Gabrielle Mérite

Alan Wilson

Data design systems and styleguides are currently a huge trend in the data design world. Moritz is joined by Gabrielle Mérite and Alan Wilson and together we exchange experiences in this emerging space, from designing dataviz components as part of Adobe Spectrum, the styleguide for Deloitte’s Insights Magazine or the WHO Data Design Language. Gabriele also wrote about adding touches of ethical guidance in guidelines in one of her recent newsletters. Enjoy! Related episodes Challenges of Being a Vis Professional in Industry with Elijah MeeksData Visualization at Capital One with Kim Rees and Steph Hay

Data design systems and styleguides are currently a huge trend in the data design world. Moritz is joined by <a href="https://www.gabriellemerite.com" rel="nofollow" target="_blank">Gabrielle Mérite</a> and <a href="https://adobe.design/stories/our-people/profile/alan-wilson" rel="nofollow" target="_blank">Alan Wilson</a> and together we exchange experiences in this emerging space, from designing dataviz components as part of <a href="https://spectrum.adobe.com" rel="nofollow" target="_blank">Adobe Spectrum</a>, the styleguide for <a href="https://www.pentagram.com/work/deloitte-insights?rel=discipline&amp;rel-id=16" rel="nofollow" target="_blank">Deloitte’s Insights Magazine</a> or the <a href="https://truth-and-beauty.net/projects/who" rel="nofollow" target="_blank">WHO Data Design Language</a>. Gabriele also wrote about adding touches of ethical guidance in guidelines in <a href="https://gabmd.substack.com/p/lessons-from-pentagram-1" rel="nofollow" target="_blank">one of her recent newsletters.</a> Enjoy! <h3>Related episodes</h3> <ul><li><a href="https://datastori.es/95-challenges-of-being-a-vis-professional-in-industry-with-elijah-meeks/" rel="nofollow" target="_blank">Challenges of Being a Vis Professional in Industry with Elijah Meeks</a></li><li><a href="https://datastori.es/99-data-visualization-at-capital-one-with-kim-rees-and-steph-hay/" rel="nofollow" target="_blank">Data Visualization at Capital One with Kim Rees and Steph Hay</a></li></ul>

170  |  Formalizing Design with Gabrielle Mérite and Alan Wilson

Vidya Setlur

We have Vidya Setlur on the show to talk about the role language, and natural language processing (NLP) play in data visualization and analytics. Vidya is the director of research at Tableau and has a background in natural language processing and visualization. She is one of the main drivers behind Eviza, a research-based prototype and the corresponding product Ask Data, developed within Tableau to interact with data visualizations through natural language. She is also the co-author, with Bridget Cogley, of Functional Aesthetics for Data Visualization, a new book on data visualization with a lot of information about semantics and language in data visualization. In the episode, we talk about the challenges of going from a research prototype to an actual product, research vs. engineering, speech and natural language interfaces, the many ways language plays a role in visualization, the advent of language models, and much more. Enjoy the show!   Links  Winners of Information is Beautiful Awards  Book: Functional Aesthetics for Data Visualization Paper: Automatic Generation of Semantic Icon Encodings for Visualizations Paper: A Linguistic Approach to Categorical Color Assignment for Data Visualization Eviza: A Natural Language Interface for Visual Analysis Paper: Snowy: Recommending Utterances for Conversational Visual Analysis  — Remember: our podcast is listener-supported. Please consider donating using Patreon or Paypal. Thanks!  Related episodes Text Visualization: Past, Present and Future with Chris Collins

