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@misc{2015f,
title = {Maps},
year = {2015},
month = sep,
url = {https://www.jasondavies.com/maps/},
urldate = {2024-04-03},
file = {/home/camille/Zotero/storage/QAN87E3C/maps.html}
}
@misc{2019b,
title = {Viz {{Palette}}},
year = {2019},
month = sep,
url = {https://projects.susielu.com/viz-palette},
urldate = {2024-02-13},
keywords = {color},
file = {/home/camille/Zotero/storage/8RB7YP9P/viz-palette.html}
}
@misc{2019c,
title = {Choropleth {{Map}}},
year = {2019},
month = aug,
journal = {Data Visualization \& Information Aesthetics},
url = {https://dvia.samizdat.co/2019/coropleth-map/},
urldate = {2024-04-11},
abstract = {-------------------------------------------------------------------------------- Choropleth maps depict variations in spatial data by shading geographic areas according to a statistical measure. They make use of a gradient of hue, value, and texture, and often follow pre-defined geographic boundaries such as census tracts, cities, states, or countries. Values The choropleth map can represent various values including percentages, percentiles, rates, integers , and fractions by grouping these},
langid = {english},
file = {/home/camille/Zotero/storage/YJTZDYPC/coropleth-map.html}
}
@misc{2023f,
title = {``{{Dispersion}} \& {{Disparity}}'' {{Research Project Results}}},
year = {2023},
month = nov,
url = {https://3iap.com/dispersion-disparity-equity-centered-data-visualization-research-project-Wi-58RCVQNSz6ypjoIoqOQ/},
urldate = {2024-02-13},
abstract = {How masking uncertainty encourages stereotyping when visualizing social outcome disparities},
langid = {english},
keywords = {equity},
file = {/home/camille/Zotero/storage/WV6IQPWN/dispersion-disparity-equity-centered-data-visualization-research-project-Wi-58RCVQNSz6ypjoIoqOQ.html}
}
@misc{2023g,
title = {Reimagining a Classic {{Cheysson}} Thematic Map},
year = {2023},
month = aug,
journal = {Adventures In Mapping},
url = {https://adventuresinmapping.com/2023/08/28/reimagining-a-classic-cheysson-thematic-map/},
urldate = {2024-03-31},
abstract = {There is no one right way to make a map. Especially data-heavy thematic maps. In that spirit my friend and colleague~Ken Field~recently challenged~Sarah Bell~and I to each re-im{\dots}},
langid = {english},
file = {/home/camille/Zotero/storage/A5BBNQBL/reimagining-a-classic-cheysson-thematic-map.html}
}
@misc{2024a,
title = {Tidyverse/Ggplot2},
year = {2024},
month = jan,
url = {https://github.com/tidyverse/ggplot2},
urldate = {2024-01-22},
abstract = {An implementation of the Grammar of Graphics in R},
howpublished = {tidyverse},
keywords = {data-visualisation,r,visualisation}
}
@misc{2024c,
title = {Programming with {{R}}: {{Best Practices}} for {{Writing R Code}}},
year = {2024},
month = feb,
url = {https://swcarpentry.github.io/r-novice-inflammation/06-best-practices-R.html},
urldate = {2024-02-09},
file = {/home/camille/Zotero/storage/TCQEHCL5/06-best-practices-R.html}
}
@misc{A.I2024,
title = {Black Communities Are Using Mapping to Document and Restore a Sense of Place},
author = {Alderman, Derek H. and Inwood, Joshua F. J.},
year = {2024},
month = feb,
journal = {The Conversation},
url = {http://theconversation.com/black-communities-are-using-mapping-to-document-and-restore-a-sense-of-place-221299},
urldate = {2024-02-05},
abstract = {Black activists have long used maps to help illustrate their communities' history and to document historical injustices.},
langid = {american},
keywords = {case2,data for action}
}
@techreport{A.S.D+2023b,
title = {Greater {{New Haven Community Wellbeing Index}} 2023},
author = {Abraham, Mark and Seaberry, Camille and Davila, Kelly and Carr, Andrew},
year = {2023},
month = mar,
url = {https://ctdatahaven.org/reports/greater-new-haven-community-wellbeing-index},
urldate = {2023-09-03},
file = {/home/camille/Zotero/storage/SXUJ23YV/greater-new-haven-community-wellbeing-index.html}
}
@misc{Abbasi2022,
title = {Dr. {{Lawrence Brown}}: {{Baltimore}}'s {{Black Butterfly}} and {{White L}}},
shorttitle = {Dr. {{Lawrence Brown}}},
author = {Abbasi, Omar},
year = {2022},
month = dec,
url = {https://www.tableau.com/foundation/data-equity/economic-power/black-butterfly-baltimore},
urldate = {2024-04-12},
abstract = {Visualizing the geography of hypersegregation in Baltimore using five key metrics: child poverty, internet access, commute time, investment in small businesses, and unemployment.},
langid = {american},
file = {/home/camille/Zotero/storage/X5N9HN3D/black-butterfly-baltimore.html}
}
@misc{AEMP2023,
title = {Anti-{{Eviction Mapping Project}} - {{Narratives}} of {{Displacement}}},
author = {{Anti-Eviction Mapping Project}},
year = {2023},
month = dec,
url = {http://www.antievictionmappingproject.net/narratives.html},
urldate = {2024-04-13},
keywords = {case2},
file = {/home/camille/Zotero/storage/S3XG7BKW/narratives.html}
}
@misc{AEMP2024,
title = {Oakland {{Community Power Map}}},
author = {{Anti-Eviction Mapping Project}},
year = {2024},
month = mar,
url = {https://arcg.is/1LPDH5},
urldate = {2024-04-13},
langid = {american},
keywords = {case2},
file = {/home/camille/Zotero/storage/GPEF83YA/index.html}
}
@misc{Aisch2016,
title = {Why We Used Jittery Gauges in Our Live Election Forecast},
author = {Aisch, Gregor},
year = {2016},
month = nov,
journal = {vis4.net},
url = {https://vis4.net/blog/jittery-gauges-election-forecast},
urldate = {2024-02-13},
langid = {english},
keywords = {uncertainty},
file = {/home/camille/Zotero/storage/J37SGMUI/jittery-gauges-election-forecast.html}
}
@misc{Aisch2019,
title = {Chroma.Js Palette Helper},
author = {Aisch, Gregor},
year = {2019},
month = jun,
url = {https://gka.github.io/palettes},
urldate = {2024-02-13},
keywords = {color},
file = {/home/camille/Zotero/storage/5S2HXZ5Z/palettes.html}
}
@misc{Aviles2020,
title = {Generating {{Data Action}}: {{How}} an {{MIT Professor Hopes Data Can Empower Civic Change}}, {{Nightingale}}},
shorttitle = {Generating {{Data Action}}},
author = {Aviles, Mary},
year = {2020},
month = nov,
journal = {Nightingale},
url = {https://nightingaledvs.com/generating-data-action-how-an-mit-professor-hopes-to-pave-the-way-for-data-to-empower-civic-change/},
urldate = {2024-02-13},
abstract = {Technology, applied responsibly, has the potential to drive social change.},
langid = {american}
}
@misc{B.S2016,
title = {Data {{Ethics}} and {{Privacy}} with {{Eleanor Saitta}}},
author = {Bertini, Enrico and Stefaner, Moritz},
number = {74},
url = {https://datastori.es/74-data-ethics-and-privacy-with-eleanor-saitta/},
urldate = {2024-04-14},
abstract = {Eleanor is Etsy's new Security Architect and "a hacker, designer, artist, writer, and barbarian." We talk with Eleanor about how to deal with data ethics and privacy.},
langid = {american},
keywords = {case2},
file = {/home/camille/Zotero/storage/VUNS2LXI/74-data-ethics-and-privacy-with-eleanor-saitta.html}
}
@misc{B.S2018,
title = {Color with {{Karen Schloss}}},
author = {Bertini, Enrico and Stefaner, Moritz},
number = {119},
url = {https://datastori.es/119-color-with-karen-schloss/},
urldate = {2024-02-07},
abstract = {Karen Schloss, Assistant Professor at the University of Wisconsin Madison, joins us on the show to talk about color.},
langid = {american},
keywords = {case studies,color},
file = {/home/camille/Zotero/storage/NG33Z4V4/119-color-with-karen-schloss.html}
}
@misc{B.S2018a,
