>47.2264416666667</td><td>2.081668e-13</td><td>2.081668e-13</td><td>0.0</td><td>0.0</td><td>200.0</td><td>490.0</td><td>1956.2</td><td>13.49</td><td>4</td><td>-999999500.0</td><td>0</td><td>-999999500.0</td><td>0</td><td>-999999500.0</td><td>-999999500.0</td><td>1</td><td>18.74</td><td>1.8810501</td></tr>
-<tr><td>5888400445204</td><td>1371</td><td>282388</td><td>202.423558333333</td><td>47.1977666666667</td><td>2.081668e-13</td><td>2.081668e-13</td><td>0.0</td><td>0.0</td><td>466.0</td><td>480.0</td><td>1969.5</td><td>15.66</td><td>8</td><td>-999999500.0</td><td>0</td><td>-999999500.0</td><td>0</td><td>14.97</td><td>-999999500.0</td><td>1</td><td>15.22</td><td>1.8820878</td></tr>
-<tr><td>5888400445231</td><td>1371</td><td>282415</td><td>202.459627777778</td><td>47.1625777777778</td><td>2.081668e-13</td><td>2.081668e-13</td><td>0.0</td><td>0.0</td><td>945.0</td><td>999.0</td><td>1976.2</td><td>-999999500.0</td><td>1</td><td>-999999500.0</td><td>0</td><td>-999999500.0</td><td>0</td><td>17.22</td><td>-999999500.0</td><td>0</td><td>10.02</td><td>2.0023563</td></tr>
+<tr><td>5888400445251</td><td>1371</td><td>282435</td><td>202.472919444444</td><td>47.1954444444444</td><td>2.081668e-13</td><td>2.081668e-13</td><td>0.0</td><td>0.0</td><td>999.0</td><td>999.0</td><td>1981.8</td><td>-999999500.0</td><td>1</td><td>9.4</td><td>9</td><td>-999999500.0</td><td>0</td><td>7.86</td><td>-999999500.0</td><td>0</td><td>8.98</td><td>0.13680966</td></tr>
+<tr><td>5892695420475</td><td>1372</td><td>290363</td><td>202.494625</td><td>47.2065472222222</td><td>2.081668e-13</td><td>2.081668e-13</td><td>0.0</td><td>0.0</td><td>332.0</td><td>999.0</td><td>1956.2</td><td>20.13</td><td>3</td><td>-999999500.0</td><td>0</td><td>-999999500.0</td><td>0</td><td>-999999500.0</td><td>-999999500.0</td><td>4</td><td>15.79</td><td>1.2253959</td></tr>
+<tr><td>5892695420458</td><td>1372</td><td>290346</td><td>202.436875</td><td>47.2094416666667</td><td>2.081668e-13</td><td>2.081668e-13</td><td>0.0</td><td>0.0</td><td>999.0</td><td>359.0</td><td>1976.2</td><td>-999999500.0</td><td>1</td><td>-999999500.0</td><td>0</td><td>-999999500.0</td><td>0</td><td>10.89</td><td>-999999500.0</td><td>0</td><td>13.27</td><td>1.5814877</td></tr>
+<tr><td>5892695420468</td><td>1372</td><td>290356</td><td>202.469830555556</td><td>47.2232805555556</td><td>2.081668e-13</td><td>2.081668e-13</td><td>0.0</td><td>0.0</td><td>560.0</td><td>934.0</td><td>1976.2</td><td>-999999500.0</td><td>3</td><td>-999999500.0</td><td>0</td><td>-999999500.0</td><td>0</td><td>18.4</td><td>-999999500.0</td><td>0</td><td>17.78</td><td>1.6813658</td></tr>
+<tr><td>5888400445256</td><td>1371</td><td>282440</td><td>202.480638888889</td><td>47.1682194444444</td><td>-20.0</td><td>-6.0</td><td>5.0</td><td>5.0</td><td>205.0</td><td>201.0</td><td>1969.5</td><td>12.79</td><td>8</td><td>-999999500.0</td><td>0</td><td>-999999500.0</td><td>0</td><td>14.87</td><td>-999999500.0</td><td>1</td><td>15.4</td><td>1.6839056</td></tr>
+<tr><td>5892695420469</td><td>1372</td><td>290357</td><td>202.4706</td><td>47.2235555555556</td><td>2.081668e-13</td><td>2.081668e-13</td><td>0.0</td><td>0.0</td><td>709.0</td><td>130.0</td><td>1956.2</td><td>15.89</td><td>3</td><td>-999999500.0</td><td>0</td><td>-999999500.0</td><td>0</td><td>-999999500.0</td><td>-999999500.0</td><td>1</td><td>17.68</td><td>1.6983474</td></tr>
+<tr><td>5892695420470</td><td>1372</td><td>290358</td><td>202.474338888889</td><td>47.2264416666667</td><td>2.081668e-13</td><td>2.081668e-13</td><td>0.0</td><td>0.0</td><td>200.0</td><td>490.0</td><td>1956.2</td><td>13.49</td><td>4</td><td>-999999500.0</td><td>0</td><td>-999999500.0</td><td>0</td><td>-999999500.0</td><td>-999999500.0</td><td>1</td><td>18.74</td><td>1.8810483</td></tr>
+<tr><td>5888400445204</td><td>1371</td><td>282388</td><td>202.423558333333</td><td>47.1977666666667</td><td>2.081668e-13</td><td>2.081668e-13</td><td>0.0</td><td>0.0</td><td>466.0</td><td>480.0</td><td>1969.5</td><td>15.66</td><td>8</td><td>-999999500.0</td><td>0</td><td>-999999500.0</td><td>0</td><td>14.97</td><td>-999999500.0</td><td>1</td><td>15.22</td><td>1.8820877</td></tr>
+<tr><td>5888400445231</td><td>1371</td><td>282415</td><td>202.459627777778</td><td>47.1625777777778</td><td>2.081668e-13</td><td>2.081668e-13</td><td>0.0</td><td>0.0</td><td>945.0</td><td>999.0</td><td>1976.2</td><td>-999999500.0</td><td>1</td><td>-999999500.0</td><td>0</td><td>-999999500.0</td><td>0</td><td>17.22</td><td>-999999500.0</td><td>0</td><td>10.02</td><td>2.0023582</td></tr>
 <tr><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td></tr>
-<tr><td>5888400445151</td><td>1371</td><td>282335</td><td>202.351194444444</td><td>47.1387361111111</td><td>4.0</td><td>12.0</td><td>0.0</td><td>12.0</td><td>23.0</td><td>324.0</td><td>1981.2</td><td>20.72</td><td>0</td><td>20.92</td><td>7</td><td>19.53</td><td>3</td><td>-999999500.0</td><td>19.53</td><td>1</td><td>-999999500.0</td><td>5.9008446</td></tr>
-<tr><td>5888400445298</td><td>1371</td><td>282482</td><td>202.515788888889</td><td>47.1018111111111</td><td>2.081668e-13</td><td>2.081668e-13</td><td>0.0</td><td>0.0</td><td>394.0</td><td>190.0</td><td>1975.3</td><td>20.84</td><td>0</td><td>-999999500.0</td><td>0</td><td>17.89</td><td>1</td><td>-999999500.0</td><td>17.89</td><td>2</td><td>-999999500.0</td><td>5.915472</td></tr>
-<tr><td>5888400445142</td><td>1371</td><td>282326</td><td>202.342727777778</td><td>47.1468222222222</td><td>2.081668e-13</td><td>2.081668e-13</td><td>0.0</td><td>0.0</td><td>999.0</td><td>999.0</td><td>1995.6</td><td>-999999500.0</td><td>0</td><td>21.08</td><td>4</td><td>20.49</td><td>5</td><td>17.92</td><td>20.49</td><td>0</td><td>-999999500.0</td><td>5.934256</td></tr>
-<tr><td>5888400445376</td><td>1371</td><td>282560</td><td>202.609608333333</td><td>47.167975</td><td>2.081668e-13</td><td>2.081668e-13</td><td>0.0</td><td>0.0</td><td>999.0</td><td>999.0</td><td>1996.8</td><td>-999999500.0</td><td>0</td><td>-999999500.0</td><td>0</td><td>20.82</td><td>3</td><td>19.06</td><td>20.82</td><td>0</td><td>-999999500.0</td><td>5.9406395</td></tr>
-<tr><td>5888400445150</td><td>1371</td><td>282334</td><td>202.350063888889</td><td>47.1384194444444</td><td>2.081668e-13</td><td>2.081668e-13</td><td>0.0</td><td>0.0</td><td>999.0</td><td>999.0</td><td>1975.3</td><td>-999999500.0</td><td>3</td><td>20.53</td><td>1</td><td>-999999500.0</td><td>0</td><td>-999999500.0</td><td>-999999500.0</td><td>0</td><td>19.62</td><td>5.9495263</td></tr>
-<tr><td>5888400445175</td><td>1371</td><td>282359</td><td>202.374458333333</td><td>47.1198861111111</td><td>-54.0</td><td>296.0</td><td>13.0</td><td>13.0</td><td>352.0</td><td>352.0</td><td>1981.7</td><td>-999999500.0</td><td>3</td><td>19.74</td><td>3</td><td>20.36</td><td>1</td><td>-999999500.0</td><td>20.36</td><td>0</td><td>19.55</td><td>5.9591174</td></tr>
-<tr><td>5892695420507</td><td>1372</td><td>290395</td><td>202.586555555556</td><td>47.2552055555556</td><td>2.081668e-13</td><td>2.081668e-13</td><td>0.0</td><td>0.0</td><td>783.0</td><td>999.0</td><td>1976.2</td><td>20.84</td><td>0</td><td>-999999500.0</td><td>0</td><td>-999999500.0</td><td>0</td><td>19.2</td><td>-999999500.0</td><td>2</td><td>-999999500.0</td><td>5.9714193</td></tr>
-<tr><td>5888400445176</td><td>1371</td><td>282360</td><td>202.374952777778</td><td>47.119275</td><td>2.081668e-13</td><td>2.081668e-13</td><td>0.0</td><td>0.0</td><td>200.0</td><td>76.0</td><td>1979.2</td><td>20.84</td><td>2</td><td>19.89</td><td>2</td><td>18.84</td><td>10</td><td>18.56</td><td>18.84</td><td>9</td><td>19.42</td><td>5.9739494</td></tr>
-<tr><td>5888400445139</td><td>1371</td><td>282323</td><td>202.340863888889</td><td>47.1474416666667</td><td>-34.0</td><td>-26.0</td><td>13.0</td><td>4.0</td><td>313.0</td><td>111.0</td><td>1985.0</td><td>-999999500.0</td><td>3</td><td>19.1</td><td>9</td><td>18.0</td><td>2</td><td>17.74</td><td>18.0</td><td>0</td><td>19.6</td><td>5.982718</td></tr>
+<tr><td>5888400445151</td><td>1371</td><td>282335</td><td>202.351194444444</td><td>47.1387361111111</td><td>4.0</td><td>12.0</td><td>0.0</td><td>12.0</td><td>23.0</td><td>324.0</td><td>1981.2</td><td>20.72</td><td>0</td><td>20.92</td><td>7</td><td>19.53</td><td>3</td><td>-999999500.0</td><td>19.53</td><td>1</td><td>-999999500.0</td><td>5.9008455</td></tr>
+<tr><td>5888400445298</td><td>1371</td><td>282482</td><td>202.515788888889</td><td>47.1018111111111</td><td>2.081668e-13</td><td>2.081668e-13</td><td>0.0</td><td>0.0</td><td>394.0</td><td>190.0</td><td>1975.3</td><td>20.84</td><td>0</td><td>-999999500.0</td><td>0</td><td>17.89</td><td>1</td><td>-999999500.0</td><td>17.89</td><td>2</td><td>-999999500.0</td><td>5.915474</td></tr>
+<tr><td>5888400445142</td><td>1371</td><td>282326</td><td>202.342727777778</td><td>47.1468222222222</td><td>2.081668e-13</td><td>2.081668e-13</td><td>0.0</td><td>0.0</td><td>999.0</td><td>999.0</td><td>1995.6</td><td>-999999500.0</td><td>0</td><td>21.08</td><td>4</td><td>20.49</td><td>5</td><td>17.92</td><td>20.49</td><td>0</td><td>-999999500.0</td><td>5.934257</td></tr>
+<tr><td>5888400445376</td><td>1371</td><td>282560</td><td>202.609608333333</td><td>47.167975</td><td>2.081668e-13</td><td>2.081668e-13</td><td>0.0</td><td>0.0</td><td>999.0</td><td>999.0</td><td>1996.8</td><td>-999999500.0</td><td>0</td><td>-999999500.0</td><td>0</td><td>20.82</td><td>3</td><td>19.06</td><td>20.82</td><td>0</td><td>-999999500.0</td><td>5.9406404</td></tr>
+<tr><td>5888400445150</td><td>1371</td><td>282334</td><td>202.350063888889</td><td>47.1384194444444</td><td>2.081668e-13</td><td>2.081668e-13</td><td>0.0</td><td>0.0</td><td>999.0</td><td>999.0</td><td>1975.3</td><td>-999999500.0</td><td>3</td><td>20.53</td><td>1</td><td>-999999500.0</td><td>0</td><td>-999999500.0</td><td>-999999500.0</td><td>0</td><td>19.62</td><td>5.9495273</td></tr>
+<tr><td>5888400445175</td><td>1371</td><td>282359</td><td>202.374458333333</td><td>47.1198861111111</td><td>-54.0</td><td>296.0</td><td>13.0</td><td>13.0</td><td>352.0</td><td>352.0</td><td>1981.7</td><td>-999999500.0</td><td>3</td><td>19.74</td><td>3</td><td>20.36</td><td>1</td><td>-999999500.0</td><td>20.36</td><td>0</td><td>19.55</td><td>5.959119</td></tr>
+<tr><td>5892695420507</td><td>1372</td><td>290395</td><td>202.586555555556</td><td>47.2552055555556</td><td>2.081668e-13</td><td>2.081668e-13</td><td>0.0</td><td>0.0</td><td>783.0</td><td>999.0</td><td>1976.2</td><td>20.84</td><td>0</td><td>-999999500.0</td><td>0</td><td>-999999500.0</td><td>0</td><td>19.2</td><td>-999999500.0</td><td>2</td><td>-999999500.0</td><td>5.971418</td></tr>
+<tr><td>5888400445176</td><td>1371</td><td>282360</td><td>202.374952777778</td><td>47.119275</td><td>2.081668e-13</td><td>2.081668e-13</td><td>0.0</td><td>0.0</td><td>200.0</td><td>76.0</td><td>1979.2</td><td>20.84</td><td>2</td><td>19.89</td><td>2</td><td>18.84</td><td>10</td><td>18.56</td><td>18.84</td><td>9</td><td>19.42</td><td>5.973951</td></tr>
+<tr><td>5888400445139</td><td>1371</td><td>282323</td><td>202.340863888889</td><td>47.1474416666667</td><td>-34.0</td><td>-26.0</td><td>13.0</td><td>4.0</td><td>313.0</td><td>111.0</td><td>1985.0</td><td>-999999500.0</td><td>3</td><td>19.1</td><td>9</td><td>18.0</td><td>2</td><td>17.74</td><td>18.0</td><td>0</td><td>19.6</td><td>5.982719</td></tr>
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@@ -761,7 +761,7 @@ <h4>Find an image service<a class="headerlink" href="#find-an-image-service" tit
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@@ -812,7 +812,7 @@ <h4>Download an image<a class="headerlink" href="#download-an-image" title="Link
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@@ -1779,15 +1779,15 @@ <h3>2.5 Table search<a class="headerlink" href="#table-search" title="Link to th
 ulxngcat                       - Ultraluminous X-Ray Sources in Nearby Galaxies Catalog
 ulxrbcat                       - Ultraluminous X-Ray Sources in External Galaxies Catalog
 upprscoxmm                     - Upper Sco XMM-Newton X-Ray Point Source Catalog
-uvotbscat                      - UVOT Bright Star Catalog
+</pre></div>
+</div>
+<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>uvotbscat                      - UVOT Bright Star Catalog
 uvqs                           - UV-Bright Quasar Survey (UVQS) DR1 Catalog