We have <a href="https://research.tableau.com/user/vidya-setlur" rel="nofollow" target="_blank">Vidya Setlur</a> on the show to talk about the role language, and natural language processing (NLP) play in data visualization and analytics. Vidya is the director of research at Tableau and has a background in natural language processing and visualization. She is one of the main drivers behind <a href="https://research.tableau.com/paper/eviza-natural-language-interface-visual-analysis" rel="nofollow" target="_blank">Eviza</a>, a research-based prototype and the corresponding product <a href="https://www.tableau.com/solutions/ai-analytics/augmented-analytics" rel="nofollow" target="_blank">Ask Data</a>, developed within Tableau to interact with data visualizations through natural language. She is also the co-author, with <a href="https://bridgetcogley.com/" rel="nofollow" target="_blank">Bridget Cogley</a>, of <a href="https://www.functionalaestheticsbook.com/" rel="nofollow" target="_blank">Functional Aesthetics for Data Visualization</a>, a new book on data visualization with a lot of information about semantics and language in data visualization. In the episode, we talk about the challenges of going from a research prototype to an actual product, research vs. engineering, speech and natural language interfaces, the many ways language plays a role in visualization, the advent of language models, and much more. Enjoy the show! Links <ul> <li><a href="https://www.informationisbeautifulawards.com/news/593-information-is-beautiful-awards-2022-the-winners" rel="nofollow" target="_blank">Winners of Information is Beautiful Awards</a> </li> <li>Book: <a href="https://www.functionalaestheticsbook.com/" rel="nofollow" target="_blank">Functional Aesthetics for Data Visualization</a></li> <li>Paper: <a href="https://research.tableau.com/sites/default/files/semanticshapes-final.pdf" rel="nofollow" target="_blank">Automatic Generation of Semantic Icon Encodings for Visualizations</a></li> <li>Paper: <a href="https://research.tableau.com/sites/default/files/setlurstoneinfovis2015_2.pdf" rel="nofollow" target="_blank">A Linguistic Approach to Categorical Color Assignment for Data Visualization</a></li> <li><a href="https://research.tableau.com/paper/eviza-natural-language-interface-visual-analysis" rel="nofollow" target="_blank">Eviza: A Natural Language Interface for Visual Analysis</a></li> <li>Paper: <a href="https://arxiv.org/pdf/2110.04323.pdf" rel="nofollow" target="_blank">Snowy: Recommending Utterances for Conversational Visual Analysis</a></li> </ul> — Remember: our podcast is listener-supported. Please consider donating using <a href="https://www.patreon.com/datastories" rel="nofollow" target="_blank">Patreon</a> or <a href="https://www.paypal.com/paypalme/datastories" rel="nofollow" target="_blank">Paypal</a>. Thanks! <h3>Related episodes</h3> <ul><li><a href="https://datastori.es/text-visualization-past-present-and-future-with-chris-collins-ds62/" rel="nofollow" target="_blank">Text Visualization: Past, Present and Future with Chris Collins</a></li></ul>

169  |  Data Conversations with Vidya Setlur

Tamara Munzner

Finally, this year we managed to record another classic episode from the IEEE VIS Conference (we recorded a total of 10 with this one!) We have Data Stories’ friend Prof. Tamara Munzner with us to talk about the conference and to highlight a few things she picked from the many events that happened over this week-long event.     Links  IEEE Vis ’22 Our guest: Tamara Munzner VIS Keynote: Marti Hearst – Show It or Tell It?       VIS Capstone: Kerry Magruder – Galileo’s Telescope Discoveries: Thinking Visually in the History of Science Keynote BELIV workshop: Casey Fiesler – Data Is People, Research Ethics Beyond Human Subjects       VAST 10 Year Test of Time Award: Enterprise Data Analysis and Visualization: An Interview Study InfoVis 10 Year Test of Time Award: Design study methodology: Reflections from the trenches and the stacks Paper: HiTailor: Interactive Transformation and Visualization for Hierarchical Tabular Data  Paper: Dashboard Design Patterns Book: AK Peters Visualization series Paper: VegaFusion: Automatic Server-Side Scaling for Interactive Vega Visualizations Paper: Plotly Resampler: Effective Visual Analytics for Large Time Series   Paper: Visualizing Graph Neural Networks with CorGIE: Corresponding a Graph to Its Embedding alt.VIS workshop Jo Wood’s visual essay “Beyond the Walled Garden“ Paper: Affective Learning Objectives for Communicative Visualizations    Related episodes from Visweek 2012IEEE VIS'13 Highlights w/ Robert KosaraIEEE VIS'14Tamara MunznerIEEE VIS’15 Recap with Robert Kosara and Johanna FuldaHighlights from IEEE VIS'16 with Jessica Hullman and Robert KosaraReview of IEEE VIS’17 with Jessica Hullman and Robert KosaraHighlights from IEEE VIS 2018Highlights from IEEE VIS'19 with Tamara Munzner and Robert KosaraHighlights from IEEE VIS'20 with Miriah Meyer and Danielle Szafir

