Skip to content

Commit

Permalink
Merge pull request #6033 from openjournals/joss.07305
Browse files Browse the repository at this point in the history
Merging automatically
  • Loading branch information
editorialbot authored Oct 22, 2024
2 parents 0cd49ba + 469c6a5 commit 2c5bbd0
Show file tree
Hide file tree
Showing 3 changed files with 845 additions and 0 deletions.
330 changes: 330 additions & 0 deletions joss.07305/10.21105.joss.07305.crossref.xml
Original file line number Diff line number Diff line change
@@ -0,0 +1,330 @@
<?xml version="1.0" encoding="UTF-8"?>
<doi_batch xmlns="http://www.crossref.org/schema/5.3.1"
xmlns:ai="http://www.crossref.org/AccessIndicators.xsd"
xmlns:rel="http://www.crossref.org/relations.xsd"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
version="5.3.1"
xsi:schemaLocation="http://www.crossref.org/schema/5.3.1 http://www.crossref.org/schemas/crossref5.3.1.xsd">
<head>
<doi_batch_id>20241022153929-98112d4d82276665812a943084d254df980beb4e</doi_batch_id>
<timestamp>20241022153929</timestamp>
<depositor>
<depositor_name>JOSS Admin</depositor_name>
<email_address>[email protected]</email_address>
</depositor>
<registrant>The Open Journal</registrant>
</head>
<body>
<journal>
<journal_metadata>
<full_title>Journal of Open Source Software</full_title>
<abbrev_title>JOSS</abbrev_title>
<issn media_type="electronic">2475-9066</issn>
<doi_data>
<doi>10.21105/joss</doi>
<resource>https://joss.theoj.org</resource>
</doi_data>
</journal_metadata>
<journal_issue>
<publication_date media_type="online">
<month>10</month>
<year>2024</year>
</publication_date>
<journal_volume>
<volume>9</volume>
</journal_volume>
<issue>102</issue>
</journal_issue>
<journal_article publication_type="full_text">
<titles>
<title>harmonize-wq: Standardize, clean and wrangle Water
Quality Portal data into more analytic-ready formats</title>
</titles>
<contributors>
<person_name sequence="first" contributor_role="author">
<given_name>Justin</given_name>
<surname>Bousquin</surname>
<ORCID>https://orcid.org/0000-0001-5797-4322</ORCID>
</person_name>
<person_name sequence="additional"
contributor_role="author">
<given_name>Cristina A.</given_name>
<surname>Mullin</surname>
<ORCID>https://orcid.org/0000-0002-0615-6087</ORCID>
</person_name>
</contributors>
<publication_date>
<month>10</month>
<day>22</day>
<year>2024</year>
</publication_date>
<pages>
<first_page>7305</first_page>
</pages>
<publisher_item>
<identifier id_type="doi">10.21105/joss.07305</identifier>
</publisher_item>
<ai:program name="AccessIndicators">
<ai:license_ref applies_to="vor">http://creativecommons.org/licenses/by/4.0/</ai:license_ref>
<ai:license_ref applies_to="am">http://creativecommons.org/licenses/by/4.0/</ai:license_ref>
<ai:license_ref applies_to="tdm">http://creativecommons.org/licenses/by/4.0/</ai:license_ref>
</ai:program>
<rel:program>
<rel:related_item>
<rel:description>Software archive</rel:description>
<rel:inter_work_relation relationship-type="references" identifier-type="doi">10.5281/zenodo.13356847</rel:inter_work_relation>
</rel:related_item>
<rel:related_item>
<rel:description>GitHub review issue</rel:description>
<rel:inter_work_relation relationship-type="hasReview" identifier-type="uri">https://github.com/openjournals/joss-reviews/issues/7305</rel:inter_work_relation>
</rel:related_item>
</rel:program>
<doi_data>
<doi>10.21105/joss.07305</doi>
<resource>https://joss.theoj.org/papers/10.21105/joss.07305</resource>
<collection property="text-mining">
<item>
<resource mime_type="application/pdf">https://joss.theoj.org/papers/10.21105/joss.07305.pdf</resource>
</item>
</collection>
</doi_data>
<citation_list>
<citation key="Beck_2021">
<article_title>tbeptools: An R package for synthesizing
estuarine data for environmental research</article_title>
<author>Beck</author>
<journal_title>Journal of Open Source
Software</journal_title>
<issue>65</issue>
<volume>6</volume>
<doi>10.21105/joss.03485</doi>
<cYear>2021</cYear>
<unstructured_citation>Beck, S., M. W., &amp; Best, B. D.
(2021). tbeptools: An R package for synthesizing estuarine data for
environmental research. Journal of Open Source Software, 6(65), 3485.
https://doi.org/10.21105/joss.03485</unstructured_citation>
</citation>
<citation key="Booth_2011">
<article_title>A Web‐Based Decision Support System for
Assessing Regional Water‐Quality Conditions and Management
Actions</article_title>
<author>Booth</author>
<journal_title>Journal of the American Water Resources
Association</journal_title>
<issue>5</issue>
<volume>47</volume>
<doi>10.1111/j.1752-1688.2011.00573.x</doi>
<cYear>2011</cYear>
<unstructured_citation>Booth, E., N. L., &amp; Murphy, L.