 uzc                            - Updated Zwicky Catalog
 vela5b                         - Vela 5B All-Sky Monitor Lightcurves
 verimaster                     - VERITAS Source Catalog
 veroncat                       - Veron Catalog of Quasars &amp; AGN, 13th Edition
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-</div>
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+vla23901p4                     - VLA A2390 Cluster of Galaxies 1.4-GHz Source Catalog
 vla3701p4                      - VLA A370 Cluster of Galaxies 1.4-GHz Source Catalog
 vla74mhzdp                     - VLA 74-MHz Deep High-Resolution Survey Source Catalog
 vlacdfscat                     - VLA Survey of Chandra Deep Field South
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 <thead><tr><th></th><th></th><th>degrees</th><th>degrees</th><th></th><th>km / s</th><th></th><th></th><th></th><th>arcmin</th><th></th><th></th><th></th><th></th><th></th><th></th><th></th></tr></thead>
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diff --git a/content/reference_notebooks/catalog_queries.html b/content/reference_notebooks/catalog_queries.html
index e1628bb..407df96 100644
--- a/content/reference_notebooks/catalog_queries.html
+++ b/content/reference_notebooks/catalog_queries.html
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+    (202.469575, 47.19525833)&gt;
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 <tr><td>ivo://cds.vizier/j/a+a/408/905</td><td>J/A+A/408/905</td><td>Very Luminous Galaxies</td></tr>
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 <thead><tr><th>float64</th><th>float64</th><th>int32</th><th>int16</th><th>float32</th><th>int16</th></tr></thead>
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 <thead><tr><th></th><th></th><th>deg</th><th>deg</th><th>deg</th><th>deg</th><th></th><th></th><th></th><th>s</th><th>s</th><th></th><th>d</th><th>d</th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th>deg</th><th>d</th><th>d</th><th></th><th></th><th></th><th></th></tr></thead>
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 <thead><tr><th>float64</th><th>float64</th><th>int32</th><th>float32</th><th>int16</th><th>float64</th><th>float64</th></tr></thead>
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 <thead><tr><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>int32</th><th>int16</th><th>float32</th></tr></thead>
diff --git a/content/reference_notebooks/image_access.html b/content/reference_notebooks/image_access.html
index 71193e2..488ea76 100644
--- a/content/reference_notebooks/image_access.html
+++ b/content/reference_notebooks/image_access.html
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 <thead><tr><th>ivoid</th><th>short_name</th><th>res_title</th></tr></thead>
 <thead><tr><th>object</th><th>object</th><th>object</th></tr></thead>
 <tr><td>ivo://archive.stsci.edu/sia/galex</td><td>GALEX</td><td>Galaxy Evolution Explorer (GALEX)</td></tr>
@@ -566,7 +566,7 @@ <h2>1. Finding SIA resources from the Registry<a class="headerlink" href="#findi
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 <div class="output text_html"><div><i>Table length=1</i>
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 <thead><tr><th>object</th><th>object</th><th>object</th></tr></thead>
 <tr><td>ivo://nasa.heasarc/skyview/swiftuvot</td><td>SWIFTUVOT</td><td>Swift UVOT Combined V Intensity Images</td></tr>
@@ -589,15 +589,15 @@ <h2>2. Using SIA to retrieve an image<a class="headerlink" href="#using-sia-to-r
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 <div class="output text_html"><div><i>Table length=6</i>
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 <thead><tr><th>Survey</th><th>Ra</th><th>Dec</th><th>Dim</th><th>Size</th><th>Scale</th><th>Format</th><th>PixFlags</th><th>URL</th><th>LogicalName</th></tr></thead>
 <thead><tr><th>object</th><th>float64</th><th>float64</th><th>int32</th><th>object</th><th>object</th><th>object</th><th>object</th><th>object</th><th>object</th></tr></thead>
-<tr><td>swiftuvotvint</td><td>202.469575</td><td>47.1952583</td><td>2</td><td>[300 300]</td><td>[-0.0006666666666666668 0.0006666666666666668]</td><td>image/jpeg</td><td>F</td><td>https://skyview.gsfc.nasa.gov/cgi-bin/images?position=202.469575%2C47.1952583&amp;survey=swiftuvotvint&amp;pixels=300%2C300&amp;sampler=LI&amp;size=0.20000000000000004%2C0.20000000000000004&amp;projection=Tan&amp;coordinates=J2000.0&amp;requestID=skv1734385753936&amp;nofits=1&amp;quicklook=jpeg&amp;return=jpeg</td><td>1</td></tr>
-<tr><td>swiftuvotbint</td><td>202.469575</td><td>47.1952583</td><td>2</td><td>[300 300]</td><td>[-0.0006666666666666668 0.0006666666666666668]</td><td>image/jpeg</td><td>F</td><td>https://skyview.gsfc.nasa.gov/cgi-bin/images?position=202.469575%2C47.1952583&amp;survey=swiftuvotbint&amp;pixels=300%2C300&amp;sampler=LI&amp;size=0.20000000000000004%2C0.20000000000000004&amp;projection=Tan&amp;coordinates=J2000.0&amp;requestID=skv1734385754201&amp;nofits=1&amp;quicklook=jpeg&amp;return=jpeg</td><td>2</td></tr>
-<tr><td>swiftuvotuint</td><td>202.469575</td><td>47.1952583</td><td>2</td><td>[300 300]</td><td>[-0.0006666666666666668 0.0006666666666666668]</td><td>image/jpeg</td><td>F</td><td>https://skyview.gsfc.nasa.gov/cgi-bin/images?position=202.469575%2C47.1952583&amp;survey=swiftuvotuint&amp;pixels=300%2C300&amp;sampler=LI&amp;size=0.20000000000000004%2C0.20000000000000004&amp;projection=Tan&amp;coordinates=J2000.0&amp;requestID=skv1734385755295&amp;nofits=1&amp;quicklook=jpeg&amp;return=jpeg</td><td>3</td></tr>
-<tr><td>swiftuvotuvw1int</td><td>202.469575</td><td>47.1952583</td><td>2</td><td>[300 300]</td><td>[-0.0006666666666666668 0.0006666666666666668]</td><td>image/jpeg</td><td>F</td><td>https://skyview.gsfc.nasa.gov/cgi-bin/images?position=202.469575%2C47.1952583&amp;survey=swiftuvotuvw1int&amp;pixels=300%2C300&amp;sampler=LI&amp;size=0.20000000000000004%2C0.20000000000000004&amp;projection=Tan&amp;coordinates=J2000.0&amp;requestID=skv1734385755771&amp;nofits=1&amp;quicklook=jpeg&amp;return=jpeg</td><td>4</td></tr>
-<tr><td>swiftuvotuvw2int</td><td>202.469575</td><td>47.1952583</td><td>2</td><td>[300 300]</td><td>[-0.0006666666666666668 0.0006666666666666668]</td><td>image/jpeg</td><td>F</td><td>https://skyview.gsfc.nasa.gov/cgi-bin/images?position=202.469575%2C47.1952583&amp;survey=swiftuvotuvw2int&amp;pixels=300%2C300&amp;sampler=LI&amp;size=0.20000000000000004%2C0.20000000000000004&amp;projection=Tan&amp;coordinates=J2000.0&amp;requestID=skv1734385756228&amp;nofits=1&amp;quicklook=jpeg&amp;return=jpeg</td><td>5</td></tr>
-<tr><td>swiftuvotuvm2int</td><td>202.469575</td><td>47.1952583</td><td>2</td><td>[300 300]</td><td>[-0.0006666666666666668 0.0006666666666666668]</td><td>image/jpeg</td><td>F</td><td>https://skyview.gsfc.nasa.gov/cgi-bin/images?position=202.469575%2C47.1952583&amp;survey=swiftuvotuvm2int&amp;pixels=300%2C300&amp;sampler=LI&amp;size=0.20000000000000004%2C0.20000000000000004&amp;projection=Tan&amp;coordinates=J2000.0&amp;requestID=skv1734385756659&amp;nofits=1&amp;quicklook=jpeg&amp;return=jpeg</td><td>6</td></tr>
+<tr><td>swiftuvotvint</td><td>202.469575</td><td>47.19525833</td><td>2</td><td>[300 300]</td><td>[-0.0006666666666666668 0.0006666666666666668]</td><td>image/jpeg</td><td>F</td><td>https://skyview.gsfc.nasa.gov/cgi-bin/images?position=202.469575%2C47.19525833&amp;survey=swiftuvotvint&amp;pixels=300%2C300&amp;sampler=LI&amp;size=0.20000000000000004%2C0.20000000000000004&amp;projection=Tan&amp;coordinates=J2000.0&amp;requestID=skv1734402145351&amp;nofits=1&amp;quicklook=jpeg&amp;return=jpeg</td><td>1</td></tr>
+<tr><td>swiftuvotbint</td><td>202.469575</td><td>47.19525833</td><td>2</td><td>[300 300]</td><td>[-0.0006666666666666668 0.0006666666666666668]</td><td>image/jpeg</td><td>F</td><td>https://skyview.gsfc.nasa.gov/cgi-bin/images?position=202.469575%2C47.19525833&amp;survey=swiftuvotbint&amp;pixels=300%2C300&amp;sampler=LI&amp;size=0.20000000000000004%2C0.20000000000000004&amp;projection=Tan&amp;coordinates=J2000.0&amp;requestID=skv1734402145614&amp;nofits=1&amp;quicklook=jpeg&amp;return=jpeg</td><td>2</td></tr>
+<tr><td>swiftuvotuint</td><td>202.469575</td><td>47.19525833</td><td>2</td><td>[300 300]</td><td>[-0.0006666666666666668 0.0006666666666666668]</td><td>image/jpeg</td><td>F</td><td>https://skyview.gsfc.nasa.gov/cgi-bin/images?position=202.469575%2C47.19525833&amp;survey=swiftuvotuint&amp;pixels=300%2C300&amp;sampler=LI&amp;size=0.20000000000000004%2C0.20000000000000004&amp;projection=Tan&amp;coordinates=J2000.0&amp;requestID=skv1734402146764&amp;nofits=1&amp;quicklook=jpeg&amp;return=jpeg</td><td>3</td></tr>
+<tr><td>swiftuvotuvw1int</td><td>202.469575</td><td>47.19525833</td><td>2</td><td>[300 300]</td><td>[-0.0006666666666666668 0.0006666666666666668]</td><td>image/jpeg</td><td>F</td><td>https://skyview.gsfc.nasa.gov/cgi-bin/images?position=202.469575%2C47.19525833&amp;survey=swiftuvotuvw1int&amp;pixels=300%2C300&amp;sampler=LI&amp;size=0.20000000000000004%2C0.20000000000000004&amp;projection=Tan&amp;coordinates=J2000.0&amp;requestID=skv1734402147249&amp;nofits=1&amp;quicklook=jpeg&amp;return=jpeg</td><td>4</td></tr>
+<tr><td>swiftuvotuvw2int</td><td>202.469575</td><td>47.19525833</td><td>2</td><td>[300 300]</td><td>[-0.0006666666666666668 0.0006666666666666668]</td><td>image/jpeg</td><td>F</td><td>https://skyview.gsfc.nasa.gov/cgi-bin/images?position=202.469575%2C47.19525833&amp;survey=swiftuvotuvw2int&amp;pixels=300%2C300&amp;sampler=LI&amp;size=0.20000000000000004%2C0.20000000000000004&amp;projection=Tan&amp;coordinates=J2000.0&amp;requestID=skv1734402147720&amp;nofits=1&amp;quicklook=jpeg&amp;return=jpeg</td><td>5</td></tr>
+<tr><td>swiftuvotuvm2int</td><td>202.469575</td><td>47.19525833</td><td>2</td><td>[300 300]</td><td>[-0.0006666666666666668 0.0006666666666666668]</td><td>image/jpeg</td><td>F</td><td>https://skyview.gsfc.nasa.gov/cgi-bin/images?position=202.469575%2C47.19525833&amp;survey=swiftuvotuvm2int&amp;pixels=300%2C300&amp;sampler=LI&amp;size=0.20000000000000004%2C0.20000000000000004&amp;projection=Tan&amp;coordinates=J2000.0&amp;requestID=skv1734402148194&amp;nofits=1&amp;quicklook=jpeg&amp;return=jpeg</td><td>6</td></tr>
 </table></div></div></div>
 </div>
 <p>Extract the fields you’re interested in, e.g., the URLs of the images made by skyview.  Note that specifying as we did SwiftUVOT, we get a number of different images, e.g., UVOT U, V, B, W1, W2, etc.  For each survey, there are two URLs, first the FITS IMAGE and second the JPEG.</p>
@@ -610,7 +610,7 @@ <h2>2. Using SIA to retrieve an image<a class="headerlink" href="#using-sia-to-r
 </div>
 </div>
 <div class="cell_output docutils container">
-<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>https://skyview.gsfc.nasa.gov/cgi-bin/images?position=202.469575%2C47.1952583&amp;survey=swiftuvotvint&amp;pixels=300%2C300&amp;sampler=LI&amp;size=0.20000000000000004%2C0.20000000000000004&amp;projection=Tan&amp;coordinates=J2000.0&amp;requestID=skv1734385753936&amp;nofits=1&amp;quicklook=jpeg&amp;return=jpeg
+<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>https://skyview.gsfc.nasa.gov/cgi-bin/images?position=202.469575%2C47.19525833&amp;survey=swiftuvotvint&amp;pixels=300%2C300&amp;sampler=LI&amp;size=0.20000000000000004%2C0.20000000000000004&amp;projection=Tan&amp;coordinates=J2000.0&amp;requestID=skv1734402145351&amp;nofits=1&amp;quicklook=jpeg&amp;return=jpeg
 </pre></div>
 </div>
 </div>
@@ -629,7 +629,7 @@ <h3>JPG images<a class="headerlink" href="#jpg-images" title="Link to this headi
 </div>
 </div>
 <div class="cell_output docutils container">
-<div class="output text_html"><img src="https://skyview.gsfc.nasa.gov/cgi-bin/images?position=202.469575%2C47.1952583&survey=swiftuvotvint&pixels=300%2C300&sampler=LI&size=0.20000000000000004%2C0.20000000000000004&projection=Tan&coordinates=J2000.0&requestID=skv1734385753936&nofits=1&quicklook=jpeg&return=jpeg"/></div></div>
+<div class="output text_html"><img src="https://skyview.gsfc.nasa.gov/cgi-bin/images?position=202.469575%2C47.19525833&survey=swiftuvotvint&pixels=300%2C300&sampler=LI&size=0.20000000000000004%2C0.20000000000000004&projection=Tan&coordinates=J2000.0&requestID=skv1734402145351&nofits=1&quicklook=jpeg&return=jpeg"/></div></div>
 </div>
 </section>
 <section id="fits-files">