Finally, this year we managed to record another classic episode from the IEEE VIS Conference (we recorded a total of 10 with this one!) We have Data Stories’ friend Prof. Tamara Munzner with us to talk about the conference and to highlight a few things she picked from the many events that happened over this week-long event. Links <ul> <li><a href="https://ieeevis.org/year/2022/welcome" rel="nofollow" target="_blank">IEEE Vis ’22</a></li> <li>Our guest: <a href="https://www.cs.ubc.ca/~tmm/" rel="nofollow" target="_blank">Tamara Munzner</a></li> <li>VIS Keynote: <a href="https://people.ischool.berkeley.edu/~hearst/" rel="nofollow" target="_blank">Marti Hearst</a> – <a href="https://www.youtube.com/watch?v=BDTEkT8p4Gs" rel="nofollow" target="_blank">Show It or Tell It</a>?     </li> <li>VIS Capstone: Kerry Magruder – <a href="https://ieeevis.org/year/2022/info/capstone-speaker" rel="nofollow" target="_blank">Galileo’s Telescope Discoveries: Thinking Visually in the History of Science</a></li> <li><a href="https://beliv-workshop.github.io/about.html" rel="nofollow" target="_blank">Keynote BELIV workshop</a>: <a href="https://caseyfiesler.com/" rel="nofollow" target="_blank">Casey Fiesler</a> – Data Is People, Research Ethics Beyond Human Subjects     </li> <li>VAST 10 Year Test of Time Award: <a href="http://idl.cs.washington.edu/files/2012-EnterpriseAnalysisInterviews-VAST.pdf" rel="nofollow" target="_blank">Enterprise Data Analysis and Visualization: An Interview Study</a></li> <li>InfoVis 10 Year Test of Time Award: <a href="https://www.cs.ubc.ca/labs/imager/tr/2012/dsm/" rel="nofollow" target="_blank">Design study methodology: Reflections from the trenches and the stacks</a></li> <li>Paper: <a href="https://arxiv.org/pdf/2208.05821.pdf" rel="nofollow" target="_blank">HiTailor: Interactive Transformation and Visualization for Hierarchical Tabular Data</a> </li> <li>Paper: <a href="https://arxiv.org/abs/2205.00757" rel="nofollow" target="_blank">Dashboard Design Patterns</a></li> <li>Book: <a href="https://www.routledge.com/AK-Peters-Visualization-Series/book-series/CRCVIS" rel="nofollow" target="_blank">AK Peters Visualization series</a></li> <li>Paper: <a href="https://arxiv.org/pdf/2208.06631.pdf" rel="nofollow" target="_blank">VegaFusion: Automatic Server-Side Scaling for Interactive Vega Visualizations</a></li> <li>Paper: <a href="https://arxiv.org/pdf/2206.08703.pdf" rel="nofollow" target="_blank">Plotly Resampler: Effective Visual Analytics for Large Time Series </a> </li> <li>Paper: <a href="https://arxiv.org/abs/2106.12839" rel="nofollow" target="_blank">Visualizing Graph Neural Networks with CorGIE: Corresponding a Graph to Its Embedding</a></li> <li><a href="https://altvis.github.io/" rel="nofollow" target="_blank">alt.VIS workshop</a></li> <li>Jo Wood’s visual essay “<a href="https://vimeo.com/760406142" rel="nofollow" target="_blank">Beyond the Walled Garden</a>“</li> <li>Paper: <a href="https://arxiv.org/abs/2208.04078" rel="nofollow" target="_blank">Affective Learning Objectives for Communicative Visualizations</a></li> </ul> <h3>Related episodes</h3> <ul><li><a href="https://datastori.es/episode-13-from-visweek-2012/" rel="nofollow" target="_blank">from Visweek 2012</a></li><li><a href="https://datastori.es/data-stories-28-ieee-vis13-highlights-w-robert-kosara/" rel="nofollow" target="_blank">IEEE VIS'13 Highlights w/ Robert Kosara</a></li><li><a href="https://datastori.es/data-stories-43-ieee-vis14/" rel="nofollow" target="_blank">IEEE VIS'14</a></li><li><a href="https://datastori.es/data-stories-44/" rel="nofollow" target="_blank">Tamara Munzner</a></li><li><a href="https://datastori.es/vis15-recap-with-robert-kosara-and-johanna-fulda-ds-63/" rel="nofollow" target="_blank">IEEE VIS’15 Recap with Robert Kosara and Johanna Fulda</a></li><li><a href="https://datastori.es/86-highlights-from-ieee-vis16-with-jessica-hullman-and-robert-kosara/" rel="nofollow" target="_blank">Highlights from IEEE VIS'16 with Jessica Hullman and Robert Kosara</a></li><li><a href="https://datastori.es/108-review-of-ieee-vis17-with-jessica-hullman-and-robert-kosara/" rel="nofollow" target="_blank">Review of IEEE VIS’17 with Jessica Hullman and Robert Kosara</a></li><li><a href="https://datastori.es/130-highlights-from-ieee-vis-2018/" rel="nofollow" target="_blank">Highlights from IEEE VIS 2018</a></li><li><a href="https://datastori.es/150-highlights-from-ieee-vis19-with-tamara-munzner-and-robert-kosara/" rel="nofollow" target="_blank">Highlights from IEEE VIS'19 with Tamara Munzner and Robert Kosara</a></li><li><a href="https://datastori.es/162-highlights-from-ieee-vis20-with-miriah-meyer-and-danielle-szafir/" rel="nofollow" target="_blank">Highlights from IEEE VIS'20 with Miriah Meyer and Danielle Szafir</a></li></ul>