(2011). A Web‐Based Decision Support System for Assessing Regional
Water‐Quality Conditions and Management Actions. Journal of the American
Water Resources Association, 47(5), 1136–1150.
https://doi.org/10.1111/j.1752-1688.2011.00573.x</unstructured_citation>
</citation>
<citation key="Bousquin_2021">
<article_title>Discrete Global Grid Systems as scalable
geospatial frameworks for characterizing coastal
environments</article_title>
<author>Bousquin</author>
<journal_title>Environmental Modelling &amp;
Software</journal_title>
<volume>146</volume>
<doi>10.1016/j.envsoft.2021.105210</doi>
<cYear>2021</cYear>
<unstructured_citation>Bousquin, J. (2021). Discrete Global
Grid Systems as scalable geospatial frameworks for characterizing
coastal environments. Environmental Modelling &amp; Software, 146,
105210.
https://doi.org/10.1016/j.envsoft.2021.105210</unstructured_citation>
</citation>
<citation key="Chegini_2021">
<article_title>HyRiver: Hydroclimate Data
Retriever</article_title>
<author>Chegini</author>
<journal_title>Journal of Open Source
Software</journal_title>
<issue>66</issue>
<volume>6</volume>
<doi>10.21105/joss.03175</doi>
<cYear>2021</cYear>
<unstructured_citation>Chegini, T., Li, H.-Y., &amp; Leung,
L. R. (2021). HyRiver: Hydroclimate Data Retriever. Journal of Open
Source Software, 6(66), 1–3.
https://doi.org/10.21105/joss.03175</unstructured_citation>
</citation>
<citation key="De_Cicco_2022">
<volume_title>dataRetrieval: R packages for discovering and
retrieving water data available from U.S. federal hydrologic web
services</volume_title>
<author>De Cicco</author>
<doi>10.5066/P9X4L3GE</doi>
<cYear>2022</cYear>
<unstructured_citation>De Cicco, L. A., Lorenz, D., Hirsch,
R. M., Watkins, W., &amp; Johnson, M. (2022). dataRetrieval: R packages
for discovering and retrieving water data available from U.S. federal
hydrologic web services (Version 2.7.12) [Computer software]. U.S.
Geological Survey; U.S. Geological Survey.
https://doi.org/10.5066/P9X4L3GE</unstructured_citation>
</citation>
<citation key="Evans_2021">
<article_title>Linking mountaintop removal mining to water
quality for imperiled species using satellite data</article_title>
<author>Evans</author>
<journal_title>PloS one</journal_title>
<issue>11</issue>
<volume>16</volume>
<doi>10.1371/journal.pone.0239691</doi>
<cYear>2021</cYear>
<unstructured_citation>Evans, K., M. J., &amp; Malcom, J. W.
(2021). Linking mountaintop removal mining to water quality for
imperiled species using satellite data. PloS One, 16(11), e0239691.
https://doi.org/10.1371/journal.pone.0239691</unstructured_citation>
</citation>
<citation key="Grecco_2021">
<article_title>Pint: Operate and manipulate physical
quantities in Python</article_title>
<author>Grecco</author>
<cYear>2021</cYear>
<unstructured_citation>Grecco, H., &amp; Chéron, J. (2021).
Pint: Operate and manipulate physical quantities in Python (Version
1.9). https://github.com/hgrecco/pint</unstructured_citation>
</citation>
<citation key="Hodson_2023">
<article_title>dataretrieval (Python): a Python package for
discovering and retrieving water data available from U.S. federal
hydrologic web services</article_title>
<author>Hodson</author>
<doi>10.5066/P94I5TX3</doi>
<cYear>2023</cYear>
<unstructured_citation>Hodson, H., T. O., &amp; Horsburgh,
J. S. (2023). dataretrieval (Python): a Python package for discovering
and retrieving water data available from U.S. federal hydrologic web
services (Version 1.0.2). U.S. Geological Survey; U.S. Geological
Survey. https://doi.org/10.5066/P94I5TX3</unstructured_citation>
</citation>
<citation key="Jordahl_2021">
<article_title>geopandas/geopandas: v0.10.2</article_title>
<author>Kelsey Jordahl</author>
<doi>10.5281/zenodo.5573592</doi>
<cYear>2021</cYear>
<unstructured_citation>Kelsey Jordahl, M. F., Joris Van den
Bossche, &amp; Wasser, L. (2021). geopandas/geopandas: v0.10.2 (Version
v0.10.2). Zenodo.
https://doi.org/10.5281/zenodo.5573592</unstructured_citation>
</citation>
<citation key="Manning_2020">
<article_title>Transport of N and P in US streams and rivers
differs with land use and between dissolved and particulate
forms</article_title>
<author>Manning</author>
<journal_title>Ecological Applications</journal_title>
<volume>30</volume>
<doi>10.1002/eap.2130</doi>
<cYear>2020</cYear>
<unstructured_citation>Manning, R., D. W., &amp; Kominoski,
J. S. (2020). Transport of N and P in US streams and rivers differs with
land use and between dissolved and particulate forms. Ecological
Applications, 30, p.e02130.
https://doi.org/10.1002/eap.2130</unstructured_citation>
</citation>
<citation key="Read_2017">
<article_title>Water quality data for national‐scale aquatic
research: The Water Quality Portal.</article_title>
<author>Read</author>
<journal_title>Water Resources Research</journal_title>
<volume>53</volume>
<doi>10.1002/2016WR019993</doi>
<cYear>2017</cYear>
<unstructured_citation>Read, C., E. K., &amp; Winslow, L. A.