@@ -648,7 +648,7 @@ <h3>Fits files<a class="headerlink" href="#fits-files" title="Link to this headi
 </div>
 </div>
 <div class="cell_output docutils container">
-<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>Filename: /home/runner/.astropy/cache/download/url/a34e6c66f0392cfbe38054abfa1340d5/contents
+<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>Filename: /home/runner/.astropy/cache/download/url/dbaa17f98770f79d75b56cdce2aa43eb/contents
 No.    Name      Ver    Type      Cards   Dimensions   Format
   0  PRIMARY       1 PrimaryHDU     111   (300, 300)   float32   
 </pre></div>
@@ -664,10 +664,10 @@ <h4>Using imshow<a class="headerlink" href="#using-imshow" title="Link to this h
 </div>
 </div>
 <div class="cell_output docutils container">
-<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;matplotlib.image.AxesImage at 0x7fcd6c656710&gt;
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;matplotlib.image.AxesImage at 0x7ff9cba4a050&gt;
 </pre></div>
 </div>
-<img alt="../../_images/ba9cffa29f71b5eef810ef3ecd08a619c2bb06f6e3711eda9023615ed0435d98.png" src="../../_images/ba9cffa29f71b5eef810ef3ecd08a619c2bb06f6e3711eda9023615ed0435d98.png" />
+<img alt="../../_images/b66b585d158253440b076e39c081016643eb6cc96da8555f8e6b4a232b140957.png" src="../../_images/b66b585d158253440b076e39c081016643eb6cc96da8555f8e6b4a232b140957.png" />
 </div>
 </div>
 </section>
diff --git a/content/reference_notebooks/spectral_access.html b/content/reference_notebooks/spectral_access.html
index 3e0738d..256251d 100644
--- a/content/reference_notebooks/spectral_access.html
+++ b/content/reference_notebooks/spectral_access.html
@@ -511,7 +511,7 @@ <h2>Finding available Spectral Access Services<a class="headerlink" href="#findi
 </div>
 <div class="cell_output docutils container">
 <div class="output text_html"><div><i>Table length=7</i>
-<table id="table140019074770752" class="table-striped table-bordered table-condensed">
+<table id="table140056417968976" class="table-striped table-bordered table-condensed">
 <thead><tr><th>ivoid</th><th>short_name</th></tr></thead>
 <thead><tr><th>object</th><th>object</th></tr></thead>
 <tr><td>ivo://nasa.heasarc/chanmaster</td><td>Chandra</td></tr>
@@ -559,7 +559,7 @@ <h2>Chandra Spectrum of Delta Ori<a class="headerlink" href="#chandra-spectrum-o
 </pre></div>
 </div>
 <div class="output text_html"><i>Table length=6</i>
-<table id="table140019075760624-358844" class="table-striped table-bordered table-condensed">
+<table id="table140057343998320-562779" class="table-striped table-bordered table-condensed">
 <thead><tr><th>idx</th><th>obsid</th><th>status</th><th>name</th><th>ra</th><th>dec</th><th>time</th><th>detector</th><th>grating</th><th>exposure</th><th>type</th><th>pi</th><th>public_date</th><th>datalink</th><th>SSA_start_time</th><th>SSA_tmid</th><th>SSA_stop_time</th><th>SSA_duration</th><th>SSA_coord_obs</th><th>SSA_ra</th><th>SSA_dec</th><th>SSA_fov</th><th>SSA_title</th><th>SSA_reference</th><th>SSA_datalength</th><th>SSA_datamodel</th><th>SSA_instrument</th><th>SSA_publisher</th><th>SSA_format</th><th>SSA_wavelength_min</th><th>SSA_wavelength_max</th><th>SSA_bandwidth</th><th>SSA_bandpass</th><th>cloud_access</th></tr></thead>
 <thead><tr><th></th><th></th><th></th><th></th><th>deg</th><th>deg</th><th>d</th><th></th><th></th><th>s</th><th></th><th></th><th>d</th><th></th><th>d</th><th>d</th><th>d</th><th>s</th><th>deg</th><th>deg</th><th>deg</th><th>deg</th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th>m</th><th>m</th><th>m</th><th>m</th><th></th></tr></thead>
 <tr><td>0</td><td>639</td><td>archived</td><td>DELTA ORI</td><td>83.00125</td><td>-0.29917</td><td>51556.1364</td><td>ACIS-S</td><td>HETG</td><td>49680</td><td>GO</td><td>Cassinelli</td><td>52037</td><td>11743:chandra.obs.misc</td><td>51556.136400463</td><td>--</td><td>--</td><td>49680.0</td><td>--</td><td>83.00125</td><td>-0.29917</td><td>0.81</td><td>acisf00639N005_pha2.fits</td><td>https://heasarc.gsfc.nasa.gov/FTP/chandra/data/byobsid/9/639/primary/acisf00639N005_pha2.fits.gz</td><td>12</td><td>Spectrum-1.0</td><td>ACIS-S</td><td>HEASARC</td><td>application/fits</td><td>1.2398e-10</td><td>6.1992e-09</td><td>6.07522e-09</td><td>3.16159e-09</td><td>{&quot;aws&quot;:{&quot;bucket_name&quot;:&quot;nasa-heasarc&quot;,&quot;region&quot;:&quot;us-east-1&quot;,&quot;policy&quot;:&quot;open&quot;,&quot;key&quot;:&quot;chandra/data/byobsid/9/639/primary/acisf00639N005_pha2.fits.gz&quot;}}</td></tr>
@@ -591,14 +591,14 @@ <h2>Chandra Spectrum of Delta Ori<a class="headerlink" href="#chandra-spectrum-o
     datatables: 'https://cdn.datatables.net/1.10.12/js/jquery.dataTables.min'
 }});
 require(["datatables"], function(){
-    console.log("$('#table140019075760624-358844').dataTable()");
+    console.log("$('#table140057343998320-562779').dataTable()");
     
 jQuery.extend( jQuery.fn.dataTableExt.oSort, {
     "optionalnum-asc": astropy_sort_num,
     "optionalnum-desc": function (a,b) { return -astropy_sort_num(a, b); }
 });
 
-    $('#table140019075760624-358844').dataTable({
+    $('#table140057343998320-562779').dataTable({
         order: [],
         pageLength: 50,
         lengthMenu: [[10, 25, 50, 100, 500, 1000, -1], [10, 25, 50, 100, 500, 1000, 'All']],
@@ -635,7 +635,7 @@ <h2>Simple example of plotting a spectrum<a class="headerlink" href="#simple-exa
 </div>
 <div class="cell_output docutils container">
 <div class="output text_html"><div><i>Table length=12</i>
-<table id="table140019034219584" class="table-striped table-bordered table-condensed">
+<table id="table140056379989472" class="table-striped table-bordered table-condensed">
 <thead><tr><th>SPEC_NUM</th><th>TG_M</th><th>TG_PART</th><th>TG_SRCID</th><th>X</th><th>Y</th><th>CHANNEL</th><th>COUNTS</th><th>STAT_ERR</th><th>BACKGROUND_UP</th><th>BACKGROUND_DOWN</th><th>BIN_LO</th><th>BIN_HI</th></tr></thead>
 <thead><tr><th>int16</th><th>int16</th><th>int16</th><th>int16</th><th>float32</th><th>float32</th><th>int16[8192]</th><th>int16[8192]</th><th>float32[8192]</th><th>int16[8192]</th><th>int16[8192]</th><th>float64[8192]</th><th>float64[8192]</th></tr></thead>
 <tr><td>1</td><td>-3</td><td>1</td><td>1</td><td>4094.9138</td><td>4132.076</td><td>1 .. 8192</td><td>0 .. 0</td><td>1.8660254 .. 1.8660254</td><td>0 .. 0</td><td>0 .. 0</td><td>7.159166666667378 .. 0.3333333333333333</td><td>7.160000000000712 .. 0.33416666666666667</td></tr>
diff --git a/content/reference_notebooks/ucds_unified_content_descriptors.html b/content/reference_notebooks/ucds_unified_content_descriptors.html
index 3d581d8..b454f30 100644
--- a/content/reference_notebooks/ucds_unified_content_descriptors.html
+++ b/content/reference_notebooks/ucds_unified_content_descriptors.html
@@ -514,25 +514,25 @@ <h1>UCDs (Unified Content Descriptors)<a class="headerlink" href="#ucds-unified-
 ----
 tap_schema.tables              - description of tables in this dataset
 ----
+tap_schema.columns             - description of columns in this dataset
+----
 </pre></div>
 </div>
-<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>tap_schema.columns             - description of columns in this dataset
-----
-tap_schema.keys                - description of foreign keys in this dataset
+<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>tap_schema.keys                - description of foreign keys in this dataset
 ----
 tap_schema.key_columns         - description of foreign key columns in this dataset
 ----
+dbo.detailedcatalog            - Detailed list of source catalog parameters
+----
 </pre></div>
 </div>
-<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>dbo.detailedcatalog            - Detailed list of source catalog parameters
+<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>dbo.hcvdetailedview            - Detailed list of Hubble Catalog of Variables parameters
 ----
-dbo.hcvdetailedview            - Detailed list of Hubble Catalog of Variables parameters
+dbo.hcvsummaryview             - Summary list of Hubble Catalog of Variables parameters
 ----
 </pre></div>
 </div>
-<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>dbo.hcvsummaryview             - Summary list of Hubble Catalog of Variables parameters
-----
-dbo.propermotionsview          - List of proper motion information
+<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>dbo.propermotionsview          - List of proper motion information
 ----
 dbo.sourcepositionsview        - List of source position information
 ----
@@ -540,11 +540,11 @@ <h1>UCDs (Unified Content Descriptors)<a class="headerlink" href="#ucds-unified-
 </div>
 <div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>dbo.summagaper2catview         - Summary list of source catalog with Aper2 magnitudes
 ----
+dbo.summagautocatview          - Summary list of source catalog with MagAuto magnitudes
+----
 </pre></div>
 </div>
-<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>dbo.summagautocatview          - Summary list of source catalog with MagAuto magnitudes
-----
-dbo.catalog_image_metadata     - Summary list of Image processing metadata
+<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>dbo.catalog_image_metadata     - Summary list of Image processing metadata
 ----
 </pre></div>
 </div>
diff --git a/content/use_case_notebooks/candidate_list_solution.html b/content/use_case_notebooks/candidate_list_solution.html
index 6ed4438..138e8b6 100644
--- a/content/use_case_notebooks/candidate_list_solution.html
+++ b/content/use_case_notebooks/candidate_list_solution.html
@@ -541,7 +541,7 @@ <h2>2. Search NED for objects in this paper<a class="headerlink" href="#search-n
 </pre></div>
 </div>
 <div class="output text_html"><i>Table length=62</i>
-<table id="table140616360887008-313595" class="table-striped table-bordered table-condensed">
+<table id="table139897424905120-953511" class="table-striped table-bordered table-condensed">
 <thead><tr><th>idx</th><th>No.</th><th>Object Name</th><th>RA</th><th>DEC</th><th>Type</th><th>Velocity</th><th>Redshift</th><th>Redshift Flag</th><th>Magnitude and Filter</th><th>Separation</th><th>References</th><th>Notes</th><th>Photometry Points</th><th>Positions</th><th>Redshift Points</th><th>Diameter Points</th><th>Associations</th></tr></thead>
 <thead><tr><th></th><th></th><th></th><th>degrees</th><th>degrees</th><th></th><th>km / s</th><th></th><th></th><th></th><th>arcmin</th><th></th><th></th><th></th><th></th><th></th><th></th><th></th></tr></thead>
 <tr><td>0</td><td>1</td><td>WISEA J001550.14-100242.3</td><td>3.95892</td><td>-10.04511</td><td>G</td><td>52766.0</td><td>0.17601</td><td>SLS</td><td>17.5g</td><td>--</td><td>15</td><td>0</td><td>63</td><td>8</td><td>9</td><td>10</td><td>0</td></tr>
@@ -629,14 +629,14 @@ <h2>2. Search NED for objects in this paper<a class="headerlink" href="#search-n
     datatables: 'https://cdn.datatables.net/1.10.12/js/jquery.dataTables.min'
 }});
 require(["datatables"], function(){
-    console.log("$('#table140616360887008-313595').dataTable()");
+    console.log("$('#table139897424905120-953511').dataTable()");
     
 jQuery.extend( jQuery.fn.dataTableExt.oSort, {
     "optionalnum-asc": astropy_sort_num,
     "optionalnum-desc": function (a,b) { return -astropy_sort_num(a, b); }
 });
 
-    $('#table140616360887008-313595').dataTable({
+    $('#table139897424905120-953511').dataTable({
         order: [],
         pageLength: 50,
         lengthMenu: [[10, 25, 50, 100, 500, 1000, -1], [10, 25, 50, 100, 500, 1000, 'All']],
@@ -704,7 +704,7 @@ <h2>3. Filter the NED results<a class="headerlink" href="#filter-the-ned-results
 </pre></div>
 </div>
 <div class="output text_html"><i>Table length=53</i>
-<table id="table140615424395584-268780" class="table-striped table-bordered table-condensed">
+<table id="table139896471553360-93962" class="table-striped table-bordered table-condensed">
 <thead><tr><th>idx</th><th>No.</th><th>Object Name</th><th>RA</th><th>DEC</th><th>Type</th><th>Velocity</th><th>Redshift</th><th>Redshift Flag</th><th>Magnitude and Filter</th><th>Separation</th><th>References</th><th>Notes</th><th>Photometry Points</th><th>Positions</th><th>Redshift Points</th><th>Diameter Points</th><th>Associations</th></tr></thead>