title = {Cognitive {{Bias}} and {{Visualization}} with {{Evanthia Dimara}}},
author = {Bertini, Enrico and Stefaner, Moritz},
number = {116},
url = {https://datastori.es/116-cognitive-bias-and-visualization-with-evanthia-dimara/},
urldate = {2024-02-14},
abstract = {We talk with Evanthia Dimara about cognitive bias and the role it plays in visualization.},
langid = {american},
keywords = {fallacies},
file = {/home/camille/Zotero/storage/K5LFJJEJ/116-cognitive-bias-and-visualization-with-evanthia-dimara.html}
}
@misc{B.S2019,
title = {Visualizing {{Uncertainty}} with {{Jessica Hullman}} and {{Matthew Kay}}},
author = {Bertini, Enrico and Stefaner, Moritz},
number = {134},
url = {https://datastori.es/134-visualizing-uncertainty-with-jessica-hullman-and-matthew-kay/},
urldate = {2024-01-30},
abstract = {Jessica Hullman and Matthew Kay join us to discuss the how and why of visualizing information uncertainty.},
langid = {american},
keywords = {uncertainty},
file = {/home/camille/Zotero/storage/PV5AKNAN/134-visualizing-uncertainty-with-jessica-hullman-and-matthew-kay.html}
}
@misc{BBC2010,
title = {Hans {{Rosling}}'s 200 {{Countries}}, 200 {{Years}}, 4 {{Minutes}} - {{The Joy}} of {{Stats}} - {{BBC Four}}},
author = {{BBC}},
year = {2010},
month = nov,
url = {https://www.youtube.com/watch?v=jbkSRLYSojo},
urldate = {2024-01-31},
abstract = {Subscribe and 🔔 to the BBC 👉 https://bit.ly/BBCYouTubeSub Watch the BBC first on iPlayer 👉 https://bbc.in/iPlayer-Home More about this programme: http://www.bbc.co.uk/programmes/b00wgq0l Hans Rosling's famous lectures combine enormous quantities of public data with a sport's commentator's style to reveal the story of the world's past, present and future development. Now he explores stats in a way he has never done before - using augmented reality animation. In this spectacular section of 'The Joy of Stats' he tells the story of the world in 200 countries over 200 years using 120,000 numbers - in just four minutes. Plotting life expectancy against income for every country since 1810, Hans shows how the world we live in is radically different from the world most of us imagine. \#bbc All our TV channels and S4C are available to watch live through BBC iPlayer, although some programmes may not be available to stream online due to rights. If you would like to read more on what types of programmes are available to watch live, check the 'Are all programmes that are broadcast available on BBC iPlayer?' FAQ 👉 https://bbc.in/2m8ks6v.},
keywords = {general}
}
@misc{Bertini2022,
type = {Substack Newsletter},
title = {Beyond {{Precision}}: {{Expressiveness}} in {{Visualization}}},
shorttitle = {Beyond {{Precision}}},
author = {Bertini, Enrico},
year = {2022},
month = feb,
journal = {FILWD},
url = {https://filwd.substack.com/p/beyond-precision-expressiveness-in},
urldate = {2024-02-13},
abstract = {Using precision as guidance for visualization design is powerful and yet limited in many different ways. Expressiveness may help.},
keywords = {case studies,case2},
file = {/home/camille/Zotero/storage/MI7Y4C5J/beyond-precision-expressiveness-in.html}
}
@misc{Bertini2024,
type = {Substack Newsletter},
title = {Shape the {{Data}}, {{Shape}} the {{Thinking}} \#4: {{Granularity}} and {{Visual Patterns}}},
shorttitle = {Shape the {{Data}}, {{Shape}} the {{Thinking}} \#4},
author = {Bertini, Enrico},
year = {2024},
month = feb,
journal = {FILWD},
url = {https://filwd.substack.com/p/shape-the-data-shape-the-thinking-66b},
urldate = {2024-02-13},
abstract = {Exploring the impact different levels of granularity have on visual representation and the different patterns that can emerge},
file = {/home/camille/Zotero/storage/PLLCFVPE/shape-the-data-shape-the-thinking-66b.html}
}
@misc{BocoupLLC2017,
title = {A {{Data Point Walks Into}} a {{Bar}}: {{Designing Data For Empathy}} - {{Lisa Charlotte Rost}}},
shorttitle = {A {{Data Point Walks Into}} a {{Bar}}},
author = {{BocoupLLC}},
year = {2017},
month = may,
url = {https://www.youtube.com/watch?v=8XgF-RmNwUc},
urldate = {2024-03-06},
keywords = {data ethics,syllabus}
}
@article{Brewer2006,
title = {Basic {{Mapping Principles}} for {{Visualizing Cancer Data Using Geographic Information Systems}} ({{GIS}})},
author = {Brewer, Cynthia A.},
year = {2006},
month = feb,
journal = {American Journal of Preventive Medicine},
volume = {30},
number = {2},
pages = {S25-S36},
publisher = {Elsevier},
issn = {0749-3797, 1873-2607},
doi = {10.1016/j.amepre.2005.09.007},
urldate = {2024-01-30},
langid = {english},
keywords = {color},
file = {/home/camille/Zotero/storage/GVSYBRZV/Brewer_2006_Basic Mapping Principles for Visualizing Cancer Data Using Geographic.pdf}
}
@book{Brown2021,
title = {The Black Butterfly: The Harmful Politics of Race and Space in {{America}}},
shorttitle = {The Black Butterfly},
author = {Brown, Lawrence T.},
year = {2021},
publisher = {Johns Hopkins University Press},
address = {Baltimore},
abstract = {"This book discusses the long history of the deleterious effects of racial segregation on health in the United States. Author Brown puts Baltimore under a microscope because Baltimore was the first city in America to enact segregationist legislation and because it remains hypersegregated to this day. "Black butterfly" describes the shape of a demographic map that plots Baltimore's population by race: a white central axis with black wings east and west"--},
isbn = {978-1-4214-3987-7 978-1-4214-4544-1},
lccn = {F189.B19 N395 2021},
keywords = {21st century,African American neighborhoods,African Americans,Case studies,Civil rights,Maryland Baltimore,Segregation,Segregation History,Social conditions,United States}
}
@misc{C.A.K+2022,
title = {Why {{Do Vaccinated People Represent Most COVID-19 Deaths Right Now}}?},
author = {Cox, Cynthia and Amin, Krutika and Kates, Jennifer and Published, Josh Michaud},
year = {2022},
month = nov,
journal = {KFF},
url = {https://www.kff.org/policy-watch/why-do-vaccinated-people-represent-most-covid-19-deaths-right-now/},
urldate = {2024-01-30},
abstract = {This post explores why the share of COVID-19 deaths among those who are vaccinated has risen, Factors include a rising share of the population that is vaccinated, waning immune protection and low uptake of boosters, and changes in immunity among the unvaccinated.},
langid = {american},
keywords = {fallacies},
file = {/home/camille/Zotero/storage/IZASQQUF/why-do-vaccinated-people-represent-most-covid-19-deaths-right-now.html}
}
@article{C.G2014,
title = {Error {{Bars Considered Harmful}}: {{Exploring Alternate Encodings}} for {{Mean}} and {{Error}}},
shorttitle = {Error {{Bars Considered Harmful}}},
author = {Correll, Michael and Gleicher, Michael},
year = {2014},
month = dec,
journal = {IEEE Transactions on Visualization and Computer Graphics},
volume = {20},
number = {12},
pages = {2142--2151},
issn = {1077-2626},
doi = {10.1109/TVCG.2014.2346298},
urldate = {2024-02-13},