168  |  Highlights from IEEE VIS'22 with Tamara Munzner

Andrew Gelman

Jessica Hullman

In this new episode, we talk about the interplay between statistics and data visualization. We do that with Andrew Gelman, Professor of Statistics and Political Science at Columbia University, and Jessica Hullman, Professor of Computer Science at Northwestern University. Andrew started the popular blog “Statistical Modeling, Causal Inference, and Social Science,” which has an active community of readers and has been around for many years. Jessica started contributing lately with many exciting posts, several of which have to do with data visualization. In the episode, we touch upon many topics, including the story behind the blog, the role of surprises, anomalies, and storytelling in science, the Anscombe’s quartet, and exploratory data analysis. Links  Jessica Hullman: http://users.eecs.northwestern.edu/~jhullman/ Andrew Gelman: http://www.stat.columbia.edu/~gelman/ Blog: Statistical Modeling, Causal Inference, and Social Science: https://statmodeling.stat.columbia.edu/ Andrew’s 2003 paper on visualization as model checks: “Exploratory Data Analysis for Complex Models” Jessica and Andrew’s follow-up article expanding on the idea of model checks for visualization research: “Designing for Interactive Exploratory Data Analysis Requires Theories of Graphical Inference” Andrew and Thomas’ paper on stories in social sciences: “When Do Stories Work? Evidence and Illustration in the Social Sciences”  — Remember: our podcast is listener-supported; please consider donating Using Patreon or Paypal. Thanks! Related episodes Big Data Skepticism w/ Kate CrawfordScience Communication at SciAm w/ Jen ChristiansenStatistical Numbing with Paul SlovicMachine Bias with Jeff LarsonCalling Bullshit with Carl Bergstrom and Jevin WestData Science and Visualization with David Robinson