 <thead><tr><th></th><th></th><th></th><th>degrees</th><th>degrees</th><th></th><th>km / s</th><th></th><th></th><th></th><th>arcmin</th><th></th><th></th><th></th><th></th><th></th><th></th><th></th></tr></thead>
 <tr><td>0</td><td>1</td><td>WISEA J001550.14-100242.3</td><td>3.95892</td><td>-10.04511</td><td>G</td><td>52766.0</td><td>0.17601</td><td>SLS</td><td>17.5g</td><td>--</td><td>15</td><td>0</td><td>63</td><td>8</td><td>9</td><td>10</td><td>0</td></tr>
@@ -783,14 +783,14 @@ <h2>3. Filter the NED results<a class="headerlink" href="#filter-the-ned-results
     datatables: 'https://cdn.datatables.net/1.10.12/js/jquery.dataTables.min'
 }});
 require(["datatables"], function(){
-    console.log("$('#table140615424395584-268780').dataTable()");
+    console.log("$('#table139896471553360-93962').dataTable()");
     
 jQuery.extend( jQuery.fn.dataTableExt.oSort, {
     "optionalnum-asc": astropy_sort_num,
     "optionalnum-desc": function (a,b) { return -astropy_sort_num(a, b); }
 });
 
-    $('#table140615424395584-268780').dataTable({
+    $('#table139896471553360-93962').dataTable({
         order: [],
         pageLength: 50,
         lengthMenu: [[10, 25, 50, 100, 500, 1000, -1], [10, 25, 50, 100, 500, 1000, 'All']],
@@ -820,7 +820,7 @@ <h2>4. Search the NAVO Registry for image resources<a class="headerlink" href="#
 </pre></div>
 </div>
 <div class="output text_html"><div><i>Table length=322</i>
-<table id="table140615424398848" class="table-striped table-bordered table-condensed">
+<table id="table139896471556672" class="table-striped table-bordered table-condensed">
 <thead><tr><th>ivoid</th><th>short_name</th><th>res_title</th></tr></thead>
 <thead><tr><th>object</th><th>object</th><th>object</th></tr></thead>
 <tr><td>ivo://3crsnapshots/sia</td><td>3CRSnap.sia</td><td>3CRSnapshots Simple Image Access Service</td></tr>
@@ -864,7 +864,7 @@ <h2>5. Search the NAVO Registry for image resources that will allow you to searc
 </pre></div>
 </div>
 <div class="output text_html"><div><i>Table length=1</i>
-<table id="table140615419760016" class="table-striped table-bordered table-condensed">
+<table id="table139896467564736" class="table-striped table-bordered table-condensed">
 <thead><tr><th>ivoid</th><th>short_name</th><th>res_title</th></tr></thead>
 <thead><tr><th>object</th><th>object</th><th>object</th></tr></thead>
 <tr><td>ivo://irsa.ipac/wise/images/allwise/l3a</td><td>AllWISE L3a</td><td>AllWISE Atlas (L3a) Coadd Images</td></tr>
@@ -947,7 +947,7 @@ <h2>9. Use the .to_table() method to view the results as an Astropy table<a clas
 </div>
 <div class="cell_output docutils container">
 <div class="output text_html"><div><i>Table length=4</i>
-<table id="table140615420394752" class="table-striped table-bordered table-condensed">
+<table id="table139896467668320" class="table-striped table-bordered table-condensed">
 <thead><tr><th>sia_title</th><th>sia_url</th><th>cloud_access</th><th>sia_naxes</th><th>sia_fmt</th><th>sia_ra</th><th>sia_dec</th><th>sia_naxis</th><th>sia_crpix</th><th>sia_crval</th><th>sia_proj</th><th>sia_scale</th><th>sia_cd</th><th>sia_bp_id</th><th>sia_bp_ref</th><th>sia_bp_hi</th><th>sia_bp_lo</th><th>sia_bp_unit</th><th>magzp</th><th>magzpunc</th><th>unc_url</th><th>cov_url</th><th>coadd_id</th></tr></thead>
 <thead><tr><th></th><th></th><th></th><th></th><th></th><th>deg</th><th>deg</th><th></th><th>pix</th><th>deg</th><th></th><th>deg / pix</th><th>deg / pix</th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th></tr></thead>
 <thead><tr><th>object</th><th>object</th><th>object</th><th>int32</th><th>object</th><th>float64</th><th>float64</th><th>int32[2]</th><th>float64[2]</th><th>float64[2]</th><th>object</th><th>float64[2]</th><th>float64[4]</th><th>object</th><th>float64</th><th>float64</th><th>float64</th><th>object</th><th>float64</th><th>float64</th><th>object</th><th>object</th><th>object</th></tr></thead>
@@ -1008,7 +1008,7 @@ <h2>11. Visualize this AllWISE image<a class="headerlink" href="#visualize-this-
 </div>
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 <div class="cell_output docutils container">
-<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;matplotlib.collections.PathCollection at 0x7fe393efe5f0&gt;
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;matplotlib.collections.PathCollection at 0x7f3c2f02df60&gt;
 </pre></div>
 </div>
 <img alt="../../_images/99c3c57cd0e8b4ac127daf7659df26cb47a7566b0ee83d6e59c1dca8217b280b.png" src="../../_images/99c3c57cd0e8b4ac127daf7659df26cb47a7566b0ee83d6e59c1dca8217b280b.png" />
@@ -1033,7 +1033,7 @@ <h2>12. Plot a cutout of the AllWISE image, centered on your position<a class="h
 </div>
 </div>
 <div class="cell_output docutils container">
-<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;matplotlib.collections.PathCollection at 0x7fe38bc7cc40&gt;
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;matplotlib.collections.PathCollection at 0x7f3c26d74220&gt;
 </pre></div>
 </div>
 <img alt="../../_images/07fac4eeb5c02470f6d9deef914353d7cfbd875541d034f680f13f6db72d8a7e.png" src="../../_images/07fac4eeb5c02470f6d9deef914353d7cfbd875541d034f680f13f6db72d8a7e.png" />
@@ -1056,7 +1056,7 @@ <h2>13. Try visualizing a cutout of a GALEX image that covers your position<a cl
 </pre></div>
 </div>
 <div class="output text_html"><div><i>Table length=3</i>
-<table id="table140615279605264" class="table-striped table-bordered table-condensed">
+<table id="table139896326421328" class="table-striped table-bordered table-condensed">
 <thead><tr><th>ivoid</th><th>short_name</th><th>res_title</th></tr></thead>
 <thead><tr><th>object</th><th>object</th><th>object</th></tr></thead>
 <tr><td>ivo://archive.stsci.edu/sia/galex</td><td>GALEX</td><td>Galaxy Evolution Explorer (GALEX)</td></tr>
@@ -1091,7 +1091,7 @@ <h2>13. Try visualizing a cutout of a GALEX image that covers your position<a cl
 </div>
 </div>
 <div class="cell_output docutils container">
-<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>AIS_270_0004_sg14-nd-int.fits.gz NUV
+<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>AIS_270_sg14-nd-int.fits.gz NUV
 </pre></div>
 </div>
 </div>
@@ -1118,9 +1118,9 @@ <h2>13. Try visualizing a cutout of a GALEX image that covers your position<a cl
 </div>
 <div class="cell_output docutils container">
 <div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>Min: 0.0
-Max: 8.866534
-Mean: 0.0014750387
-Stdev: 0.013614772
+Max: 7.1870303
+Mean: 0.0014934327
+Stdev: 0.012639926
 </pre></div>
 </div>
 </div>
@@ -1135,10 +1135,10 @@ <h2>13. Try visualizing a cutout of a GALEX image that covers your position<a cl
 </div>
 </div>
 <div class="cell_output docutils container">
-<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;matplotlib.collections.PathCollection at 0x7fe388a944c0&gt;
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;matplotlib.collections.PathCollection at 0x7f3c24b0efb0&gt;
 </pre></div>
 </div>
-<img alt="../../_images/7113bf8838459efca35dc42634789c65727473b0f77c8069ac322a43b484d19f.png" src="../../_images/7113bf8838459efca35dc42634789c65727473b0f77c8069ac322a43b484d19f.png" />
+<img alt="../../_images/709471c04f3485c1924208d699a17e5a3b302c2f513c426a456b19a23847adf9.png" src="../../_images/709471c04f3485c1924208d699a17e5a3b302c2f513c426a456b19a23847adf9.png" />
 </div>
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 <div class="cell docutils container">
@@ -1154,10 +1154,10 @@ <h2>13. Try visualizing a cutout of a GALEX image that covers your position<a cl
 </div>
 </div>
 <div class="cell_output docutils container">
-<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;matplotlib.collections.PathCollection at 0x7fe38890cb50&gt;
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;matplotlib.collections.PathCollection at 0x7f3c24b90eb0&gt;
 </pre></div>
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-<img alt="../../_images/3c0e2c37bbc263b0058a1bc0769df333d3f253eba1e5879ebbcf0a11726d74a9.png" src="../../_images/3c0e2c37bbc263b0058a1bc0769df333d3f253eba1e5879ebbcf0a11726d74a9.png" />
+<img alt="../../_images/a7fdc1e8c14db6bd7ab9ea9ddd10bbca10ff3b2e3d9567c0e377d80f44adbafc.png" src="../../_images/a7fdc1e8c14db6bd7ab9ea9ddd10bbca10ff3b2e3d9567c0e377d80f44adbafc.png" />
 </div>
 </div>
 </section>
@@ -1178,7 +1178,7 @@ <h2>14. Try visualizing a cutout of an SDSS image that covers your position<a cl
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 <div class="cell_output docutils container">
 <div class="output text_html"><div><i>Table length=21</i>
-<table id="table140615227112848" class="table-striped table-bordered table-condensed">
+<table id="table139896326417824" class="table-striped table-bordered table-condensed">
 <thead><tr><th>ivoid</th><th>short_name</th><th>res_title</th><th>source_value</th></tr></thead>
 <thead><tr><th>object</th><th>object</th><th>object</th><th>object</th></tr></thead>
 <tr><td>ivo://mast.stsci/siap/al218</td><td>VLA.AL218</td><td>VLA-A Array AL218 Texas Survey Source Snapshots (AL218)</td><td></td></tr>
@@ -1275,7 +1275,7 @@ <h2>14. Try visualizing a cutout of an SDSS image that covers your position<a cl
 <div class="output stderr highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>WARNING: FITSFixedWarning: &#39;datfix&#39; made the change &#39;Set MJD-OBS to 54007.000000 from DATE-OBS&#39;. [astropy.wcs.wcs]
 </pre></div>
 </div>
-<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;matplotlib.collections.PathCollection at 0x7fe3889e3e80&gt;
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;matplotlib.collections.PathCollection at 0x7f3c24abb3d0&gt;
 </pre></div>
 </div>
 <img alt="../../_images/c6437eda497b676362e20637ad992737a2bbe1bfb2b33b7b32b18ecb6dc952c5.png" src="../../_images/c6437eda497b676362e20637ad992737a2bbe1bfb2b33b7b32b18ecb6dc952c5.png" />
@@ -1297,7 +1297,7 @@ <h2>14. Try visualizing a cutout of an SDSS image that covers your position<a cl
 <div class="output stderr highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>WARNING: FITSFixedWarning: &#39;datfix&#39; made the change &#39;Set MJD-OBS to 54007.000000 from DATE-OBS&#39;. [astropy.wcs.wcs]
 </pre></div>
 </div>
-<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;matplotlib.collections.PathCollection at 0x7fe388864580&gt;
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;matplotlib.collections.PathCollection at 0x7f3c24ae89a0&gt;
 </pre></div>
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 <img alt="../../_images/cace13656c31942febb4172e15d1c1b59fbd5a36a975dfa024ca98c610680293.png" src="../../_images/cace13656c31942febb4172e15d1c1b59fbd5a36a975dfa024ca98c610680293.png" />
@@ -1428,7 +1428,7 @@ <h2>15. Try looping over all positions and plotting multiwavelength cutouts<a cl
 <div class="output stderr highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>WARNING: FITSFixedWarning: &#39;datfix&#39; made the change &#39;Set MJD-OBS to 51465.000000 from DATE-OBS&#39;. [astropy.wcs.wcs]
 </pre></div>
 </div>
-<img alt="../../_images/5cae1c9156881ebdafc4d45992e167ae8081d708ffb09c1d96f3da4b5badf634.png" src="../../_images/5cae1c9156881ebdafc4d45992e167ae8081d708ffb09c1d96f3da4b5badf634.png" />
+<img alt="../../_images/f985e497b906730d3361e774d3ed3e3946061539b90c046c70a8ccad428bbeb5.png" src="../../_images/f985e497b906730d3361e774d3ed3e3946061539b90c046c70a8ccad428bbeb5.png" />
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diff --git a/content/use_case_notebooks/hr_diagram_solution.html b/content/use_case_notebooks/hr_diagram_solution.html
index 560fa30..d7938f7 100644
--- a/content/use_case_notebooks/hr_diagram_solution.html
+++ b/content/use_case_notebooks/hr_diagram_solution.html
@@ -530,7 +530,7 @@ <h3>DATA DISCOVERY STEPS<a class="headerlink" href="#data-discovery-steps" title
 </pre></div>
 </div>
 <div class="output text_html"><div><i>Table length=145</i>
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+<table id="table139869975185968" class="table-striped table-bordered table-condensed">
 <thead><tr><th>index</th><th>short_name</th><th>title</th><th>description</th><th>interfaces</th></tr></thead>
 <thead><tr><th>int64</th><th>str16</th><th>str55</th><th>str4800</th><th>str7</th></tr></thead>