abstract = {When making an inference or comparison with uncertain, noisy, or incomplete data, measurement error and confidence intervals can be as important for judgment as the actual mean values of different groups. These often misunderstood statistical quantities are frequently represented by bar charts with error bars. This paper investigates drawbacks with this standard encoding, and considers a set of alternatives designed to more effectively communicate the implications of mean and error data to a general audience, drawing from lessons learned from the use of visual statistics in the information visualization community. We present a series of crowd-sourced experiments that confirm that the encoding of mean and error significantly changes how viewers make decisions about uncertain data. Careful consideration of design tradeoffs in the visual presentation of data results in human reasoning that is more consistently aligned with statistical inferences. We suggest the use of gradient plots (which use transparency to encode uncertainty) and violin plots (which use width) as better alternatives for inferential tasks than bar charts with error bars.},
langid = {english},
keywords = {uncertainty},
file = {/home/camille/Zotero/storage/M4FSYMLX/Correll and Gleicher - 2014 - Error Bars Considered Harmful Exploring Alternate.pdf}
}
@inproceedings{C.M.H2018,
title = {Value-{{Suppressing Uncertainty Palettes}}},
booktitle = {Proceedings of the 2018 {{CHI Conference}} on {{Human Factors}} in {{Computing Systems}}},
author = {Correll, Michael and Moritz, Dominik and Heer, Jeffrey},
year = {2018},
month = apr,
pages = {1--11},
publisher = {ACM},
address = {Montreal QC Canada},
doi = {10.1145/3173574.3174216},
urldate = {2024-02-07},
abstract = {Understanding uncertainty is critical for many analytical tasks. One common approach is to encode data values and uncertainty values independently, using two visual variables. These resulting bivariate maps can be difficult to interpret, and interference between visual channels can reduce the discriminability of marks. To address this issue, we contribute ValueSuppressing Uncertainty Palettes (VSUPs). VSUPs allocate larger ranges of a visual channel to data when uncertainty is low, and smaller ranges when uncertainty is high. This non-uniform budgeting of the visual channels makes more economical use of the limited visual encoding space when uncertainty is low, and encourages more cautious decisionmaking when uncertainty is high. We demonstrate several examples of VSUPs, and present a crowdsourced evaluation showing that, compared to traditional bivariate maps, VSUPs encourage people to more heavily weight uncertainty information in decision-making tasks.},
isbn = {978-1-4503-5620-6},
langid = {english},
keywords = {uncertainty},
file = {/home/camille/Zotero/storage/RPGGDPYV/Correll et al. - 2018 - Value-Suppressing Uncertainty Palettes.pdf}
}
@book{C.S2022,
title = {Functional {{Aesthetics}} for {{Data Visualization}}},
author = {Cogley, Bridget and Setlur, Vidya},
year = {2022},
publisher = {{John Wiley and Sons}},
address = {Indianapolis},
isbn = {978-1-119-81008-7},
keywords = {general}
}
@book{Cairo2019,
title = {How Charts Lie: Getting Smarter about Visual Information},
shorttitle = {How Charts Lie},
author = {Cairo, Alberto},
year = {2019},
edition = {First edition},
publisher = {W. W. Norton \& Company},
address = {New York},
abstract = {"A leading data visualization expert explores the negative--and positive--influences that charts have on our perception of truth. We've all heard that a picture is worth a thousand words, but what if we don't understand what we're looking at? Social media has made charts, infographics, and diagrams ubiquitous--and easier to share than ever. While such visualizations can better inform us, they can also deceive by displaying incomplete or inaccurate data, suggesting misleading patterns-- or simply misinform us by being poorly designed, such as the confusing "eye of the storm" maps shown on TV every hurricane season. Many of us are ill equipped to interpret the visuals that politicians, journalists, advertisers, and even employers present each day, enabling bad actors to easily manipulate visuals to promote their own agendas. Public conversations are increasingly driven by numbers, and to make sense of them we must be able to decode and use visual information. By examining contemporary examples ranging from election-result infographics to global GDP maps and box-office record charts, How Charts Lie teaches us how to do just that"--},
isbn = {978-1-324-00156-0},
lccn = {T385 .C3388 2019},
keywords = {Charts diagrams etc,Computer graphics,Design,Information visualization,main texts,Social media,syllabus},
file = {/home/camille/Zotero/storage/HL5NG8ZX/Cairo_2019_How charts lie.pdf}
}
@misc{cbappendix,
title = {Appendix {{B}}: {{Measures}} of {{Residential Segregation}}},
author = {{US Census Bureau}},
year = {2021},
month = nov,
journal = {Guidance for Housing Patterns Data Users},
url = {https://www.census.gov/topics/housing/housing-patterns/guidance/appendix-b.html},
urldate = {2021-09-17},
keywords = {spatial analysis}
}
@misc{Cesal2020,
title = {Writing {{Alt Text}} for {{Data Visualization}}, {{Nightingale}}},
author = {Cesal, Amy},
year = {2020},
month = jul,
journal = {Nightingale},
url = {https://medium.com/nightingale/writing-alt-text-for-data-visualization-2a218ef43f81?source=friends_link&sk=32db60d651933b5ac2c5b6507f3763b5},
urldate = {2024-03-05},
abstract = {Alt text~(sometimes called alt tags or alternative text) are written descriptions added to images that convey the meaning of the visual.},
langid = {american},
keywords = {accessibility,syllabus},
file = {/home/camille/Zotero/storage/VB64M3Z6/writing-alt-text-for-data-visualization.html}
}
@book{Chang2018a,
title = {R Graphics Cookbook: Practical Recipes for Visualizing Data},
shorttitle = {R Graphics Cookbook},
author = {Chang, Winston},
year = {2018},
edition = {Second edition},
publisher = {O'Reilly},
address = {Beijing ; Boston},
url = {https://r-graphics.org/},
isbn = {978-1-4919-7860-3},
lccn = {QA276.45.R3 C44 2018},
keywords = {Computer graphics,Computer Graphics,Data processing,general,Informatique Manuels d'enseignement superieur,Manuels d'enseignement superieur,Mathematical Computing,Mathematical statistics,R (Computer program language),R (logiciel),Software,statistics & numerical data,Statistics as Topic,Statistique},
annotation = {OCLC: on1076544092}
}
@misc{Cheysson,
title = {Reimagining a {{Classic Cheysson Map}}},
author = {{John Nelson Maps}},
year = {2023},
month = aug,
url = {https://www.youtube.com/watch?v=ibHkrK42uok},
urldate = {2024-03-31},
abstract = {My friend and colleague Ken Field challenged Sarah Bell and I, for a recent presentation, to each reimagine a few classic maps. This multivariate map by {\'E}mile Cheysson was one of those we were tasked with revamping. Now, I'd never say that I could improve on this map, but since there is no one right way to make a map it was an opportunity to bring a different perspective. And the beauty of a subjective/objective field like thematic mapping is that everyone has something to share. In this video I'll make two different maps. The first is done in an aesthetic somewhat like Cheysson's but with a twist on the thematic symbol. The second map is a big departure but uses a "small multiple" layout to visually communicate lots of data. I'll blab on and on about why I'm doing these things, but the gist of it is two things: 1. When making a thematic map, always ask your self, "why not just..." as a prompt to continually rethink and simplify. 2. The biggest mistake we make in thematic mapping is asking too much of one single map. Enjoy! Here is a link to Cheysson's classic map: https://www.davidrumsey.com/luna/serv... Here is Sarah Bell's lovely take on it: ~~~{$\bullet~$}Watch~How~Mapmaker~Animates~Antique~F...~~ If you would like a boatload of glorious resources for making maps in the visual style of Cheysson, check out this blog post from Ken Field: https://www.esri.com/arcgis-blog/prod... What's a multivariate map? ~~~{$\bullet~$}Million~and~One~Ways~to~Make~a~Multiv...~~ Check out some other social channels where I share how-to's and updates on random map adventures: http://adventuresinmapping.com https://www.esri.com/arcgis-blog/auth... ~~/~john\_m\_nelson~~ ~~/~johnmnelson~~ ~~/~johnmnelson~~ Music: Divine Life Society, by Jesse Gallagher}