In this new episode, we talk about the interplay between statistics and data visualization. We do that with <a href="http://www.stat.columbia.edu/~gelman/" rel="nofollow" target="_blank">Andrew Gelman</a>, Professor of Statistics and Political Science at Columbia University, and <a href="http://users.eecs.northwestern.edu/~jhullman/" rel="nofollow" target="_blank">Jessica Hullman</a>, Professor of Computer Science at Northwestern University. Andrew started the popular blog “Statistical Modeling, Causal Inference, and Social Science,” which has an active community of readers and has been around for many years. Jessica started contributing lately with many exciting posts, several of which have to do with data visualization. In the episode, we touch upon many topics, including the story behind the blog, the role of surprises, anomalies, and storytelling in science, the <a href="https://en.wikipedia.org/wiki/Anscombe%27s_quartet" rel="nofollow" target="_blank">Anscombe’s quartet</a>, and exploratory data analysis. Links <ul> <li>Jessica Hullman: <a href="http://users.eecs.northwestern.edu/~jhullman/" rel="nofollow" target="_blank">http://users.eecs.northwestern.edu/~jhullman/</a></li> <li>Andrew Gelman: <a href="http://www.stat.columbia.edu/~gelman/" rel="nofollow" target="_blank">http://www.stat.columbia.edu/~gelman/</a></li> <li>Blog: Statistical Modeling, Causal Inference, and Social Science: <a href="https://statmodeling.stat.columbia.edu/" rel="nofollow" target="_blank">https://statmodeling.stat.columbia.edu/</a></li> <li>Andrew’s 2003 paper on visualization as model checks: “<a href="https://www.tandfonline.com/doi/abs/10.1198/106186004X11435?journalCode=ucgs20" rel="nofollow" target="_blank">Exploratory Data Analysis for Complex Models</a>”</li> <li>Jessica and Andrew’s follow-up article expanding on the idea of model checks for visualization research: “<a href="https://hdsr.mitpress.mit.edu/pub/w075glo6/release/3" rel="nofollow" target="_blank">Designing for Interactive Exploratory Data Analysis Requires Theories of Graphical Inference</a>”</li> <li>Andrew and Thomas’ paper on stories in social sciences: “<a href="https://journals.sagepub.com/doi/pdf/10.1177/0049124114526377?casa_token=cTq-ZsSVb6YAAAAA:NXIMPSaOIDUS3PVOrNvUm_dkO1D16CGJX4nhfC6ttGcqH324MCWTGlrt1a9m0bddQ8cBsNrQfEcn" rel="nofollow" target="_blank">When Do Stories Work? Evidence and Illustration in the Social Sciences</a>”</li> </ul> — Remember: our podcast is listener-supported; please consider donating Using <a href="https://www.patreon.com/datastories" rel="nofollow" target="_blank">Patreon</a> or <a href="https://www.paypal.com/paypalme/datastories" rel="nofollow" target="_blank">Paypal</a>. Thanks! <h3>Related episodes</h3> <ul><li><a href="https://datastori.es/data-stories-27-big-data-skepticism-w-kate-crawford/" rel="nofollow" target="_blank">Big Data Skepticism w/ Kate Crawford</a></li><li><a href="https://datastori.es/ds-52-science-communication-w-jen-christiansen/" rel="nofollow" target="_blank">Science Communication at SciAm w/ Jen Christiansen</a></li><li><a href="https://datastori.es/84-statistical-numbing-with-paul-slovic/" rel="nofollow" target="_blank">Statistical Numbing with Paul Slovic</a></li><li><a href="https://datastori.es/85-machine-bias-with-jeff-larson/" rel="nofollow" target="_blank">Machine Bias with Jeff Larson</a></li><li><a href="https://datastori.es/97-calling-bullshit-with-carl-bergstrom-and-jevin-west/" rel="nofollow" target="_blank">Calling Bullshit with Carl Bergstrom and Jevin West</a></li><li><a href="https://datastori.es/120-data-science-with-david-robinson/" rel="nofollow" target="_blank">Data Science and Visualization with David Robinson</a></li></ul>

167  |  Visualization and Statistics with Andrew Gelman and Jessica Hullman

Amanda Makulec

Hey all, we are back! In this episode, we have Amanda Makulec to catch up on what happened during this whole period of time. Amanda is a public health and data visualization expert and she is the Executive Director of the Data Visualization Society. In the episode, we talk about the Data Visualization Society, the new Information is Beautiful Awards (now organized by the DVS team), and how visualization has evolved lately. Links  WHO Data Design Language Climate &amp; Conflict Analysis for German Foreign Office Enrico’s FILWD Newsletter https://www.amandamakulec.com https://twitter.com/abmakulec https://www.datavisualizationsociety.org https://www.informationisbeautifulawards.com/awards/2022 Frank Elavsky (A11y work in vis) Uncertainty visualization work (Jessica Hullman and Matthew Kay) Data Humanism (Giorgia Lupi) Moritz’s keynote at EUROVIS Crystal Lee’s work on how vis is used for covid19 communication Why Shouldn’t All Charts Be Scatter Plots? Beyond Precision-Driven Visualizations Joss Fong’s Automating Bias Warming stripes  — Remember: our podcast is listener-supported, please consider making a donation! Using Patreon or Paypal. Thanks  Related episodes Data Visualization SocietyIconic Climate Visuals with Ed Hawkins