 <tr><td>0</td><td>I/163</td><td>US Naval Observatory Pleiades Catalog</td><td>This catalog is a special subset of the Eichhorn et al. (1970) Pleiades catalog (see &lt;I/90&gt;) updated to B1950.0 positions and with proper motions added. It was prepared for the purpose of predicting occultations of Pleiades stars by the Moon, but is useful for general applications because it contains many faint stars not present in the current series of large astrometric catalogs.</td><td>tap#aux</td></tr>
@@ -4055,7 +4055,7 @@ <h2>Step 2: Acquire the relevant data and make a plot<a class="headerlink" href=
 </pre></div>
 </div>
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 <thead><tr><th></th><th></th><th>mag</th><th>mag</th><th>deg</th><th>ms</th><th>deg</th><th>mas</th><th></th><th></th><th>mas / yr</th><th>mas / yr</th><th>mas / yr</th><th>mas / yr</th><th>arcsec</th><th>arcsec</th><th>deg</th><th>deg</th></tr></thead>
 <thead><tr><th>int32</th><th>int16</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>int16</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th></tr></thead>
@@ -4103,7 +4103,7 @@ <h3>Plotting<a class="headerlink" href="#plotting" title="Link to this heading">
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-<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>[&lt;matplotlib.lines.Line2D at 0x7fc909d17850&gt;]
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>[&lt;matplotlib.lines.Line2D at 0x7f35e2d33850&gt;]
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 <img alt="../../_images/b42395cf23e56c1d04597a950797687a5b0c98304e196110b7139ca953872f16.png" src="../../_images/b42395cf23e56c1d04597a950797687a5b0c98304e196110b7139ca953872f16.png" />
@@ -4162,7 +4162,7 @@ <h2>Step 3. Compare with other color-magnitude diagrams for Pleiades<a class="he
 Waveband Coverage:
 </pre></div>
 </div>
-<div class="output stderr highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>/tmp/ipykernel_2183/2733767379.py:11: DeprecationWarning: Conversion of an array with ndim &gt; 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)
+<div class="output stderr highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>/tmp/ipykernel_2098/2733767379.py:11: DeprecationWarning: Conversion of an array with ndim &gt; 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)
   ind = int(match[0])
 </pre></div>
 </div>
@@ -4199,7 +4199,7 @@ <h2>Step 3. Compare with other color-magnitude diagrams for Pleiades<a class="he
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 <div class="output text_html"><div><i>Table length=270</i>
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 <thead><tr><th>recno</th><th>HII</th><th>Vmag</th><th>B-V</th><th>xpos</th><th>ypos</th><th>Dist</th><th>Mult</th><th>Rem</th><th>Mass</th><th>MassA</th><th>MassB</th><th>MassC</th><th>MassD</th></tr></thead>
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@@ -4266,7 +4266,7 @@ <h2>BONUS: Step 4: The CMD as a distance indicator<a class="headerlink" href="#b
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diff --git a/content/use_case_notebooks/proposal_prep_solution.html b/content/use_case_notebooks/proposal_prep_solution.html
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@@ -559,7 +559,7 @@ <h2>Step 1: Find out what the previously quoted Chandra 2-10 keV flux of the cen
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 <thead><tr><th>ra</th><th>dec</th><th>exposure</th><th>flux</th><th>flux_lower</th><th>flux_upper</th></tr></thead>
 <thead><tr><th>deg</th><th>deg</th><th>s</th><th>erg/s/cm^2</th><th>erg/s/cm^2</th><th>erg/s/cm^2</th></tr></thead>
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@@ -582,7 +582,7 @@ <h3>Create ultraviolet and X-ray images<a class="headerlink" href="#create-ultra
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 <thead><tr><th>ivoid</th><th>short_name</th></tr></thead>
 <thead><tr><th>object</th><th>object</th></tr></thead>
 <tr><td>ivo://archive.stsci.edu/sia/galex</td><td>GALEX</td></tr>
@@ -601,7 +601,7 @@ <h3>Create ultraviolet and X-ray images<a class="headerlink" href="#create-ultra
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 <thead><tr><th>ivoid</th><th>short_name</th></tr></thead>
 <thead><tr><th>object</th><th>object</th></tr></thead>
 <tr><td>ivo://archive.stsci.edu/sia/galex</td><td>GALEX</td></tr>
@@ -629,7 +629,7 @@ <h3>Create ultraviolet and X-ray images<a class="headerlink" href="#create-ultra
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 <thead><tr><th>productType</th><th>imageFormat</th><th>contentLength</th><th>name</th><th>collection</th><th>insname</th><th>metaRelease</th><th>dataRelease</th><th>trgposRA</th><th>trgPosDec</th><th>s_region</th><th>position_naxes</th><th>position_naxis</th><th>position_scale</th><th>crpix</th><th>crval</th><th>cdmatrix</th><th>coordFrame</th><th>projection</th><th>position_ctype1</th><th>position_ctype2</th><th>position_cunit1</th><th>position_cunit2</th><th>timBoundsSTCS</th><th>time_bounds_cval1</th><th>time_bounds_cval2</th><th>time_bounds_center</th><th>timExposure</th><th>energy_bandpassName</th><th>energy_bounds_cval1</th><th>energy_bounds_cval2</th><th>energy_bounds_center</th><th>energy_units</th><th>publisherDID</th><th>accessURL</th><th>cloud_access</th></tr></thead>
 <thead><tr><th>object</th><th>object</th><th>int32</th><th>object</th><th>object</th><th>object</th><th>object</th><th>object</th><th>float64</th><th>float64</th><th>object</th><th>int32</th><th>object</th><th>object</th><th>object</th><th>object</th><th>object</th><th>object</th><th>str3</th><th>object</th><th>object</th><th>object</th><th>object</th><th>object</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>object</th><th>float64</th><th>float64</th><th>float64</th><th>object</th><th>object</th><th>object</th><th>object</th></tr></thead>
 <tr><td>science</td><td>image/fits</td><td>12544983</td><td>FORNAX_MOS06-xd-mcat.fits.gz</td><td>GALEX</td><td>GALEX</td><td>5/11/2010 12:15:31 AM</td><td>5/11/2010 12:15:31 AM</td><td>53.0653359237686</td><td>-36.3609134371405</td><td>CIRCLE ICRS  53.06533592 -36.36091344 0.625</td><td>2</td><td>[3840 3840]</td><td>[-0.00041666667 0.00041666667]</td><td>[1920.5 1920.5]</td><td>[53.0653 -36.3609]</td><td>[-0.000416667 -0.0 -0.0 0.000416667]</td><td>ICRS</td><td>TAN</td><td>RA---TAN</td><td>DEC--TAN</td><td>deg</td><td>deg</td><td>RANGE 54106.382801 54117.283171</td><td>54106.3828009259</td><td>54117.2831712963</td><td>54111.8329861111</td><td>3445.05</td><td>NUV</td><td>1.693e-07</td><td>3.007e-07</td><td>2.35e-07</td><td>meters</td><td>ivo://archive.stsci.edu/GALEX?2555302543848636416</td><td>https://mast.stsci.edu/api/v0.1/Download/file?uri=mast:GALEX/url/data/GR6/pipe/01-vsn/07090-FORNAX_MOS06/d/01-main/0001-img/07-try/FORNAX_MOS06-xd-mcat.fits.gz</td><td>{&quot;aws&quot;: {&quot;bucket_name&quot;:&quot;stpubdata&quot;,&quot;region&quot;:&quot;us-east-1&quot;,&quot;access&quot;:&quot;open&quot;,&quot;key&quot;:&quot;galex/GR6/pipe/01-vsn/07090-FORNAX_MOS06/d/01-main/0001-img/07-try/FORNAX_MOS06-xd-mcat.fits.gz&quot;}}</td></tr>
@@ -642,16 +642,16 @@ <h3>Create ultraviolet and X-ray images<a class="headerlink" href="#create-ultra
 <tr><td>SCIENCE</td><td>image/fits</td><td>17443052</td><td>FORNAX_MOS06-nd-int.fits.gz</td><td>GALEX</td><td>GALEX</td><td>5/11/2010 12:15:31 AM</td><td>5/11/2010 12:15:31 AM</td><td>53.0653359237686</td><td>-36.3609134371405</td><td>CIRCLE ICRS  53.06533592 -36.36091344 0.625</td><td>2</td><td>[3840 3840]</td><td>[-0.00041666667 0.00041666667]</td><td>[1920.5 1920.5]</td><td>[53.0653 -36.3609]</td><td>[-0.000416667 -0.0 -0.0 0.000416667]</td><td>ICRS</td><td>TAN</td><td>RA---TAN</td><td>DEC--TAN</td><td>deg</td><td>deg</td><td>RANGE 54106.382801 54117.283171</td><td>54106.3828009259</td><td>54117.2831712963</td><td>54111.8329861111</td><td>3445.05</td><td>NUV</td><td>1.693e-07</td><td>3.007e-07</td><td>2.35e-07</td><td>meters</td><td>ivo://archive.stsci.edu/GALEX?2555302543848636416</td><td>https://mast.stsci.edu/api/v0.1/Download/file?uri=mast:GALEX/url/data/GR6/pipe/01-vsn/07090-FORNAX_MOS06/d/01-main/0001-img/07-try/FORNAX_MOS06-nd-int.fits.gz</td><td>{&quot;aws&quot;: {&quot;bucket_name&quot;:&quot;stpubdata&quot;,&quot;region&quot;:&quot;us-east-1&quot;,&quot;access&quot;:&quot;open&quot;,&quot;key&quot;:&quot;galex/GR6/pipe/01-vsn/07090-FORNAX_MOS06/d/01-main/0001-img/07-try/FORNAX_MOS06-nd-int.fits.gz&quot;}}</td></tr>
 <tr><td>AUXILIARY</td><td>image/fits</td><td>5756688</td><td>FORNAX_MOS06-nd-cnt.fits.gz</td><td>GALEX</td><td>GALEX</td><td>5/11/2010 12:15:31 AM</td><td>5/11/2010 12:15:31 AM</td><td>53.0653359237686</td><td>-36.3609134371405</td><td>CIRCLE ICRS  53.06533592 -36.36091344 0.625</td><td>2</td><td>[3840 3840]</td><td>[-0.00041666667 0.00041666667]</td><td>[1920.5 1920.5]</td><td>[53.0653 -36.3609]</td><td>[-0.000416667 -0.0 -0.0 0.000416667]</td><td>ICRS</td><td>TAN</td><td>RA---TAN</td><td>DEC--TAN</td><td>deg</td><td>deg</td><td>RANGE 54106.382801 54117.283171</td><td>54106.3828009259</td><td>54117.2831712963</td><td>54111.8329861111</td><td>3445.05</td><td>NUV</td><td>1.693e-07</td><td>3.007e-07</td><td>2.35e-07</td><td>meters</td><td>ivo://archive.stsci.edu/GALEX?2555302543848636416</td><td>https://mast.stsci.edu/api/v0.1/Download/file?uri=mast:GALEX/url/data/GR6/pipe/01-vsn/07090-FORNAX_MOS06/d/01-main/0001-img/07-try/FORNAX_MOS06-nd-cnt.fits.gz</td><td>{&quot;aws&quot;: {&quot;bucket_name&quot;:&quot;stpubdata&quot;,&quot;region&quot;:&quot;us-east-1&quot;,&quot;access&quot;:&quot;open&quot;,&quot;key&quot;:&quot;galex/GR6/pipe/01-vsn/07090-FORNAX_MOS06/d/01-main/0001-img/07-try/FORNAX_MOS06-nd-cnt.fits.gz&quot;}}</td></tr>
 <tr><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td></tr>
-<tr><td>AUXILIARY</td><td>image/fits</td><td>3967636</td><td>AIS_423_0002_sg49-fd-intbgsub.fits.gz</td><td>GALEX</td><td>GALEX</td><td>6/16/2010 2:52:42 AM</td><td>6/16/2010 2:52:42 AM</td><td>53.9452301043047</td><td>-36.1117650864775</td><td>CIRCLE ICRS  53.94523010 -36.11176509 0.625</td><td>2</td><td>[3840 3840]</td><td>[-0.00041666667 0.00041666667]</td><td>[1920.5 1920.5]</td><td>[53.9452 -36.1118]</td><td>[-0.000416667 -0.0 -0.0 0.000416667]</td><td>ICRS</td><td>TAN</td><td>RA---TAN</td><td>DEC--TAN</td><td>deg</td><td>deg</td><td>RANGE 54460.401042 54460.402153</td><td>54460.4010416667</td><td>54460.4021527778</td><td>54460.4015972222</td><td>96.0</td><td>FUV</td><td>1.34e-07</td><td>1.806e-07</td><td>1.573e-07</td><td>meters</td><td>ivo://archive.stsci.edu/GALEX?6385798660088659968</td><td>https://mast.stsci.edu/api/v0.1/Download/file?uri=mast:GALEX/url/data/GR6/pipe/02-vsn/50423-AIS_423/d/00-visits/0002-img/07-try/AIS_423_0002_sg49-fd-intbgsub.fits.gz</td><td>{&quot;aws&quot;: {&quot;bucket_name&quot;:&quot;stpubdata&quot;,&quot;region&quot;:&quot;us-east-1&quot;,&quot;access&quot;:&quot;open&quot;,&quot;key&quot;:&quot;galex/GR6/pipe/02-vsn/50423-AIS_423/d/00-visits/0002-img/07-try/AIS_423_0002_sg49-fd-intbgsub.fits.gz&quot;}}</td></tr>
-<tr><td>AUXILIARY</td><td>image/fits</td><td>11794</td><td>AIS_423_0002_sg49-fd-flags.fits.gz</td><td>GALEX</td><td>GALEX</td><td>6/16/2010 2:52:42 AM</td><td>6/16/2010 2:52:42 AM</td><td>53.9452301043047</td><td>-36.1117650864775</td><td>CIRCLE ICRS  53.94523010 -36.11176509 0.625</td><td>2</td><td>[3840 3840]</td><td>[-0.00041666667 0.00041666667]</td><td>[1920.5 1920.5]</td><td>[53.9452 -36.1118]</td><td>[-0.000416667 -0.0 -0.0 0.000416667]</td><td>ICRS</td><td>TAN</td><td>RA---TAN</td><td>DEC--TAN</td><td>deg</td><td>deg</td><td>RANGE 54460.401042 54460.402153</td><td>54460.4010416667</td><td>54460.4021527778</td><td>54460.4015972222</td><td>96.0</td><td>FUV</td><td>1.34e-07</td><td>1.806e-07</td><td>1.573e-07</td><td>meters</td><td>ivo://archive.stsci.edu/GALEX?6385798660088659968</td><td>https://mast.stsci.edu/api/v0.1/Download/file?uri=mast:GALEX/url/data/GR6/pipe/02-vsn/50423-AIS_423/d/00-visits/0002-img/07-try/AIS_423_0002_sg49-fd-flags.fits.gz</td><td>{&quot;aws&quot;: {&quot;bucket_name&quot;:&quot;stpubdata&quot;,&quot;region&quot;:&quot;us-east-1&quot;,&quot;access&quot;:&quot;open&quot;,&quot;key&quot;:&quot;galex/GR6/pipe/02-vsn/50423-AIS_423/d/00-visits/0002-img/07-try/AIS_423_0002_sg49-fd-flags.fits.gz&quot;}}</td></tr>