}
@article{colorgorical,
title = {Colorgorical: Creating Discriminable and Preferable Color Palettes for Information Visualization},
author = {Gramazio, Connor C. and Laidlaw, David H. and Schloss, Karen B.},
year = {2017},
journal = {IEEE Transactions on Visualization and Computer Graphics},
doi = {10.1109/TVCG.2016.2598918},
keywords = {color}
}
@book{D.B.R2018,
title = {W.{{E}}.{{B Du Bois}}'s Data Portraits: Visualizing {{Black America}}},
shorttitle = {W.{{E}}.{{B Du Bois}}'s Data Portraits},
author = {Du Bois, W. E. B. and {Battle-Baptiste}, Whitney and Rusert, Britt},
year = {2018},
edition = {First edition},
publisher = {The W.E.B. Du Bois Center At the University of Massachusetts Amherst ; Princeton Architectural Press},
address = {[Amherst, Mass.] : Hudson, NY},
abstract = {"The colorful charts, graphs, and maps presented at the 1900 Paris Exposition by famed sociologist and black rights activist W.E.B. Du Bois offered a look behind the veil into the lives of black Americans to convey a literal and figurative representation of what Du Bois famously termed "the color line," and became the talk of the Expo. From advances in education to the lingering effects of slavery, these prophetic infographics--beautiful in design and powerful in content--make visible a wide spectrum of black experience. W.E.B. Du Bois's Data Portraits collects the complete set of graphs in full color for the first time, making their insights and innovations available to a contemporary imagination. These data portraits shaped how Du Bois thought about sociology, informing his ideas with which he set the world ablaze three years later with The Souls of Black Folk"--},
isbn = {978-1-61689-706-2},
lccn = {E185.86 .D846 2018},
keywords = {African American sociologists,African Americans,Charts diagrams etc,Du Bois W. E. B,Exposition universelle,general,Graphs,History,Information visualization,Social conditions,Sociology,United States,William Edward Burghardt}
}
@incollection{D.I2024,
title = {Chapter 14: {{Detect Lies}} and {{Reduce Bias}}},
booktitle = {Hands-{{On Data Visualization}}},
author = {Dougherty, Jack and Ilyankou, Ilya},
year = {2024},
url = {https://handsondataviz.org/detect.html},
urldate = {2024-01-20},
abstract = {Tell your story and show it with data, using free and easy-to-learn tools on the web. This introductory book teaches you how to design interactive charts and customized maps for your website, beginning with easy drag-and-drop tools, such as Google Sheets, Datawrapper, and Tableau Public. You will also gradually learn how to edit open-source code templates built with Chart.js, Highcharts, and Leaflet on GitHub. Follow along with the step-by-step tutorials, real-world examples, and online resources. This book is ideal for students, non-profit organizations, small business owners, local governments, journalists, academics, or anyone who wants to tell their story and show the data. No coding experience is required.},
langid = {english},
keywords = {syllabus},
file = {/home/camille/Zotero/storage/RKBDCTTY/detect.html}
}
@book{D.K2020,
title = {Data Feminism},
author = {D'Ignazio, Catherine and Klein, Lauren F.},
year = {2020},
series = {{$<$}{{Strong}}{$>$} Ideas Series},
publisher = {The MIT Press},
address = {Cambridge, Massachusetts London, England},
url = {https://data-feminism.mitpress.mit.edu/},
abstract = {"We have seen through many examples that data science and artificial intelligence can reinforce structural inequalities like sexism and racism. Data is power, and that power is distributed unequally. This book offers a vision for a feminist data science that can challenge power and work towards justice. This book takes a stand against a world that benefits some (including the authors, two white women) at the expense of others. It seeks to provide concrete steps for data scientists seeking to learn how feminism can help them work towards justice, and for feminists seeking to learn how their own work can carry over to the growing field of data science. It is addressed to professionals in all fields where data-driven decisions are being made, as well as to communities that want to better understand the data that surrounds them. It is written for everyone who seeks to better understand the charts and statistics that they encounter in their day-to-day lives, and for everyone who seeks to better communicate the significance of such charts and statistics to others. This is an example-driven book written with a broad audience of scholars, students, and practitioners in mind. It offers a way of thinking about data, both their uses and their limits, that is informed by direct experience, by a commitment to action, and by the ideas associated with intersectional feminist thought"--},
isbn = {978-0-262-04400-4},
langid = {english},
keywords = {general},
file = {/home/camille/Zotero/storage/8XYWQSDE/D'Ignazio_Klein_2020_Data feminism.pdf}
}
@incollection{D.K2020a,
title = {Chapter 2. {{Collect}}, {{Analyze}}, {{Imagine}}, {{Teach}}},
booktitle = {Data {{Feminism}}},
author = {D'Ignazio, Catherine and Klein, Lauren},
year = {2020},
month = mar,
url = {https://data-feminism.mitpress.mit.edu/pub/ei7cogfn/release/4},
urldate = {2024-04-14},
abstract = {Principle \#2 of Data Feminism is to Challenge Power. Data feminism commits to challenging unequal power structures and working toward justice.},
langid = {english},
keywords = {case2,No DOI found},
file = {/home/camille/Zotero/storage/U5HJKJ3S/D'Ignazio_Klein_2020_2.pdf}
}
@misc{Datawrapper2021,
title = {What to Consider When Choosing Colors for Data Visualization},
author = {{Datawrapper}},
year = {2021},
month = mar,
url = {https://academy.datawrapper.de/article/140-what-to-consider-when-choosing-colors-for-data-visualization},
urldate = {2024-02-13},
abstract = {xData Visualisation can be defined as representing numbers with shapes -- and no matter what these shapes look like (areas, lines, dots), they need to have a col},
keywords = {color},
file = {/home/camille/Zotero/storage/GG87H7D9/140-what-to-consider-when-choosing-colors-for-data-visualization.html}
}
@misc{dcws,
title = {{{DataHaven Community Wellbeing Survey}}},
author = {{DataHaven}},
url = {https://ctdatahaven.org/reports/datahaven-community-wellbeing-survey},
keywords = {dh_common},
file = {/home/camille/Zotero/storage/YE7PLXI4/datahaven-community-wellbeing-survey.html}
}
@misc{DIgnazio2015,
title = {What Would Feminist Data Visualization Look Like?},
shorttitle = {What Would Feminist Data Visualization Look Like?},
author = {D'Ignazio, Catherine},
year = {2015},
month = dec,
url = {https://civic.mit.edu/feminist-data-visualization.html},
urldate = {2024-01-21},
langid = {american},
keywords = {general,syllabus},
file = {/home/camille/Zotero/storage/5HJDVHPY/feminist-data-visualization.html}
}