Hey all, we are back! In this episode, we have <a href="https://www.amandamakulec.com/" rel="nofollow" target="_blank">Amanda Makulec</a> to catch up on what happened during this whole period of time. Amanda is a public health and data visualization expert and she is the Executive Director of the <a href="https://www.datavisualizationsociety.org" rel="nofollow" target="_blank">Data Visualization Society</a>. In the episode, we talk about the Data Visualization Society, the new <a href="https://www.informationisbeautifulawards.com/awards/2022" rel="nofollow" target="_blank">Information is Beautiful Awards</a> (now organized by the DVS team), and how visualization has evolved lately. Links <ul> <li><a href="https://truth-and-beauty.net/projects/who" rel="nofollow" target="_blank">WHO Data Design Language</a></li> <li><a href="https://truth-and-beauty.net/projects/climate-and-conflict" rel="nofollow" target="_blank">Climate &amp; Conflict Analysis for German Foreign Office</a></li> <li><a href="https://filwd.substack.com/" rel="nofollow" target="_blank">Enrico’s FILWD Newsletter</a></li> <li><a href="https://www.amandamakulec.com" rel="nofollow" target="_blank">https://www.amandamakulec.com</a></li> <li><a href="https://twitter.com/abmakulec" rel="nofollow" target="_blank">https://twitter.com/abmakulec</a></li> <li><a href="https://www.datavisualizationsociety.org" rel="nofollow" target="_blank">https://www.datavisualizationsociety.org</a></li> <li><a href="https://www.informationisbeautifulawards.com/awards/2022" rel="nofollow" target="_blank">https://www.informationisbeautifulawards.com/awards/2022</a></li> <li><a href="https://www.frank.computer/" rel="nofollow" target="_blank">Frank Elavsky (A11y work in vis)</a></li> <li><a href="https://idl.cs.washington.edu/papers/uncertainty-eval-survey/" rel="nofollow" target="_blank">Uncertainty visualization work (Jessica Hullman and Matthew Kay)</a></li> <li><a href="http://giorgialupi.com/data-humanism-my-manifesto-for-a-new-data-wold" rel="nofollow" target="_blank">Data Humanism (Giorgia Lupi)</a></li> <li><a href="https://youtu.be/6HX3te-eO8w?t=256" rel="nofollow" target="_blank">Moritz’s keynote at EUROVIS</a></li> <li><a href="http://vis.csail.mit.edu/pubs/viral-visualizations/" rel="nofollow" target="_blank">Crystal Lee’s work on how vis is used for covid19 communication</a></li> <li><a href="https://arxiv.org/abs/2008.11310" rel="nofollow" target="_blank">Why Shouldn’t All Charts Be Scatter Plots? Beyond Precision-Driven Visualizations</a></li> <li><a href="https://aas.princeton.edu/news/are-we-automating-bias" rel="nofollow" target="_blank">Joss Fong’s Automating Bias</a></li> <li><a href="https://datastori.es/147-iconic-climate-visuals-with-ed-hawkins/" rel="nofollow" target="_blank">Warming stripes</a></li> </ul> — Remember: our podcast is listener-supported, please consider making a donation! Using <a href="https://www.patreon.com/datastories" rel="nofollow" target="_blank">Patreon</a> or <a href="https://www.paypal.com/paypalme/datastories" rel="nofollow" target="_blank">Paypal</a>. Thanks <h3>Related episodes</h3> <ul><li><a href="https://datastori.es/data-visualization-society/" rel="nofollow" target="_blank">Data Visualization Society</a></li><li><a href="https://datastori.es/147-iconic-climate-visuals-with-ed-hawkins/" rel="nofollow" target="_blank">Iconic Climate Visuals with Ed Hawkins</a></li></ul>