-<tr><td>INFO</td><td>image/fits</td><td>13483</td><td>AIS_423_0002_sg49-rtastar.fits.gz</td><td>GALEX</td><td>GALEX</td><td>6/16/2010 2:52:42 AM</td><td>6/16/2010 2:52:42 AM</td><td>53.9452301043047</td><td>-36.1117650864775</td><td>CIRCLE ICRS  53.94523010 -36.11176509 0.625</td><td>2</td><td>[3840 3840]</td><td>[-0.00041666667 0.00041666667]</td><td>[1920.5 1920.5]</td><td>[53.9452 -36.1118]</td><td>[-0.000416667 -0.0 -0.0 0.000416667]</td><td>ICRS</td><td>TAN</td><td>RA---TAN</td><td>DEC--TAN</td><td>deg</td><td>deg</td><td>RANGE 54460.401042 54460.402153</td><td>54460.4010416667</td><td>54460.4021527778</td><td>54460.4015972222</td><td>96.0</td><td>FUV</td><td>1.34e-07</td><td>1.806e-07</td><td>1.573e-07</td><td>meters</td><td>ivo://archive.stsci.edu/GALEX?6385798660088659968</td><td>https://mast.stsci.edu/api/v0.1/Download/file?uri=mast:GALEX/url/data/GR6/pipe/02-vsn/50423-AIS_423/d/00-visits/0002-img/07-try/AIS_423_0002_sg49-rtastar.fits.gz</td><td>{&quot;aws&quot;: {&quot;bucket_name&quot;:&quot;stpubdata&quot;,&quot;region&quot;:&quot;us-east-1&quot;,&quot;access&quot;:&quot;open&quot;,&quot;key&quot;:&quot;galex/GR6/pipe/02-vsn/50423-AIS_423/d/00-visits/0002-img/07-try/AIS_423_0002_sg49-rtastar.fits.gz&quot;}}</td></tr>
-<tr><td>INFO</td><td>image/fits</td><td>8757</td><td>AIS_423_0002_sg49-aspraw.fits.gz</td><td>GALEX</td><td>GALEX</td><td>6/16/2010 2:52:42 AM</td><td>6/16/2010 2:52:42 AM</td><td>53.9452301043047</td><td>-36.1117650864775</td><td>CIRCLE ICRS  53.94523010 -36.11176509 0.625</td><td>2</td><td>[3840 3840]</td><td>[-0.00041666667 0.00041666667]</td><td>[1920.5 1920.5]</td><td>[53.9452 -36.1118]</td><td>[-0.000416667 -0.0 -0.0 0.000416667]</td><td>ICRS</td><td>TAN</td><td>RA---TAN</td><td>DEC--TAN</td><td>deg</td><td>deg</td><td>RANGE 54460.401042 54460.402153</td><td>54460.4010416667</td><td>54460.4021527778</td><td>54460.4015972222</td><td>96.0</td><td>FUV</td><td>1.34e-07</td><td>1.806e-07</td><td>1.573e-07</td><td>meters</td><td>ivo://archive.stsci.edu/GALEX?6385798660088659968</td><td>https://mast.stsci.edu/api/v0.1/Download/file?uri=mast:GALEX/url/data/GR6/pipe/02-vsn/50423-AIS_423/d/00-visits/0002-img/07-try/AIS_423_0002_sg49-aspraw.fits.gz</td><td>{&quot;aws&quot;: {&quot;bucket_name&quot;:&quot;stpubdata&quot;,&quot;region&quot;:&quot;us-east-1&quot;,&quot;access&quot;:&quot;open&quot;,&quot;key&quot;:&quot;galex/GR6/pipe/02-vsn/50423-AIS_423/d/00-visits/0002-img/07-try/AIS_423_0002_sg49-aspraw.fits.gz&quot;}}</td></tr>
-<tr><td>SCIENCE</td><td>image/fits</td><td>1970004</td><td>AIS_423_sg49-fd-int.fits.gz</td><td>GALEX</td><td>GALEX</td><td>8/18/2010 1:25:11 AM</td><td>8/18/2010 1:25:11 AM</td><td>53.9552232357184</td><td>-36.108680599578</td><td>CIRCLE ICRS  53.95522324 -36.10868060 0.625</td><td>2</td><td>[3840 3840]</td><td>[-0.00041666667 0.00041666667]</td><td>[1920.5 1920.5]</td><td>[53.9552 -36.1087]</td><td>[-0.000416667 -0.0 -0.0 0.000416667]</td><td>ICRS</td><td>TAN</td><td>RA---TAN</td><td>DEC--TAN</td><td>deg</td><td>deg</td><td>RANGE 54385.423877 54460.402153</td><td>54385.4238773148</td><td>54460.4021527778</td><td>54422.9130150463</td><td>200.0</td><td>FUV</td><td>1.34e-07</td><td>1.806e-07</td><td>1.573e-07</td><td>meters</td><td>ivo://archive.stsci.edu/GALEX?6385798797494059008</td><td>https://mast.stsci.edu/api/v0.1/Download/file?uri=mast:GALEX/url/data/GR6/pipe/02-vsn/50423-AIS_423/d/01-main/0001-img/07-try/AIS_423_sg49-fd-int.fits.gz</td><td>{&quot;aws&quot;: {&quot;bucket_name&quot;:&quot;stpubdata&quot;,&quot;region&quot;:&quot;us-east-1&quot;,&quot;access&quot;:&quot;open&quot;,&quot;key&quot;:&quot;galex/GR6/pipe/02-vsn/50423-AIS_423/d/01-main/0001-img/07-try/AIS_423_sg49-fd-int.fits.gz&quot;}}</td></tr>
-<tr><td>AUXILIARY</td><td>image/fits</td><td>10548360</td><td>AIS_423_sg49-fd-rrhr.fits.gz</td><td>GALEX</td><td>GALEX</td><td>8/18/2010 1:25:11 AM</td><td>8/18/2010 1:25:11 AM</td><td>53.9552232357184</td><td>-36.108680599578</td><td>CIRCLE ICRS  53.95522324 -36.10868060 0.625</td><td>2</td><td>[3840 3840]</td><td>[-0.00041666667 0.00041666667]</td><td>[1920.5 1920.5]</td><td>[53.9552 -36.1087]</td><td>[-0.000416667 -0.0 -0.0 0.000416667]</td><td>ICRS</td><td>TAN</td><td>RA---TAN</td><td>DEC--TAN</td><td>deg</td><td>deg</td><td>RANGE 54385.423877 54460.402153</td><td>54385.4238773148</td><td>54460.4021527778</td><td>54422.9130150463</td><td>200.0</td><td>FUV</td><td>1.34e-07</td><td>1.806e-07</td><td>1.573e-07</td><td>meters</td><td>ivo://archive.stsci.edu/GALEX?6385798797494059008</td><td>https://mast.stsci.edu/api/v0.1/Download/file?uri=mast:GALEX/url/data/GR6/pipe/02-vsn/50423-AIS_423/d/01-main/0001-img/07-try/AIS_423_sg49-fd-rrhr.fits.gz</td><td>{&quot;aws&quot;: {&quot;bucket_name&quot;:&quot;stpubdata&quot;,&quot;region&quot;:&quot;us-east-1&quot;,&quot;access&quot;:&quot;open&quot;,&quot;key&quot;:&quot;galex/GR6/pipe/02-vsn/50423-AIS_423/d/01-main/0001-img/07-try/AIS_423_sg49-fd-rrhr.fits.gz&quot;}}</td></tr>
-<tr><td>AUXILIARY</td><td>image/fits</td><td>2797390</td><td>AIS_423_sg49-fd-skybg.fits.gz</td><td>GALEX</td><td>GALEX</td><td>8/18/2010 1:25:11 AM</td><td>8/18/2010 1:25:11 AM</td><td>53.9552232357184</td><td>-36.108680599578</td><td>CIRCLE ICRS  53.95522324 -36.10868060 0.625</td><td>2</td><td>[3840 3840]</td><td>[-0.00041666667 0.00041666667]</td><td>[1920.5 1920.5]</td><td>[53.9552 -36.1087]</td><td>[-0.000416667 -0.0 -0.0 0.000416667]</td><td>ICRS</td><td>TAN</td><td>RA---TAN</td><td>DEC--TAN</td><td>deg</td><td>deg</td><td>RANGE 54385.423877 54460.402153</td><td>54385.4238773148</td><td>54460.4021527778</td><td>54422.9130150463</td><td>200.0</td><td>FUV</td><td>1.34e-07</td><td>1.806e-07</td><td>1.573e-07</td><td>meters</td><td>ivo://archive.stsci.edu/GALEX?6385798797494059008</td><td>https://mast.stsci.edu/api/v0.1/Download/file?uri=mast:GALEX/url/data/GR6/pipe/02-vsn/50423-AIS_423/d/01-main/0001-img/07-try/AIS_423_sg49-fd-skybg.fits.gz</td><td>{&quot;aws&quot;: {&quot;bucket_name&quot;:&quot;stpubdata&quot;,&quot;region&quot;:&quot;us-east-1&quot;,&quot;access&quot;:&quot;open&quot;,&quot;key&quot;:&quot;galex/GR6/pipe/02-vsn/50423-AIS_423/d/01-main/0001-img/07-try/AIS_423_sg49-fd-skybg.fits.gz&quot;}}</td></tr>
-<tr><td>AUXILIARY</td><td>image/fits</td><td>14254446</td><td>AIS_423_sg49-fd-wt.fits.gz</td><td>GALEX</td><td>GALEX</td><td>8/18/2010 1:25:11 AM</td><td>8/18/2010 1:25:11 AM</td><td>53.9552232357184</td><td>-36.108680599578</td><td>CIRCLE ICRS  53.95522324 -36.10868060 0.625</td><td>2</td><td>[3840 3840]</td><td>[-0.00041666667 0.00041666667]</td><td>[1920.5 1920.5]</td><td>[53.9552 -36.1087]</td><td>[-0.000416667 -0.0 -0.0 0.000416667]</td><td>ICRS</td><td>TAN</td><td>RA---TAN</td><td>DEC--TAN</td><td>deg</td><td>deg</td><td>RANGE 54385.423877 54460.402153</td><td>54385.4238773148</td><td>54460.4021527778</td><td>54422.9130150463</td><td>200.0</td><td>FUV</td><td>1.34e-07</td><td>1.806e-07</td><td>1.573e-07</td><td>meters</td><td>ivo://archive.stsci.edu/GALEX?6385798797494059008</td><td>https://mast.stsci.edu/api/v0.1/Download/file?uri=mast:GALEX/url/data/GR6/pipe/02-vsn/50423-AIS_423/d/01-main/0001-img/07-try/AIS_423_sg49-fd-wt.fits.gz</td><td>{&quot;aws&quot;: {&quot;bucket_name&quot;:&quot;stpubdata&quot;,&quot;region&quot;:&quot;us-east-1&quot;,&quot;access&quot;:&quot;open&quot;,&quot;key&quot;:&quot;galex/GR6/pipe/02-vsn/50423-AIS_423/d/01-main/0001-img/07-try/AIS_423_sg49-fd-wt.fits.gz&quot;}}</td></tr>
-<tr><td>THUMBNAIL</td><td>image/jpeg</td><td>9914</td><td>AIS_423_sg49-xd-int_2color_thumb.jpg</td><td>GALEX</td><td>GALEX</td><td>8/18/2010 1:25:11 AM</td><td>8/18/2010 1:25:11 AM</td><td>53.9552232357184</td><td>-36.108680599578</td><td>CIRCLE ICRS  53.95522324 -36.10868060 0.625</td><td>2</td><td>[3840 3840]</td><td>[-0.00041666667 0.00041666667]</td><td>[1920.5 1920.5]</td><td>[53.9552 -36.1087]</td><td>[-0.000416667 -0.0 -0.0 0.000416667]</td><td>ICRS</td><td>TAN</td><td>RA---TAN</td><td>DEC--TAN</td><td>deg</td><td>deg</td><td>RANGE 54385.423877 54460.402153</td><td>54385.4238773148</td><td>54460.4021527778</td><td>54422.9130150463</td><td>200.0</td><td>FUV</td><td>1.34e-07</td><td>1.806e-07</td><td>1.573e-07</td><td>meters</td><td>ivo://archive.stsci.edu/GALEX?6385798797494059008</td><td>https://mast.stsci.edu/api/v0.1/Download/file?uri=mast:GALEX/url/data/GR6/pipe/02-vsn/50423-AIS_423/d/01-main/0001-img/07-try/qa/AIS_423_sg49-xd-int_2color_thumb.jpg</td><td>{&quot;aws&quot;: {&quot;bucket_name&quot;:&quot;stpubdata&quot;,&quot;region&quot;:&quot;us-east-1&quot;,&quot;access&quot;:&quot;open&quot;,&quot;key&quot;:&quot;galex/GR6/pipe/02-vsn/50423-AIS_423/d/01-main/0001-img/07-try/qa/AIS_423_sg49-xd-int_2color_thumb.jpg&quot;}}</td></tr>
-<tr><td>PREVIEW</td><td>image/jpeg</td><td>576442</td><td>AIS_423_sg49-xd-int_2color_medium_annot.jpg</td><td>GALEX</td><td>GALEX</td><td>8/18/2010 1:25:11 AM</td><td>8/18/2010 1:25:11 AM</td><td>53.9552232357184</td><td>-36.108680599578</td><td>CIRCLE ICRS  53.95522324 -36.10868060 0.625</td><td>2</td><td>[3840 3840]</td><td>[-0.00041666667 0.00041666667]</td><td>[1920.5 1920.5]</td><td>[53.9552 -36.1087]</td><td>[-0.000416667 -0.0 -0.0 0.000416667]</td><td>ICRS</td><td>TAN</td><td>RA---TAN</td><td>DEC--TAN</td><td>deg</td><td>deg</td><td>RANGE 54385.423877 54460.402153</td><td>54385.4238773148</td><td>54460.4021527778</td><td>54422.9130150463</td><td>200.0</td><td>FUV</td><td>1.34e-07</td><td>1.806e-07</td><td>1.573e-07</td><td>meters</td><td>ivo://archive.stsci.edu/GALEX?6385798797494059008</td><td>https://mast.stsci.edu/api/v0.1/Download/file?uri=mast:GALEX/url/data/GR6/pipe/02-vsn/50423-AIS_423/d/01-main/0001-img/07-try/qa/AIS_423_sg49-xd-int_2color_medium_annot.jpg</td><td>{&quot;aws&quot;: {&quot;bucket_name&quot;:&quot;stpubdata&quot;,&quot;region&quot;:&quot;us-east-1&quot;,&quot;access&quot;:&quot;open&quot;,&quot;key&quot;:&quot;galex/GR6/pipe/02-vsn/50423-AIS_423/d/01-main/0001-img/07-try/qa/AIS_423_sg49-xd-int_2color_medium_annot.jpg&quot;}}</td></tr>
+<tr><td>science</td><td>image/fits</td><td>269663</td><td>AIS_423_0002_sg49_asprefine-nd-cat.fits.gz</td><td>GALEX</td><td>GALEX</td><td>6/16/2010 2:52:42 AM</td><td>6/16/2010 2:52:42 AM</td><td>53.9452301043047</td><td>-36.1117650864775</td><td>CIRCLE ICRS  53.94523010 -36.11176509 0.625</td><td>2</td><td>[3840 3840]</td><td>[-0.00041666667 0.00041666667]</td><td>[1920.5 1920.5]</td><td>[53.9452 -36.1118]</td><td>[-0.000416667 -0.0 -0.0 0.000416667]</td><td>ICRS</td><td>TAN</td><td>RA---TAN</td><td>DEC--TAN</td><td>deg</td><td>deg</td><td>RANGE 54460.401030 54460.402222</td><td>54460.4010300926</td><td>54460.4022222222</td><td>54460.4016261574</td><td>103.0</td><td>NUV</td><td>1.693e-07</td><td>3.007e-07</td><td>2.35e-07</td><td>meters</td><td>ivo://archive.stsci.edu/GALEX?6385798660088659968</td><td>https://mast.stsci.edu/api/v0.1/Download/file?uri=mast:GALEX/url/data/GR6/pipe/02-vsn/50423-AIS_423/d/00-visits/0002-img/07-try/qa/AIS_423_0002_sg49_asprefine-nd-cat.fits.gz</td><td>{&quot;aws&quot;: {&quot;bucket_name&quot;:&quot;stpubdata&quot;,&quot;region&quot;:&quot;us-east-1&quot;,&quot;access&quot;:&quot;open&quot;,&quot;key&quot;:&quot;galex/GR6/pipe/02-vsn/50423-AIS_423/d/00-visits/0002-img/07-try/qa/AIS_423_0002_sg49_asprefine-nd-cat.fits.gz&quot;}}</td></tr>
+<tr><td>AUXILIARY</td><td>image/fits</td><td>339243</td><td>AIS_423_0002_sg49-nd-fcat.fits.gz</td><td>GALEX</td><td>GALEX</td><td>6/16/2010 2:52:42 AM</td><td>6/16/2010 2:52:42 AM</td><td>53.9452301043047</td><td>-36.1117650864775</td><td>CIRCLE ICRS  53.94523010 -36.11176509 0.625</td><td>2</td><td>[3840 3840]</td><td>[-0.00041666667 0.00041666667]</td><td>[1920.5 1920.5]</td><td>[53.9452 -36.1118]</td><td>[-0.000416667 -0.0 -0.0 0.000416667]</td><td>ICRS</td><td>TAN</td><td>RA---TAN</td><td>DEC--TAN</td><td>deg</td><td>deg</td><td>RANGE 54460.401030 54460.402222</td><td>54460.4010300926</td><td>54460.4022222222</td><td>54460.4016261574</td><td>103.0</td><td>NUV</td><td>1.693e-07</td><td>3.007e-07</td><td>2.35e-07</td><td>meters</td><td>ivo://archive.stsci.edu/GALEX?6385798660088659968</td><td>https://mast.stsci.edu/api/v0.1/Download/file?uri=mast:GALEX/url/data/GR6/pipe/02-vsn/50423-AIS_423/d/00-visits/0002-img/07-try/AIS_423_0002_sg49-nd-fcat.fits.gz</td><td>{&quot;aws&quot;: {&quot;bucket_name&quot;:&quot;stpubdata&quot;,&quot;region&quot;:&quot;us-east-1&quot;,&quot;access&quot;:&quot;open&quot;,&quot;key&quot;:&quot;galex/GR6/pipe/02-vsn/50423-AIS_423/d/00-visits/0002-img/07-try/AIS_423_0002_sg49-nd-fcat.fits.gz&quot;}}</td></tr>