@misc{Dunne2021,
title = {Endless {{River}}: {{An Overview}} of {{Dataviz}} for {{Categorical Data}}, {{Nightingale}}},
shorttitle = {Endless {{River}}},
author = {Dunne, Jonathan},
year = {2021},
month = aug,
journal = {Nightingale},
url = {https://nightingaledvs.com/endless-river-an-overview-of-dataviz-for-categorical-data/},
urldate = {2024-02-13},
abstract = {Let us explore some flow and network chart types that are ready-made for visual storytelling using categorical data ~ As a data scientist, I am...},
langid = {american}
}
@misc{Elavsky2022,
title = {The {{Chartability Workbook}}},
author = {Elavsky, Frank},
year = {2022},
month = jun,
journal = {Chartability},
url = {https://chartability.github.io/POUR-CAF/},
urldate = {2024-02-29},
abstract = {A tool for auditing the accessibility of data experiences.},
langid = {american},
keywords = {accessibility},
file = {/home/camille/Zotero/storage/H329I9TV/POUR-CAF.html}
}
@misc{Elghany2023,
title = {How {{Ethical Data Visualization Tells}} the {{Human Story}}},
author = {Elghany, Soha},
year = {2023},
month = aug,
journal = {Nightingale},
url = {https://nightingaledvs.com/ethical-data-visualization-tells-the-human-story/},
urldate = {2024-01-30},
abstract = {If you fail to show the human behind the data, you risk telling an incomplete and misleading tale, devoid of crucial information.},
langid = {american},
keywords = {data ethics}
}
@misc{Ericson2011,
title = {When {{Maps Shouldn}}'t {{Be Maps}}},
author = {Ericson, Matthew},
year = {2011},
month = oct,
journal = {ericson.net},
url = {https://www.ericson.net/content/2011/10/when-maps-shouldnt-be-maps/},
urldate = {2024-03-27},
abstract = {Often, when you get data that is organized by geography --- say, for example, food stamp rates in every county, high school graduation rates in every state, election results in every House district, {\dots}},
langid = {american},
keywords = {spatial analysis,syllabus},
file = {/home/camille/Zotero/storage/5DPAPSQI/when-maps-shouldnt-be-maps.html}
}
@misc{Etter2023,
title = {Data {{Visualization}}: {{A Subjective Lens}} on {{Reality}}},
shorttitle = {Data {{Visualization}}},
author = {Etter, Elena},
year = {2023},
month = jun,
journal = {Nightingale},
url = {https://nightingaledvs.com/data-visualization-a-subjective-lens-on-reality/},
urldate = {2024-01-30},
abstract = {An analysis of three elements that influence data visualization{$\mkern1mu$} and that render the underlying data to be more subjective than objective.},
langid = {american},
keywords = {case studies,framing}
}
@article{F.R.S+2022,
ids = {f.r.s+2022a},
title = {New {{Evidence}} on {{Redlining}} by {{Federal Housing Programs}} in the 1930s},
author = {Fishback, Price and Rose, Jonathan and Snowden, Kenneth A. and Storrs, Thomas},
year = {2022},
month = may,
journal = {Journal of Urban Economics},
pages = {103462},
issn = {0094-1190},
doi = {10.1016/j.jue.2022.103462},
urldate = {2022-11-15},
abstract = {We show that the Federal Housing Administration (FHA), from its inception in the 1930s, did not insure mortgages in low income urban neighborhoods where the vast majority of urban Black Americans lived. This pattern emerged before the Home Owners' Loan Corporation (HOLC) drafted its infamous maps. In contrast, the HOLC itself broadly loaned to core urban neighborhoods and to Black homeowners. We conclude that the mechanisms through which the HOLC's maps could have affected the geographic scope of mortgage lending were likely quite limited. The FHA instead evaluated neighborhoods using block-level information developed in the 1930s and other data, rather than on the basis of the HOLC maps.},
langid = {english},
keywords = {Federal Housing Administration,Home Owners' Loan Corporation,Housing finance history,Redlining},
file = {/home/camille/Zotero/storage/6IVZHNZR/Fishback et al. - 2022 - New Evidence on Redlining by Federal Housing Progr.pdf;/home/camille/Zotero/storage/M7KXC2DR/Fishback et al. - 2022 - New Evidence on Redlining by Federal Housing Progr.pdf;/home/camille/Zotero/storage/EX776WSV/S0094119022000390.html}
}
@book{F.R2009,
title = {The {{Sage}} Handbook of Spatial Analysis},
author = {Fotheringham, A. Stewart and Rogerson, Peter},
year = {2009},
series = {The {{Sage}} Handbook Of},
publisher = {Sage},
address = {London},
isbn = {978-1-4129-1082-8},
langid = {english},
file = {/home/camille/Zotero/storage/F46H2CXB/Fotheringham_Rogerson_2009_The Sage handbook of spatial analysis.pdf}
}
@article{Fabricant2018,
title = {Black Neighborhoods Matter: An Interview with {{Lawrence Brown}} on Community and Healing},
shorttitle = {Black Neighborhoods Matter},
author = {Fabricant, Nicole},
year = {2018},
journal = {New Politics},
volume = {17},
number = {1},
pages = {58--64},
issn = {00286494},
url = {https://newpol.org/issue_post/black-neighborhoods-matter/},
urldate = {2024-04-12},
abstract = {Associate professor of public health, Morgan State University},
keywords = {african american communities,baltimore maryland,neighborhoods,No DOI found,police and community relations,racism institutional,u s history},
file = {/home/camille/Zotero/storage/YECS4MKY/Fabricant_2018_Black neighborhoods matter.pdf}
}
@misc{Ferdio,
title = {Data {{Viz Project}}},
author = {{Ferdio}},
journal = {Data Viz Project},
url = {https://datavizproject.com/},
urldate = {2024-01-28},
abstract = {Collection of data visualizations to get inspired and find the right type},
langid = {american},
file = {/home/camille/Zotero/storage/TBK63YVG/datavizproject.com.html}
}
@misc{Forrest2023,
title = {Monroe {{Nathan Work}}: A {{Black Data Pioneer}} of {{Race Statistics}}},
shorttitle = {Monroe {{Nathan Work}}},
author = {Forrest, Jason},
year = {2023},
month = feb,
journal = {Nightingale},
url = {https://nightingaledvs.com/monroe-nathan-work-education-in-the-negro-year-book/},
urldate = {2024-02-13},
abstract = {Monroe Nathan Work shed light on Black living conditions in the early 20th century using data and charts. Here's how he exposed educational inequalities.},
langid = {american},
file = {/home/camille/Zotero/storage/CA9JTS4J/monroe-nathan-work-education-in-the-negro-year-book.html}
}
@misc{France2020,
title = {Choosing {{Fonts}} for {{Your Data Visualization}}, {{Nightingale}}},
author = {France, Tiffany},
year = {2020},
month = jun,
journal = {Nightingale},
url = {https://nightingaledvs.com/choosing-fonts-for-your-data-visualization/},
urldate = {2024-02-13},
abstract = {The purpose of data visualization is to provide a layout that relays lots of information quickly.},
langid = {american},
keywords = {annotations},
file = {/home/camille/Zotero/storage/F84FP8CU/choosing-fonts-for-your-data-visualization.html}
}
@misc{Fratczak2023,
title = {Can {{Datavis Make Unpalatable Data More Enjoyable}}?},
author = {Fratczak, Monika},
year = {2023},
month = nov,
journal = {Nightingale},
url = {https://nightingaledvs.com/can-datavis-make-unpalatable-data-more-enjoyable/},
urldate = {2024-02-13},
abstract = {I studied emotional reactions to climate-related data visuals. Certain visuals evoked positive feelings---despite the unsettling topic.},
langid = {american},
keywords = {case studies,case2,storytelling},
file = {/home/camille/Zotero/storage/2D5865MD/can-datavis-make-unpalatable-data-more-enjoyable.html}
}
@misc{GeospatialSupportWorld,
title = {Geospatial {{Support For The UN World Food Programme}} - {{March}} 31, 2024},