(2017). Water quality data for national‐scale aquatic research: The
Water Quality Portal. Water Resources Research, 53, 1735–1745.
https://doi.org/10.1002/2016WR019993</unstructured_citation>
</citation>
<citation key="Ross_2019">
<article_title>AquaSat: A data set to enable remote sensing
of water quality for inland waters</article_title>
<author>Ross</author>
<journal_title>Water Resources Research</journal_title>
<volume>55</volume>
<doi>10.1029/2019WR024883</doi>
<cYear>2019</cYear>
<unstructured_citation>Ross, T., M. R., &amp; Pavelsky, T.
M. (2019). AquaSat: A data set to enable remote sensing of water quality
for inland waters. Water Resources Research, 55, 10012–10025.
https://doi.org/10.1029/2019WR024883</unstructured_citation>
</citation>
<citation key="Shaughnessy_2019">
<article_title>Three Principles to Use in Streamlining Water
Quality Research through Data Uniformity</article_title>
<author>Shaughnessy</author>
<journal_title>Environmental Science &amp;
Technology</journal_title>
<volume>53</volume>
<doi>10.1021/acs.est.9b06406</doi>
<cYear>2019</cYear>
<unstructured_citation>Shaughnessy, W., A. R., &amp;
Brantley, S. L. (2019). Three Principles to Use in Streamlining Water
Quality Research through Data Uniformity. Environmental Science &amp;
Technology, 53, 13549–13550.
https://doi.org/10.1021/acs.est.9b06406</unstructured_citation>
</citation>
<citation key="Shen_2020">
<article_title>Estimating nitrogen and phosphorus
concentrations in streams and rivers, within a machine learning
framework</article_title>
<author>Shen</author>
<journal_title>Scientific Data</journal_title>
<volume>7</volume>
<doi>10.1038/s41597-020-0478-7</doi>
<cYear>2020</cYear>
<unstructured_citation>Shen, A., L. Q., &amp; Domisch, S.
(2020). Estimating nitrogen and phosphorus concentrations in streams and
rivers, within a machine learning framework. Scientific Data, 7, 161.
https://doi.org/10.1038/s41597-020-0478-7</unstructured_citation>
</citation>
<citation key="Sprague_2017">
<article_title>Challenges with secondary use of multi-source
water-quality data in the United States</article_title>
<author>Sprague</author>
<journal_title>Water Research</journal_title>
<volume>110</volume>
<doi>10.1016/j.watres.2016.12.024</doi>
<cYear>2017</cYear>
<unstructured_citation>Sprague, O., L. A., &amp; Argue, D.
M. (2017). Challenges with secondary use of multi-source water-quality
data in the United States. Water Research, 110, 252–261.
https://doi.org/10.1016/j.watres.2016.12.024</unstructured_citation>
</citation>
<citation key="Wickham_2014">
<article_title>Tidy data</article_title>
<author>Wickham</author>
<journal_title>The Journal of Statistical
Software</journal_title>
<volume>59</volume>
<doi>10.18637/jss.v059.i10</doi>
<cYear>2014</cYear>
<unstructured_citation>Wickham, H. (2014). Tidy data. The
Journal of Statistical Software, 59, 252–261.
https://doi.org/10.18637/jss.v059.i10</unstructured_citation>
</citation>
<citation key="USEPA_2018">
<volume_title>WQX Web API</volume_title>
<cYear>2018</cYear>
<unstructured_citation>WQX Web API. (2018). [Computer
software]. U.S. Environmental Protection Agency, Office of Water; U.S.
Environmental Protection Agency.
https://www.epa.gov/sites/default/files/2018-09/documents/wqx_web_application_programming_interface_api.pdf</unstructured_citation>
</citation>
<citation key="USEPA_2020">
<volume_title>WQX web user guide</volume_title>
<cYear>2020</cYear>
<unstructured_citation>WQX web user guide (Version 3.0).
(2020). [Computer software]. U.S. Environmental Protection Agency,
Office of Water; U.S. Environmental Protection Agency.
https://www.epa.gov/sites/default/files/2020-03/documents/wqx_web_user_guide_v3.0.pdf</unstructured_citation>
</citation>
</citation_list>
</journal_article>
</journal>
</body>
</doi_batch>
Binary file added joss.07305/10.21105.joss.07305.pdf
Binary file not shown.
Loading

0 comments on commit 2c5bbd0

Please sign in to comment.