+<tr><td>PREVIEW</td><td>image/jpeg</td><td>3487526</td><td>AIS_423_0002_sg49-xd-int_2color.jpg</td><td>GALEX</td><td>GALEX</td><td>6/16/2010 2:52:42 AM</td><td>6/16/2010 2:52:42 AM</td><td>53.9452301043047</td><td>-36.1117650864775</td><td>CIRCLE ICRS  53.94523010 -36.11176509 0.625</td><td>2</td><td>[3840 3840]</td><td>[-0.00041666667 0.00041666667]</td><td>[1920.5 1920.5]</td><td>[53.9452 -36.1118]</td><td>[-0.000416667 -0.0 -0.0 0.000416667]</td><td>ICRS</td><td>TAN</td><td>RA---TAN</td><td>DEC--TAN</td><td>deg</td><td>deg</td><td>RANGE 54460.401030 54460.402222</td><td>54460.4010300926</td><td>54460.4022222222</td><td>54460.4016261574</td><td>103.0</td><td>NUV</td><td>1.693e-07</td><td>3.007e-07</td><td>2.35e-07</td><td>meters</td><td>ivo://archive.stsci.edu/GALEX?6385798660088659968</td><td>https://mast.stsci.edu/api/v0.1/Download/file?uri=mast:GALEX/url/data/GR6/pipe/02-vsn/50423-AIS_423/d/00-visits/0002-img/07-try/qa/AIS_423_0002_sg49-xd-int_2color.jpg</td><td>{&quot;aws&quot;: {&quot;bucket_name&quot;:&quot;stpubdata&quot;,&quot;region&quot;:&quot;us-east-1&quot;,&quot;access&quot;:&quot;open&quot;,&quot;key&quot;:&quot;galex/GR6/pipe/02-vsn/50423-AIS_423/d/00-visits/0002-img/07-try/qa/AIS_423_0002_sg49-xd-int_2color.jpg&quot;}}</td></tr>
+<tr><td>PREVIEW</td><td>image/jpeg</td><td>663752</td><td>AIS_423_0002_sg49-xd-int_2color_large.jpg</td><td>GALEX</td><td>GALEX</td><td>6/16/2010 2:52:42 AM</td><td>6/16/2010 2:52:42 AM</td><td>53.9452301043047</td><td>-36.1117650864775</td><td>CIRCLE ICRS  53.94523010 -36.11176509 0.625</td><td>2</td><td>[3840 3840]</td><td>[-0.00041666667 0.00041666667]</td><td>[1920.5 1920.5]</td><td>[53.9452 -36.1118]</td><td>[-0.000416667 -0.0 -0.0 0.000416667]</td><td>ICRS</td><td>TAN</td><td>RA---TAN</td><td>DEC--TAN</td><td>deg</td><td>deg</td><td>RANGE 54460.401030 54460.402222</td><td>54460.4010300926</td><td>54460.4022222222</td><td>54460.4016261574</td><td>103.0</td><td>NUV</td><td>1.693e-07</td><td>3.007e-07</td><td>2.35e-07</td><td>meters</td><td>ivo://archive.stsci.edu/GALEX?6385798660088659968</td><td>https://mast.stsci.edu/api/v0.1/Download/file?uri=mast:GALEX/url/data/GR6/pipe/02-vsn/50423-AIS_423/d/00-visits/0002-img/07-try/qa/AIS_423_0002_sg49-xd-int_2color_large.jpg</td><td>{&quot;aws&quot;: {&quot;bucket_name&quot;:&quot;stpubdata&quot;,&quot;region&quot;:&quot;us-east-1&quot;,&quot;access&quot;:&quot;open&quot;,&quot;key&quot;:&quot;galex/GR6/pipe/02-vsn/50423-AIS_423/d/00-visits/0002-img/07-try/qa/AIS_423_0002_sg49-xd-int_2color_large.jpg&quot;}}</td></tr>
+<tr><td>PREVIEW</td><td>image/jpeg</td><td>575892</td><td>AIS_423_0002_sg49-xd-int_2color_medium.jpg</td><td>GALEX</td><td>GALEX</td><td>6/16/2010 2:52:42 AM</td><td>6/16/2010 2:52:42 AM</td><td>53.9452301043047</td><td>-36.1117650864775</td><td>CIRCLE ICRS  53.94523010 -36.11176509 0.625</td><td>2</td><td>[3840 3840]</td><td>[-0.00041666667 0.00041666667]</td><td>[1920.5 1920.5]</td><td>[53.9452 -36.1118]</td><td>[-0.000416667 -0.0 -0.0 0.000416667]</td><td>ICRS</td><td>TAN</td><td>RA---TAN</td><td>DEC--TAN</td><td>deg</td><td>deg</td><td>RANGE 54460.401030 54460.402222</td><td>54460.4010300926</td><td>54460.4022222222</td><td>54460.4016261574</td><td>103.0</td><td>NUV</td><td>1.693e-07</td><td>3.007e-07</td><td>2.35e-07</td><td>meters</td><td>ivo://archive.stsci.edu/GALEX?6385798660088659968</td><td>https://mast.stsci.edu/api/v0.1/Download/file?uri=mast:GALEX/url/data/GR6/pipe/02-vsn/50423-AIS_423/d/00-visits/0002-img/07-try/qa/AIS_423_0002_sg49-xd-int_2color_medium.jpg</td><td>{&quot;aws&quot;: {&quot;bucket_name&quot;:&quot;stpubdata&quot;,&quot;region&quot;:&quot;us-east-1&quot;,&quot;access&quot;:&quot;open&quot;,&quot;key&quot;:&quot;galex/GR6/pipe/02-vsn/50423-AIS_423/d/00-visits/0002-img/07-try/qa/AIS_423_0002_sg49-xd-int_2color_medium.jpg&quot;}}</td></tr>
+<tr><td>PREVIEW</td><td>image/jpeg</td><td>134331</td><td>AIS_423_0002_sg49-xd-int_2color_small.jpg</td><td>GALEX</td><td>GALEX</td><td>6/16/2010 2:52:42 AM</td><td>6/16/2010 2:52:42 AM</td><td>53.9452301043047</td><td>-36.1117650864775</td><td>CIRCLE ICRS  53.94523010 -36.11176509 0.625</td><td>2</td><td>[3840 3840]</td><td>[-0.00041666667 0.00041666667]</td><td>[1920.5 1920.5]</td><td>[53.9452 -36.1118]</td><td>[-0.000416667 -0.0 -0.0 0.000416667]</td><td>ICRS</td><td>TAN</td><td>RA---TAN</td><td>DEC--TAN</td><td>deg</td><td>deg</td><td>RANGE 54460.401030 54460.402222</td><td>54460.4010300926</td><td>54460.4022222222</td><td>54460.4016261574</td><td>103.0</td><td>NUV</td><td>1.693e-07</td><td>3.007e-07</td><td>2.35e-07</td><td>meters</td><td>ivo://archive.stsci.edu/GALEX?6385798660088659968</td><td>https://mast.stsci.edu/api/v0.1/Download/file?uri=mast:GALEX/url/data/GR6/pipe/02-vsn/50423-AIS_423/d/00-visits/0002-img/07-try/qa/AIS_423_0002_sg49-xd-int_2color_small.jpg</td><td>{&quot;aws&quot;: {&quot;bucket_name&quot;:&quot;stpubdata&quot;,&quot;region&quot;:&quot;us-east-1&quot;,&quot;access&quot;:&quot;open&quot;,&quot;key&quot;:&quot;galex/GR6/pipe/02-vsn/50423-AIS_423/d/00-visits/0002-img/07-try/qa/AIS_423_0002_sg49-xd-int_2color_small.jpg&quot;}}</td></tr>
+<tr><td>INFO</td><td>image/fits</td><td>8737</td><td>AIS_423_0002_sg49-asp.fits.gz</td><td>GALEX</td><td>GALEX</td><td>6/16/2010 2:52:42 AM</td><td>6/16/2010 2:52:42 AM</td><td>53.9452301043047</td><td>-36.1117650864775</td><td>CIRCLE ICRS  53.94523010 -36.11176509 0.625</td><td>2</td><td>[3840 3840]</td><td>[-0.00041666667 0.00041666667]</td><td>[1920.5 1920.5]</td><td>[53.9452 -36.1118]</td><td>[-0.000416667 -0.0 -0.0 0.000416667]</td><td>ICRS</td><td>TAN</td><td>RA---TAN</td><td>DEC--TAN</td><td>deg</td><td>deg</td><td>RANGE 54460.401030 54460.402222</td><td>54460.4010300926</td><td>54460.4022222222</td><td>54460.4016261574</td><td>103.0</td><td>NUV</td><td>1.693e-07</td><td>3.007e-07</td><td>2.35e-07</td><td>meters</td><td>ivo://archive.stsci.edu/GALEX?6385798660088659968</td><td>https://mast.stsci.edu/api/v0.1/Download/file?uri=mast:GALEX/url/data/GR6/pipe/02-vsn/50423-AIS_423/d/00-visits/0002-img/07-try/AIS_423_0002_sg49-asp.fits.gz</td><td>{&quot;aws&quot;: {&quot;bucket_name&quot;:&quot;stpubdata&quot;,&quot;region&quot;:&quot;us-east-1&quot;,&quot;access&quot;:&quot;open&quot;,&quot;key&quot;:&quot;galex/GR6/pipe/02-vsn/50423-AIS_423/d/00-visits/0002-img/07-try/AIS_423_0002_sg49-asp.fits.gz&quot;}}</td></tr>
+<tr><td>AUXILIARY</td><td>image/fits</td><td>64456</td><td>AIS_423_0002_sg49-nd-cat_mch_flagstar.fits.gz</td><td>GALEX</td><td>GALEX</td><td>6/16/2010 2:52:42 AM</td><td>6/16/2010 2:52:42 AM</td><td>53.9452301043047</td><td>-36.1117650864775</td><td>CIRCLE ICRS  53.94523010 -36.11176509 0.625</td><td>2</td><td>[3840 3840]</td><td>[-0.00041666667 0.00041666667]</td><td>[1920.5 1920.5]</td><td>[53.9452 -36.1118]</td><td>[-0.000416667 -0.0 -0.0 0.000416667]</td><td>ICRS</td><td>TAN</td><td>RA---TAN</td><td>DEC--TAN</td><td>deg</td><td>deg</td><td>RANGE 54460.401030 54460.402222</td><td>54460.4010300926</td><td>54460.4022222222</td><td>54460.4016261574</td><td>103.0</td><td>NUV</td><td>1.693e-07</td><td>3.007e-07</td><td>2.35e-07</td><td>meters</td><td>ivo://archive.stsci.edu/GALEX?6385798660088659968</td><td>https://mast.stsci.edu/api/v0.1/Download/file?uri=mast:GALEX/url/data/GR6/pipe/02-vsn/50423-AIS_423/d/00-visits/0002-img/07-try/AIS_423_0002_sg49-nd-cat_mch_flagstar.fits.gz</td><td>{&quot;aws&quot;: {&quot;bucket_name&quot;:&quot;stpubdata&quot;,&quot;region&quot;:&quot;us-east-1&quot;,&quot;access&quot;:&quot;open&quot;,&quot;key&quot;:&quot;galex/GR6/pipe/02-vsn/50423-AIS_423/d/00-visits/0002-img/07-try/AIS_423_0002_sg49-nd-cat_mch_flagstar.fits.gz&quot;}}</td></tr>
+<tr><td>AUXILIARY</td><td>image/fits</td><td>25691</td><td>AIS_423_0002_sg49-nd-flag_tbl.fits.gz</td><td>GALEX</td><td>GALEX</td><td>6/16/2010 2:52:42 AM</td><td>6/16/2010 2:52:42 AM</td><td>53.9452301043047</td><td>-36.1117650864775</td><td>CIRCLE ICRS  53.94523010 -36.11176509 0.625</td><td>2</td><td>[3840 3840]</td><td>[-0.00041666667 0.00041666667]</td><td>[1920.5 1920.5]</td><td>[53.9452 -36.1118]</td><td>[-0.000416667 -0.0 -0.0 0.000416667]</td><td>ICRS</td><td>TAN</td><td>RA---TAN</td><td>DEC--TAN</td><td>deg</td><td>deg</td><td>RANGE 54460.401030 54460.402222</td><td>54460.4010300926</td><td>54460.4022222222</td><td>54460.4016261574</td><td>103.0</td><td>NUV</td><td>1.693e-07</td><td>3.007e-07</td><td>2.35e-07</td><td>meters</td><td>ivo://archive.stsci.edu/GALEX?6385798660088659968</td><td>https://mast.stsci.edu/api/v0.1/Download/file?uri=mast:GALEX/url/data/GR6/pipe/02-vsn/50423-AIS_423/d/00-visits/0002-img/07-try/AIS_423_0002_sg49-nd-flag_tbl.fits.gz</td><td>{&quot;aws&quot;: {&quot;bucket_name&quot;:&quot;stpubdata&quot;,&quot;region&quot;:&quot;us-east-1&quot;,&quot;access&quot;:&quot;open&quot;,&quot;key&quot;:&quot;galex/GR6/pipe/02-vsn/50423-AIS_423/d/00-visits/0002-img/07-try/AIS_423_0002_sg49-nd-flag_tbl.fits.gz&quot;}}</td></tr>
+<tr><td>AUXILIARY</td><td>image/fits</td><td>9113</td><td>FORNAX_MOS07_0002-fd-cat_mch_flagstar.fits.gz</td><td>GALEX</td><td>GALEX</td><td>4/28/2010 3:21:44 PM</td><td>4/28/2010 3:21:44 PM</td><td>54.0359149055626</td><td>-36.3362710522186</td><td>CIRCLE ICRS  54.03591491 -36.33627105 0.625</td><td>2</td><td>[3840 3840]</td><td>[-0.00041666667 0.00041666667]</td><td>[1920.5 1920.5]</td><td>[54.0359 -36.3363]</td><td>[-0.000416667 -0.0 -0.0 0.000416667]</td><td>ICRS</td><td>TAN</td><td>RA---TAN</td><td>DEC--TAN</td><td>deg</td><td>deg</td><td>RANGE 54110.286030 54110.296377</td><td>54110.2860300926</td><td>54110.2963773148</td><td>54110.2912037037</td><td>894.45</td><td>FUV</td><td>1.34e-07</td><td>1.806e-07</td><td>1.573e-07</td><td>meters</td><td>ivo://archive.stsci.edu/GALEX?2555337590815326208</td><td>https://mast.stsci.edu/api/v0.1/Download/file?uri=mast:GALEX/url/data/GR6/pipe/01-vsn/07091-FORNAX_MOS07/d/00-visits/0002-img/07-try/FORNAX_MOS07_0002-fd-cat_mch_flagstar.fits.gz</td><td>{&quot;aws&quot;: {&quot;bucket_name&quot;:&quot;stpubdata&quot;,&quot;region&quot;:&quot;us-east-1&quot;,&quot;access&quot;:&quot;open&quot;,&quot;key&quot;:&quot;galex/GR6/pipe/01-vsn/07091-FORNAX_MOS07/d/00-visits/0002-img/07-try/FORNAX_MOS07_0002-fd-cat_mch_flagstar.fits.gz&quot;}}</td></tr>
 </table></div></div></div>
 </div>
 <div class="cell docutils container">
@@ -665,11 +665,11 @@ <h3>Create ultraviolet and X-ray images<a class="headerlink" href="#create-ultra
 </div>
 <div class="cell_output docutils container">
 <div class="output text_html"><div><i>Table length=2</i>
-<table id="table140562901717232" class="table-striped table-bordered table-condensed">
+<table id="table140186403329392" class="table-striped table-bordered table-condensed">
 <thead><tr><th>Survey</th><th>Ra</th><th>Dec</th><th>Dim</th><th>Size</th><th>Scale</th><th>Format</th><th>PixFlags</th><th>URL</th><th>LogicalName</th></tr></thead>
 <thead><tr><th>object</th><th>float64</th><th>float64</th><th>int32</th><th>object</th><th>object</th><th>object</th><th>object</th><th>object</th><th>object</th></tr></thead>
-<tr><td>galexnear</td><td>53.4019083</td><td>-36.1406583</td><td>2</td><td>[300 300]</td><td>[-0.0003333333333333334 0.0003333333333333334]</td><td>image/fits</td><td>F</td><td>https://skyview.gsfc.nasa.gov/cgi-bin/images?position=53.4019083%2C-36.1406583&amp;survey=galexnear&amp;pixels=300%2C300&amp;sampler=LI&amp;size=0.10000000000000002%2C0.10000000000000002&amp;projection=Tan&amp;coordinates=J2000.0&amp;requestID=skv1734385870169&amp;return=FITS</td><td>1</td></tr>
-<tr><td>galexfar</td><td>53.4019083</td><td>-36.1406583</td><td>2</td><td>[300 300]</td><td>[-0.0003333333333333334 0.0003333333333333334]</td><td>image/fits</td><td>F</td><td>https://skyview.gsfc.nasa.gov/cgi-bin/images?position=53.4019083%2C-36.1406583&amp;survey=galexfar&amp;pixels=300%2C300&amp;sampler=LI&amp;size=0.10000000000000002%2C0.10000000000000002&amp;projection=Tan&amp;coordinates=J2000.0&amp;requestID=skv1734385870381&amp;return=FITS</td><td>2</td></tr>