url = {https://mapscaping.com/podcast/geospatial-support-for-the-un-world-food-programme/},
urldate = {2024-03-31},
abstract = {So you might be wondering why the United Nations World Food Programme needs a geospatial support unit. Let me give you a brief overview, Basically, they curate and maintain global datasets that they use to model the risk of sudden-onset disasters ...},
langid = {american},
file = {/home/camille/Zotero/storage/BPG9LWL4/geospatial-support-for-the-un-world-food-programme.html}
}
@book{Gilmore2023,
title = {Abolition {{Geography}}},
author = {Gilmore, Ruth Wilson},
year = {2023},
urldate = {2023-09-16},
abstract = {The first collection of writings from one of the foremost contemporary critical thinkers on racism, geography and incarceration Gathering together Ruth Wilson Gilmore's work from over three decades,...},
langid = {american},
keywords = {general},
file = {/home/camille/Zotero/storage/XXGDHXYR/abolition-geography-by-ruth-wilson-gilmore.html}
}
@misc{Gunn2021,
title = {The {{Why}}, the {{What}}, and the {{How}} in {{Dataviz}}, {{Nightingale}}},
author = {Gunn, Erica},
year = {2021},
month = jul,
journal = {Nightingale},
url = {https://nightingaledvs.com/the-why-the-what-and-the-how-in-datavis/},
urldate = {2024-02-13},
abstract = {This is part nine in a series of articles that illustrate how basic design principles can improve information display.},
langid = {american}
}
@article{H.A1995,
title = {Re-{{Thinking Margins}} and {{Borders}}: {{An Interview}} with {{Gloria Anzald{\'u}a}}},
shorttitle = {Re-{{Thinking Margins}} and {{Borders}}},
author = {Hern{\'a}ndez, Ellie and Anzald{\'u}a, Gloria},
year = {1995},
journal = {Discourse},
volume = {18},
number = {1/2},
eprint = {41389399},
eprinttype = {jstor},
pages = {7--15},
publisher = {Wayne State University Press},
issn = {1522-5321},
url = {https://www.jstor.org/stable/41389399},
urldate = {2024-04-12},
keywords = {case2,No DOI found},
file = {/home/camille/Zotero/storage/S3J7T8N6/Hernández_Anzaldúa_1995_Re-Thinking Margins and Borders.pdf}
}
@article{H.B2010,
title = {Crowdsourcing Graphical Perception: Using Mechanical Turk to Assess Visualization Design},
shorttitle = {Crowdsourcing Graphical Perception},
author = {Heer, Jeffrey and Bostock, Michael},
year = {2010},
month = apr,
journal = {Proceedings of the SIGCHI Conference on Human Factors in Computing Systems},
pages = {203--212},
doi = {10.1145/1753326.1753357},
urldate = {2023-12-25},
abstract = {Understanding perception is critical to effective visualization design. With its low cost and scalability, crowdsourcing presents an attractive option for evaluating the large design space of visualizations; however, it first requires validation. In this paper, we assess the viability of Amazon's Mechanical Turk as a platform for graphical perception experiments. We replicate previous studies of spatial encoding and luminance contrast and compare our results. We also conduct new experiments on rectangular area perception (as in treemaps or cartograms) and on chart size and gridline spacing. Our results demonstrate that crowdsourced perception experiments are viable and contribute new insights for visualization design. Lastly, we report cost and performance data from our experiments and distill recommendations for the design of crowdsourced studies.},
langid = {english},
keywords = {perception}
}
@article{H.D2011,
title = {Visualization {{Rhetoric}}: {{Framing Effects}} in {{Narrative Visualization}}},
shorttitle = {Visualization {{Rhetoric}}},
author = {Hullman, J. and Diakopoulos, N.},
year = {2011},
month = dec,
journal = {IEEE Transactions on Visualization and Computer Graphics},
volume = {17},
number = {12},
pages = {2231--2240},
issn = {1077-2626},
doi = {10.1109/TVCG.2011.255},
urldate = {2024-01-21},
abstract = {Narrative visualizations combine conventions of communicative and exploratory information visualization to convey an intended story. We demonstrate visualization rhetoric as an analytical framework for understanding how design techniques that prioritize particular interpretations in visualizations that ``tell a story'' can significantly affect end-user interpretation. We draw a parallel between narrative visualization interpretation and evidence from framing studies in political messaging, decision-making, and literary studies. Devices for understanding the rhetorical nature of narrative information visualizations are presented, informed by the rigorous application of concepts from critical theory, semiotics, journalism, and political theory. We draw attention to how design tactics represent additions or omissions of information at various levels---the data, visual representation, textual annotations, and interactivity---and how visualizations denote and connote phenomena with reference to unstated viewing conventions and codes. Classes of rhetorical techniques identified via a systematic analysis of recent narrative visualizations are presented, and characterized according to their rhetorical contribution to the visualization. We describe how designers and researchers can benefit from the potentially positive aspects of visualization rhetoric in designing engaging, layered narrative visualizations and how our framework can shed light on how a visualization design prioritizes specific interpretations. We identify areas where future inquiry into visualization rhetoric can improve understanding of visualization interpretation.},
langid = {english},
keywords = {storytelling},
file = {/home/camille/Zotero/storage/UBZRMWDQ/Hullman and Diakopoulos - 2011 - Visualization Rhetoric Framing Effects in Narrati.pdf}
}
@inproceedings{H.K.F2015,
title = {{{ISOTYPE Visualization}}: {{Working Memory}}, {{Performance}}, and {{Engagement}} with {{Pictographs}}},
shorttitle = {{{ISOTYPE Visualization}}},
booktitle = {Proceedings of the 33rd {{Annual ACM Conference}} on {{Human Factors}} in {{Computing Systems}}},
author = {Haroz, Steve and Kosara, Robert and Franconeri, Steven L.},
year = {2015},
month = apr,
pages = {1191--1200},
publisher = {ACM},
address = {Seoul Republic of Korea},
doi = {10.1145/2702123.2702275},
urldate = {2024-02-13},
abstract = {Although the infographic and design communities have used simple pictographic representations for decades, it is still unclear whether they can make visualizations more effective. Using simple charts, we tested how pictographic representations impact (1) memory for information just viewed, as well as under the load of additional information, (2) speed of finding information, and (3) engagement and preference in seeking out these visualizations. We find that superfluous images can distract. But we find no user costs -- and some intriguing benefits -- when pictographs are used to represent the data.},
isbn = {978-1-4503-3145-6},
langid = {english},
keywords = {case studies},
file = {/home/camille/Zotero/storage/2EKUGZT7/Haroz et al. - 2015 - ISOTYPE Visualization Working Memory, Performance.pdf}
}
@article{H.K.L2017,
title = {Finding a {{Clear Path}}: {{Structuring Strategies}} for {{Visualization Sequences}}},
shorttitle = {Finding a {{Clear Path}}},
author = {Hullman, Jessica and Kosara, Robert and Lam, Heidi},
year = {2017},
month = jun,
journal = {Computer Graphics Forum},
volume = {36},
number = {3},
pages = {365--375},
issn = {0167-7055, 1467-8659},
doi = {10.1111/cgf.13194},
urldate = {2024-02-13},