166  |  Catching up with Amanda Makulec

Sarah Fossheim

Visualization is a very powerful cognitive tool. I think we all agree with that. But what happens if a person is visually impaired or has other impairments that prevent them to fully benefit from it? It’s surprising, despite the huge success visualization had during these last few years, how little we have to show in terms of supporting this very relevant segment of the population. To discuss this topic we have on the show Sarah Fossheim. Sarah is a full-stack developer and UX researcher with a specific expertise on accessible design for data visualization projects. See for instance their “How to create a screen reader accessible graph like Apple’s with D3.js“. On the show, we talk about what is accessibility and what role it plays in data visualization, how to make charts and visual representations more accessible, and how to get started with accessible design. This is a hugely important topic and we hope you will find some inspiration by listening to it! Links:  https://fossheim.io https://twitter.com/liatrisbian Chartability &lt;https://chartability.fizz.studio&gt; Dataviz Accessibility Resources &lt;https://github.com/dataviza11y/resources&gt; Outlier 2021—Are your visualizations excluding ppl? Writing Alt Text for Data Visualization Apple previews powerful software updates designed for people with disabilities Summarizing Information Graphics Textually Loud Numbers Podcast DS 075  |  Listening to Data From Space with Scott Hughes   — Remember: our podcast is listener-supported, please consider making a donation! Using Patreon or Paypal. Thanks  Related episodes Listening to Data From Space with Scott HughesTouch Graphics with Steve Landau

Visualization is a very powerful cognitive tool. I think we all agree with that. But what happens if a person is visually impaired or has other impairments that prevent them to fully benefit from it? It’s surprising, despite the huge success visualization had during these last few years, how little we have to show in terms of supporting this very relevant segment of the population. To discuss this topic we have on the show <a href="https://fossheim.io" rel="nofollow" target="_blank">Sarah Fossheim.</a> Sarah is a full-stack developer and UX researcher with a specific expertise on accessible design for data visualization projects. See for instance their “<a href="https://fossheim.io/writing/posts/apple-dataviz-a11y-tutorial/" rel="nofollow" target="_blank">How to create a screen reader accessible graph like Apple’s with D3.js</a>“. On the show, we talk about what is accessibility and what role it plays in data visualization, how to make charts and visual representations more accessible, and how to get started with accessible design. This is a hugely important topic and we hope you will find some inspiration by listening to it! Links: <ul> <li><a href="https://fossheim.io" rel="nofollow" target="_blank">https://fossheim.io</a></li> <li><a href="https://twitter.com/liatrisbian" rel="nofollow" target="_blank">https://twitter.com/liatrisbian</a></li> <li>Chartability &lt;<a href="https://chartability.fizz.studio" rel="nofollow" target="_blank">https://chartability.fizz.studio&gt;</a></li> <li>Dataviz Accessibility Resources &lt;<a href="https://github.com/dataviza11y/resources" rel="nofollow" target="_blank">https://github.com/dataviza11y/resources</a>&gt;</li> <li><a href="https://www.youtube.com/watch?v=SWB-KLXN-Ok" rel="nofollow" target="_blank">Outlier 2021—Are your visualizations excluding ppl?</a></li> <li><a href="https://medium.com/nightingale/writing-alt-text-for-data-visualization-2a218ef43f81" rel="nofollow" target="_blank">Writing Alt Text for Data Visualization</a></li> <li><a href="https://www.apple.com/newsroom/2021/05/apple-previews-powerful-software-updates-designed-for-people-with-disabilities/" rel="nofollow" target="_blank">Apple previews powerful software updates designed for people with disabilities</a></li> <li><a href="http://cognet.mit.edu/journal/10.1162/coli_a_00091" rel="nofollow" target="_blank">Summarizing Information Graphics Textually</a></li> <li><a href="https://www.loudnumbers.net/" rel="nofollow" target="_blank">Loud Numbers Podcast</a></li> <li><a href="https://datastori.es/75-sonification-scott-hughes/" rel="nofollow" target="_blank">DS 075  |  Listening to Data From Space with Scott Hughes</a> </li> </ul> — Remember: our podcast is listener-supported, please consider making a donation! Using <a href="https://www.patreon.com/datastories" rel="nofollow" target="_blank">Patreon</a> or <a href="https://www.paypal.com/paypalme/datastories" rel="nofollow" target="_blank">Paypal</a>. Thanks <h3>Related episodes</h3> <ul><li><a href="https://datastori.es/75-sonification-scott-hughes/" rel="nofollow" target="_blank">Listening to Data From Space with Scott Hughes</a></li><li><a href="https://datastori.es/123-touch-graphics-with-steve-landau/" rel="nofollow" target="_blank">Touch Graphics with Steve Landau</a></li></ul>