+<tr><td>galexnear</td><td>53.40190833</td><td>-36.14065833</td><td>2</td><td>[300 300]</td><td>[-0.0003333333333333334 0.0003333333333333334]</td><td>image/fits</td><td>F</td><td>https://skyview.gsfc.nasa.gov/cgi-bin/images?position=53.40190833%2C-36.14065833&amp;survey=galexnear&amp;pixels=300%2C300&amp;sampler=LI&amp;size=0.10000000000000002%2C0.10000000000000002&amp;projection=Tan&amp;coordinates=J2000.0&amp;requestID=skv1734402283226&amp;return=FITS</td><td>1</td></tr>
+<tr><td>galexfar</td><td>53.40190833</td><td>-36.14065833</td><td>2</td><td>[300 300]</td><td>[-0.0003333333333333334 0.0003333333333333334]</td><td>image/fits</td><td>F</td><td>https://skyview.gsfc.nasa.gov/cgi-bin/images?position=53.40190833%2C-36.14065833&amp;survey=galexfar&amp;pixels=300%2C300&amp;sampler=LI&amp;size=0.10000000000000002%2C0.10000000000000002&amp;projection=Tan&amp;coordinates=J2000.0&amp;requestID=skv1734402283432&amp;return=FITS</td><td>2</td></tr>
 </table></div></div></div>
 </div>
 <div class="cell docutils container">
@@ -701,10 +701,10 @@ <h3>Create ultraviolet and X-ray images<a class="headerlink" href="#create-ultra
 </div>
 </div>
 <div class="cell_output docutils container">
-<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;matplotlib.image.AxesImage at 0x7fd759670340&gt;
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;matplotlib.image.AxesImage at 0x7f7fb027fc40&gt;
 </pre></div>
 </div>
-<img alt="../../_images/1979cc91924887400ac07d0500b0876bc3e1e33ac2eee690c5c4c8c19bd17795.png" src="../../_images/1979cc91924887400ac07d0500b0876bc3e1e33ac2eee690c5c4c8c19bd17795.png" />
+<img alt="../../_images/45cf46ef36053e22c2b84cbedc5d254d708d3b154667d3e26c3806145e7465da.png" src="../../_images/45cf46ef36053e22c2b84cbedc5d254d708d3b154667d3e26c3806145e7465da.png" />
 </div>
 </div>
 <p>Hint: Repeat steps for X-ray image. (Note: Ideally, we would find an image in the Chandra ‘cxc’ catalog)</p>
@@ -784,7 +784,7 @@ <h3>Find what Chandra spectral observations exist already for this source<a clas
 </div>
 <div class="cell_output docutils container">
 <div class="output text_html"><div><i>Table length=7</i>
-<table id="table140562767840544" class="table-striped table-bordered table-condensed">
+<table id="table140186336908224" class="table-striped table-bordered table-condensed">
 <thead><tr><th>short_name</th><th>ivoid</th><th>waveband</th></tr></thead>
 <thead><tr><th>object</th><th>object</th><th>object</th></tr></thead>
 <tr><td>Chandra</td><td>ivo://nasa.heasarc/chanmaster</td><td>x-ray</td></tr>
@@ -806,7 +806,7 @@ <h3>Find what Chandra spectral observations exist already for this source<a clas
 </div>
 <div class="cell_output docutils container">
 <div class="output text_html"><div><i>Table length=15</i>
-<table id="table140562889916128" class="table-striped table-bordered table-condensed">
+<table id="table140186391394816" class="table-striped table-bordered table-condensed">
 <thead><tr><th>obsid</th><th>status</th><th>name</th><th>ra</th><th>dec</th><th>time</th><th>detector</th><th>grating</th><th>exposure</th><th>type</th><th>pi</th><th>public_date</th><th>datalink</th><th>SSA_start_time</th><th>SSA_tmid</th><th>SSA_stop_time</th><th>SSA_duration</th><th>SSA_coord_obs</th><th>SSA_ra</th><th>SSA_dec</th><th>SSA_fov</th><th>SSA_title</th><th>SSA_reference</th><th>SSA_datalength</th><th>SSA_datamodel</th><th>SSA_instrument</th><th>SSA_publisher</th><th>SSA_format</th><th>SSA_wavelength_min</th><th>SSA_wavelength_max</th><th>SSA_bandwidth</th><th>SSA_bandpass</th><th>cloud_access</th></tr></thead>
 <thead><tr><th></th><th></th><th></th><th>deg</th><th>deg</th><th>d</th><th></th><th></th><th>s</th><th></th><th></th><th>d</th><th></th><th>d</th><th>d</th><th>d</th><th>s</th><th>deg</th><th>deg</th><th>deg</th><th>deg</th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th>m</th><th>m</th><th>m</th><th>m</th><th></th></tr></thead>
 <thead><tr><th>object</th><th>object</th><th>object</th><th>float64</th><th>float64</th><th>float64</th><th>object</th><th>object</th><th>float64</th><th>object</th><th>object</th><th>int32</th><th>object</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>object</th><th>object</th><th>object</th><th>object</th><th>object</th><th>object</th><th>object</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>object</th></tr></thead>
diff --git a/searchindex.js b/searchindex.js
index 83e4e79..98199e0 100644
--- a/searchindex.js
+++ b/searchindex.js
@@ -1 +1 @@
-Search.setIndex({"alltitles": {"0. (Only for Windows) Install WSL": [[0, "only-for-windows-install-wsl"]], "0. Setup": [[2, "setup"]], "1. Finding SIA resources from the Registry": [[4, "finding-sia-resources-from-the-registry"]], "1. Import the Python modules we\u2019ll be using": [[8, "import-the-python-modules-we-ll-be-using"], [9, "import-the-python-modules-we-ll-be-using"]], "1. Install Miniconda (if needed)": [[0, "install-miniconda-if-needed"]], "1. Overview": [[2, "overview"]], "1. Simple cone search": [[3, "simple-cone-search"]], "10. From the result in 8., select the first record for an image taken in WISE band W1 (3.6 micron)": [[8, "from-the-result-in-8-select-the-first-record-for-an-image-taken-in-wise-band-w1-3-6-micron"], [9, "from-the-result-in-8-select-the-first-record-for-an-image-taken-in-wise-band-w1-3-6-micron"]], "11. Visualize this AllWISE image": [[8, "visualize-this-allwise-image"], [9, "visualize-this-allwise-image"]], "12. Plot a cutout of the AllWISE image, centered on your position": [[8, "plot-a-cutout-of-the-allwise-image-centered-on-your-position"], [9, "plot-a-cutout-of-the-allwise-image-centered-on-your-position"]], "13. Try visualizing a cutout of a GALEX image that covers your position": [[8, "try-visualizing-a-cutout-of-a-galex-image-that-covers-your-position"], [9, "try-visualizing-a-cutout-of-a-galex-image-that-covers-your-position"]], "14. Try visualizing a cutout of an SDSS image that covers your position": [[8, "try-visualizing-a-cutout-of-an-sdss-image-that-covers-your-position"], [9, "try-visualizing-a-cutout-of-an-sdss-image-that-covers-your-position"]], "15. Try looping over all positions and plotting multiwavelength cutouts": [[8, "try-looping-over-all-positions-and-plotting-multiwavelength-cutouts"], [9, "try-looping-over-all-positions-and-plotting-multiwavelength-cutouts"]], "2. Search NED for objects in this paper": [[8, "search-ned-for-objects-in-this-paper"], [9, "search-ned-for-objects-in-this-paper"]], "2. Table Access Protocol queries": [[3, "table-access-protocol-queries"]], "2. Update conda version": [[0, "update-conda-version"]], "2. Using SIA to retrieve an image": [[4, "using-sia-to-retrieve-an-image"]], "2. VO Services": [[2, "vo-services"]], "2.0 Import Necessary Packages": [[2, "import-necessary-packages"]], "2.1 Look Up Services in VO Registry": [[2, "look-up-services-in-vo-registry"]], "2.1 TAP services": [[3, "tap-services"]], "2.1.1 Use different arguments/values to modify the simple example": [[2, "use-different-arguments-values-to-modify-the-simple-example"]], "2.1.2 Inspect the results": [[2, "inspect-the-results"]], "2.2 Cone search": [[2, "cone-search"]], "2.2 Expressing queries in ADQL": [[3, "expressing-queries-in-adql"]], "2.3 A use case": [[3, "a-use-case"]], "2.3 Image search": [[2, "image-search"]], "2.4 Spectral search": [[2, "spectral-search"]], "2.4 TAP examples for a given service": [[3, "tap-examples-for-a-given-service"]], "2.5 Table search": [[2, "table-search"]], "3. Astroquery": [[2, "astroquery"]], "3. Filter the NED results": [[8, "filter-the-ned-results"], [9, "filter-the-ned-results"]], "3. Install git (if needed)": [[0, "install-git-if-needed"]], "3. Using the TAP to cross-correlate and combine": [[3, "using-the-tap-to-cross-correlate-and-combine"]], "3. Viewing the resulting image": [[4, "viewing-the-resulting-image"]], "3.1 Cross-correlating to combine catalogs": [[3, "cross-correlating-to-combine-catalogs"]], "3.1 NED": [[2, "ned"]], "3.2 Cross-correlating with user-defined columns": [[3, "cross-correlating-with-user-defined-columns"]], "4. Clone This Repository": [[0, "clone-this-repository"]], "4. Search the NAVO Registry for image resources": [[8, "search-the-navo-registry-for-image-resources"], [9, "search-the-navo-registry-for-image-resources"]], "4. Synchronous versus asynchronous queries": [[3, "synchronous-versus-asynchronous-queries"]], "5. Create a conda environment for the workshop": [[0, "create-a-conda-environment-for-the-workshop"]], "5. 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Plot a cutout of the AllWISE image, centered on your position": [[8, "plot-a-cutout-of-the-allwise-image-centered-on-your-position"], [9, "plot-a-cutout-of-the-allwise-image-centered-on-your-position"]], "13. Try visualizing a cutout of a GALEX image that covers your position": [[8, "try-visualizing-a-cutout-of-a-galex-image-that-covers-your-position"], [9, "try-visualizing-a-cutout-of-a-galex-image-that-covers-your-position"]], "14. Try visualizing a cutout of an SDSS image that covers your position": [[8, "try-visualizing-a-cutout-of-an-sdss-image-that-covers-your-position"], [9, "try-visualizing-a-cutout-of-an-sdss-image-that-covers-your-position"]], "15. Try looping over all positions and plotting multiwavelength cutouts": [[8, "try-looping-over-all-positions-and-plotting-multiwavelength-cutouts"], [9, "try-looping-over-all-positions-and-plotting-multiwavelength-cutouts"]], "2. Search NED for objects in this paper": [[8, "search-ned-for-objects-in-this-paper"], [9, "search-ned-for-objects-in-this-paper"]], "2. Table Access Protocol queries": [[3, "table-access-protocol-queries"]], "2. Update conda version": [[0, "update-conda-version"]], "2. Using SIA to retrieve an image": [[4, "using-sia-to-retrieve-an-image"]], "2. VO Services": [[2, "vo-services"]], "2.0 Import Necessary Packages": [[2, "import-necessary-packages"]], "2.1 Look Up Services in VO Registry": [[2, "look-up-services-in-vo-registry"]], "2.1 TAP services": [[3, "tap-services"]], "2.1.1 Use different arguments/values to modify the simple example": [[2, "use-different-arguments-values-to-modify-the-simple-example"]], "2.1.2 Inspect the results": [[2, "inspect-the-results"]], "2.2 Cone search": [[2, "cone-search"]], "2.2 Expressing queries in ADQL": [[3, "expressing-queries-in-adql"]], "2.3 A use case": [[3, "a-use-case"]], "2.3 Image search": [[2, "image-search"]], "2.4 Spectral search": [[2, "spectral-search"]], "2.4 TAP examples for a given service": [[3, "tap-examples-for-a-given-service"]], "2.5 Table search": [[2, "table-search"]], "3. Astroquery": [[2, "astroquery"]], "3. Filter the NED results": [[8, "filter-the-ned-results"], [9, "filter-the-ned-results"]], "3. Install git (if needed)": [[0, "install-git-if-needed"]], "3. Using the TAP to cross-correlate and combine": [[3, "using-the-tap-to-cross-correlate-and-combine"]], "3. Viewing the resulting image": [[4, "viewing-the-resulting-image"]], "3.1 Cross-correlating to combine catalogs": [[3, "cross-correlating-to-combine-catalogs"]], "3.1 NED": [[2, "ned"]], "3.2 Cross-correlating with user-defined columns": [[3, "cross-correlating-with-user-defined-columns"]], "4. Clone This Repository": [[0, "clone-this-repository"]], "4. Search the NAVO Registry for image resources": [[8, "search-the-navo-registry-for-image-resources"], [9, "search-the-navo-registry-for-image-resources"]], "4. Synchronous versus asynchronous queries": [[3, "synchronous-versus-asynchronous-queries"]], "5. Create a conda environment for the workshop": [[0, "create-a-conda-environment-for-the-workshop"]], "5. Search the NAVO Registry for image resources that will allow you to search for AllWISE images": [[8, "search-the-navo-registry-for-image-resources-that-will-allow-you-to-search-for-allwise-images"], [9, "search-the-navo-registry-for-image-resources-that-will-allow-you-to-search-for-allwise-images"]], "6. Check Installation": [[0, "check-installation"]], "6. Choose the AllWISE image service that you are interested in": [[8, "choose-the-allwise-image-service-that-you-are-interested-in"], [9, "choose-the-allwise-image-service-that-you-are-interested-in"]], "7. Choose one of the galaxies in the NED list": [[8, "choose-one-of-the-galaxies-in-the-ned-list"], [9, "choose-one-of-the-galaxies-in-the-ned-list"]], "7. Starting Jupyterlab": [[0, "starting-jupyterlab"]], "8. Handling Notebooks in MyST-Markdown format": [[0, "handling-notebooks-in-myst-markdown-format"]], "8. 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