abstract = {Little is known about how people structure sets of visualizations to support sequential viewing. We contribute findings from several studies examining visualization sequencing and reception. In our first study, people made decisions between various possible structures as they ordered a set of related visualizations (consisting of either bar charts or thematic maps) into what they considered the clearest sequence for showing the data. We find that most people structure visualization sequences hierarchically: they create high level groupings based on shared data properties like time period, measure, level of aggregation, and spatial region, then order the views within these groupings. We also observe a tendency for certain types of similarities between views, like a common spatial region or aggregation level, to be seen as more appropriate categories for organizing views in a sequence than others, like a common time period or measure. In a second study, we find that viewers' perceptions of the quality and intention of different sequences are largely consistent with the perceptions of the users who created them. The understanding of sequence preferences and perceptions that emerges from our studies has implications for the development of visualization authoring tools and sequence recommendations for guided analysis.},
langid = {english},
file = {/home/camille/Zotero/storage/QG56546J/Hullman et al. - 2017 - Finding a Clear Path Structuring Strategies for V.pdf}
}
@misc{H.K.M+2020,
title = {{{KFF COVID-19 Vaccine Monitor}}: {{December}} 2020},
shorttitle = {{{KFF COVID-19 Vaccine Monitor}}},
author = {Hamel, Liz and Kirzinger, Ashley and Mu{\~n}ana, Cailey and Published, Mollyann Brodie},
year = {2020},
month = dec,
journal = {KFF},
url = {https://www.kff.org/coronavirus-covid-19/report/kff-covid-19-vaccine-monitor-december-2020/},
urldate = {2024-01-30},
abstract = {This initial survey for the KFF COVID-19 Vaccine Monitor tracks the public's attitudes and experiences with COVID-19 vaccinations, with a focus on sub-groups of Americans. It explores confidence in vaccines, assesses trust in messengers, and highlights key challenges for vaccination efforts.},
langid = {american},
keywords = {survey data},
file = {/home/camille/Zotero/storage/7WI6QUTF/kff-covid-19-vaccine-monitor-december-2020.html}
}
@misc{H.L.P2021,
title = {{{KFF COVID-19 Vaccine Monitor}}: {{What Do We Know About Those Who Want}} to ``{{Wait}} and {{See}}'' {{Before Getting}} a {{COVID-19 Vaccine}}?},
shorttitle = {{{KFF COVID-19 Vaccine Monitor}}},
author = {Hamel, Liz and Lopes, Lunna and Published, Mollyann Brodie},
year = {2021},
month = feb,
journal = {KFF},
url = {https://www.kff.org/coronavirus-covid-19/poll-finding/kff-covid-19-vaccine-monitor-wait-and-see/},
urldate = {2024-01-30},
abstract = {Thirty-one percent of the public wants to ``wait and see'' how the COVID-19 vaccine is working for other people before getting vaccinated themselves. While they share a similar level of vaccine hesitancy, this group is not monolithic in their attitudes and beliefs. This brief examines how people with different partisan identities and those belonging to different racial and ethnic groups differ in their levels of concern about the vaccine and may respond differently to messages and information.},
langid = {american},
keywords = {survey data},
file = {/home/camille/Zotero/storage/2EX3D623/kff-covid-19-vaccine-monitor-wait-and-see.html}
}
@misc{H.L.P2021a,
title = {{{KFF COVID-19 Vaccine Monitor}}: {{What Do We Know About Those Who Want}} to ``{{Wait}} and {{See}}'' {{Before Getting}} a {{COVID-19 Vaccine}}?},
shorttitle = {{{KFF COVID-19 Vaccine Monitor}}},
author = {Hamel, Liz and Lopes, Lunna and Published, Mollyann Brodie},
year = {2021},
month = feb,
journal = {KFF},
url = {https://www.kff.org/coronavirus-covid-19/poll-finding/kff-covid-19-vaccine-monitor-wait-and-see/},
urldate = {2024-03-05},
abstract = {Thirty-one percent of the public wants to ``wait and see'' how the COVID-19 vaccine is working for other people before getting vaccinated themselves. While they share a similar level of vaccine hesitancy, this group is not monolithic in their attitudes and beliefs. This brief examines how people with different partisan identities and those belonging to different racial and ethnic groups differ in their levels of concern about the vaccine and may respond differently to messages and information.},
langid = {american},
file = {/home/camille/Zotero/storage/VG7VWGUF/kff-covid-19-vaccine-monitor-wait-and-see.html}
}
@incollection{H.M2018,
title = {Editorial},
booktitle = {This {{Is Not}} an {{Atlas}}},
author = {Halder, Severin and Michel, Boris},
year = {2018},
month = nov,
publisher = {kollektiv orangotango},
url = {https://notanatlas.org/wp-content/uploads/2018/11/This-Is-Not-an-Atlas_Introduction.pdf},
urldate = {2024-04-13},
keywords = {case2},
file = {/home/camille/Zotero/storage/5QFNT8UT/This-Is-Not-an-Atlas_Introduction.pdf}
}
@article{Hahn2023,
title = {"{{Data}} Replicates the Existing Systems of Power" Says {{Pulitzer Prize-winner Mona Chalabi}}},
author = {Hahn, Jennifer},
year = {2023},
month = nov,
journal = {Dezeen},
url = {https://www.dezeen.com/2023/11/16/mona-chalabi-pulitzer-prize-winner/},
urldate = {2024-02-19},
abstract = {On the heels of taking home this year's Pulitzer Prize for illustrated reporting, journalist Mona Chalabi discusses the pitfalls of visualising skewed data in this exclusive interview.},
chapter = {design},
langid = {english},
keywords = {case2,data ethics},
file = {/home/camille/Zotero/storage/MH8EGGVU/mona-chalabi-pulitzer-prize-winner.html}
}
@misc{Hare2022,
title = {R {{Ladies New York Alt Text Workshop}}},
author = {Hare, Liz},
year = {2022},
month = oct,
url = {https://lizharedogs.github.io/RLadiesNYAltText/index.html},
urldate = {2024-03-05},
abstract = {Writing Meaningful Alt Texts for Data Visualizations in R},
keywords = {accessibility},
file = {/home/camille/Zotero/storage/XWRYE4NI/RLadiesNYAltText.html}
}
@misc{Holder2022,
title = {Unfair {{Comparisons}}: {{How Visualizing Social Inequality Can Make It Worse}}, {{Nightingale}}},
shorttitle = {Unfair {{Comparisons}}},
author = {Holder, Eli},
year = {2022},
month = dec,
journal = {Nightingale},
url = {https://nightingaledvs.com/unfair-comparisons-how-visualizing-social-inequality-can-make-it-worse/},
urldate = {2024-02-13},
abstract = {Our new research shows how popular chart choices can trigger unconscious social biases and reinforce systemic racism.},
langid = {american},
keywords = {equity}
}
@techreport{ipums,
title = {{{IPUMS USA}}: {{Version}} 13.0 [Dataset].},
author = {Ruggles, Stephen and Flood, Sarah and Sobek, Matthew and Brockman, Danika and Cooper, Grace and Richards, Stephanie and Schouweiler, Megan},
year = {2023},
address = {Minneapolis, MN},
institution = {IPUMS},
url = {https://doi.org/10.18128/D010.V13.0},
keywords = {dh_common}
}
@article{K.A.S+2023,
title = {On Exploring Bivariate and Trivariate Maps as Visualization Tools for Spatial Associations in Digital Soil Mapping: {{A}} Focus on Soil Properties},
shorttitle = {On Exploring Bivariate and Trivariate Maps as Visualization Tools for Spatial Associations in Digital Soil Mapping},
author = {Kebonye, Ndiye M. and Agyeman, Prince C. and Seletlo, Zibanani and Eze, Peter N.},
year = {2023},
month = apr,
journal = {Precision Agriculture},
volume = {24},
number = {2},
pages = {511--532},
issn = {13852256},
doi = {10.1007/s11119-022-09955-7},
urldate = {2023-11-27},
abstract = {The benefits of digital soil maps cannot be overemphasised. For many years, researchers have mapped different soil classes, properties and processes while identifying the spatial associations between soil properties using side-by-side visualization maps. Although this is acceptable, it may be difficult to identify complex spatial associations between the mapped soil properties. For some, the task may be challenging owing to multiple times of side-by-side placing of the maps and the possible application of none user-friendly colour palettes and or schemes. Innovative tools are proposed for visualizing and identifying spatial associations between digital soil maps (raster layers) using bivariate and trivariate maps. These tools are applied in a case study to identify the spatial interactions between pH and selected macro-nutrients [nitrogen (N) and potassium (K)] of similar locality (Czech Republic), resolution and scale. This study further gives a brief overview of the applicability of bivariate and trivariate maps following the digital soil mapping process. Results show that bivariate and trivariate maps are effective for visualizing complex associations between pH and macro-nutrients. However, precautionary measures should be taken while applying bivariate and trivariate maps to ensure they are self-explanatory and that the legend colour schemes applied are user-friendly. Also, the variables mapped should be related. In this case, pH is a key soil quality indicator that affects macro-nutrient availability in soils.},
keywords = {color,Czech Republic,CZECH Republic,DIGITAL maps,DIGITAL soil mapping,Environmental covariates,MAPS,Predictive soil mapping,Soil macro-nutrients,SOIL mapping,Visual analytics,VISUALIZATION}
}
@inproceedings{K.D.B2023,
title = {Reflecting on the {{Design Criteria}} for {{Explanatory Visualizations}}},
booktitle = {Workshop on {{Creation}}, {{Curation}}, {{Critique}} and {{Conditioning}} of {{Principles}} and {{Guidelines}} in {{Visualization}} ({{C4PGV}})},
author = {Kosara, Robert and Dasgupta, Aritra and Bertini, Enrico},
year = {2023},
month = jul,
url = {https://media.eagereyes.org/papers/2016/Kosara-C4PGV-2016.pdf},
abstract = {The visualization field has developed a good set of design criteria, metrics, and methods to assess visualization techniques and systems. These are all focused on analytical and exploratory uses, however. A large class of visualizations are created to present and communicate data and issues, however, and are seen by millions of people. We do not currently have a good grasp of what criteria should be used to systematically design and compare them, and how to do that. The aim of this paper is to raise the issue, describe different uses of visualizations, and propose criteria that should be considered while designing and critiquing them.},
langid = {english},
keywords = {No DOI found},
file = {/home/camille/Zotero/storage/CTLEZJGE/Kosara et al. - Reflecting on the Design Criteria for Explanatory V.pdf}
}
@inproceedings{K.K.H+2016,
title = {When (Ish) Is {{My Bus}}?: {{User-centered Visualizations}} of {{Uncertainty}} in {{Everyday}}, {{Mobile Predictive Systems}}},
shorttitle = {When (Ish) Is {{My Bus}}?},
booktitle = {Proceedings of the 2016 {{CHI Conference}} on {{Human Factors}} in {{Computing Systems}}},
author = {Kay, Matthew and Kola, Tara and Hullman, Jessica R. and Munson, Sean A.},
year = {2016},
month = may,
pages = {5092--5103},
publisher = {ACM},
address = {San Jose California USA},
doi = {10.1145/2858036.2858558},
urldate = {2024-01-30},
abstract = {Users often rely on realtime predictions in everyday contexts like riding the bus, but may not grasp that such predictions are subject to uncertainty. Existing uncertainty visualizations may not align with user needs or how they naturally reason about probability. We present a novel mobile interface design and visualization of uncertainty for transit predictions on mobile phones based on discrete outcomes. To develop it, we identified domain specific design requirements for visualizing uncertainty in transit prediction through: 1) a literature review, 2) a large survey of users of a popular realtime transit application, and 3) an iterative design process. We present several candidate visualizations of uncertainty for realtime transit predictions in a mobile context, and we propose a novel discrete representation of continuous outcomes designed for small screens, quantile dotplots. In a controlled experiment we find that quantile dotplots reduce the variance of probabilistic estimates by {\textasciitilde}1.15 times compared to density plots and facilitate more confident estimation by end-users in the context of realtime transit prediction scenarios.},
isbn = {978-1-4503-3362-7},
langid = {english},
keywords = {case studies,case2,uncertainty},
file = {/home/camille/Zotero/storage/6AWKL7QD/Kay et al. - 2016 - When (ish) is My Bus User-centered Visualization.pdf}
}
@misc{K.M2021,
title = {Asterisk {{Nation}}: {{One Tribe}}'s {{Challenge}} to {{Find Data About}} Its {{Population}}},
shorttitle = {Asterisk {{Nation}}},
author = {Krackov, Andy and Marikos, Sarah},
year = {2021},
month = feb,
journal = {Nightingale},
url = {https://nightingaledvs.com/asterisk-nation-one-tribes-challenge-to-find-data-about-its-population/},
urldate = {2024-01-30},
abstract = {The Yurok Tribe in far northern California needs to address a condition plaguing numerous rural communities in the United States: addiction and substance...},
langid = {american},
keywords = {case2,missing data},
file = {/home/camille/Zotero/storage/6VBMVKPA/asterisk-nation-one-tribes-challenge-to-find-data-about-its-population.html}
}
@inproceedings{K.S.A2021,
title = {Towards {{Understanding How Readers Integrate Charts}} and {{Captions}}: {{A Case Study}} with {{Line Charts}}},
shorttitle = {Towards {{Understanding How Readers Integrate Charts}} and {{Captions}}},
booktitle = {Proceedings of the 2021 {{CHI Conference}} on {{Human Factors}} in {{Computing Systems}}},
author = {Kim, Dae Hyun and Setlur, Vidya and Agrawala, Maneesh},
year = {2021},
month = may,
pages = {1--11},
publisher = {ACM},
address = {Yokohama Japan},
doi = {10.1145/3411764.3445443},
urldate = {2024-02-13},
abstract = {Charts often contain visually prominent features that draw attention to aspects of the data and include text captions that emphasize aspects of the data. Through a crowdsourced study, we explore how readers gather takeaways when considering charts and captions together. We first ask participants to mark visually prominent regions in a set of line charts. We then generate text captions based on the prominent features and ask participants to report their takeaways after observing chart-caption pairs. We find that when both the chart and caption describe a high-prominence feature, readers treat the doubly emphasized high-prominence feature as the takeaway; when the caption describes a low-prominence chart feature, readers rely on the chart and report a higher-prominence feature as the takeaway. We also find that external information that provides context, helps further convey the caption's message to the reader. We use these findings to provide guidelines for authoring effective chart-caption pairs.},
isbn = {978-1-4503-8096-6},