165  |  Data Visualization Accessibility with Sarah Fossheim

Sandra Rendgen

Edward Tufte

We have our friend Sandra Rendgen on the show to talk about the work of Edward Tufte. Tufte does not need any introductions of course. We discuss his early works and efforts, all the books he published, his contribution and legacy and the influence he had on our work. Enjoy the show! Remember: our podcast is listener-supported, please consider making a donation! Using Patreon or Paypal. Thanks  Links  Impfdashboard &lt;https://impfdashboard.de&gt; Enrico’s ML vis work: Slice Lens &lt;https://github.com/nyuvis/SliceLens&gt; Observable notebooks for teaching &lt;https://observablehq.com/collection/@nyuvis/guides-and-examples&gt; Our guest: Sandra Rendgen &lt;https://sandrarendgen.wordpress.com/&gt; First book “The Visual Display of Quantitative Information” and how it influenced a lot of people &lt;https://www.edwardtufte.com/tufte/books_vdqi&gt; Second book “Envisioning Information” &lt;https://www.edwardtufte.com/tufte/books_ei&gt; Third book “Visual Explanations: Images and Quantities, Evidence and Narrative”&lt;https://www.edwardtufte.com/tufte/books_visex&gt;  Fourth book “Beautiful Evidence” &lt;https://www.edwardtufte.com/tufte/books_visex&gt; Fifth book “Seeing with Fresh Eyes: Meaning, Space, Data, Truth“ &lt;https://www.edwardtufte.com/tufte/seeing-with-fresh-eyes&gt; Robert Kosara’s review of Tufte’s workshops &lt;https://eagereyes.org/criticism/edward-tufte-one-day-course&gt;

We have our friend Sandra Rendgen on the show to talk about the work of Edward Tufte. Tufte does not need any introductions of course. We discuss his early works and efforts, all the books he published, his contribution and legacy and the influence he had on our work. Enjoy the show! Remember: our podcast is listener-supported, please consider making a donation! Using <a href="https://www.patreon.com/datastories" rel="nofollow" target="_blank">Patreon</a> or <a href="https://www.paypal.com/paypalme/datastories" rel="nofollow" target="_blank">Paypal</a>. Thanks Links <ul> <li>Impfdashboard &lt;<a href="https://impfdashboard.de" rel="nofollow" target="_blank">https://impfdashboard.de</a>&gt;</li> <li>Enrico’s ML vis work: Slice Lens &lt;<a href="https://github.com/nyuvis/SliceLens" rel="nofollow" target="_blank">https://github.com/nyuvis/SliceLens</a>&gt;</li> <li>Observable notebooks for teaching &lt;<a href="https://observablehq.com/collection/@nyuvis/guides-and-examples" rel="nofollow" target="_blank">https://observablehq.com/collection/@nyuvis/guides-and-examples</a>&gt;</li> <li>Our guest: Sandra Rendgen &lt;<a href="https://sandrarendgen.wordpress.com/" rel="nofollow" target="_blank">https://sandrarendgen.wordpress.com/</a>&gt;</li> <li>First book “The Visual Display of Quantitative Information” and how it influenced a lot of people &lt;<a href="https://www.edwardtufte.com/tufte/books_vdqi" rel="nofollow" target="_blank">https://www.edwardtufte.com/tufte/books_vdqi</a>&gt;</li> <li>Second book “Envisioning Information” &lt;<a href="https://www.edwardtufte.com/tufte/books_ei" rel="nofollow" target="_blank">https://www.edwardtufte.com/tufte/books_ei</a>&gt;</li> <li>Third book “Visual Explanations: Images and Quantities, Evidence and Narrative”&lt;<a href="https://www.edwardtufte.com/tufte/books_visex" rel="nofollow" target="_blank">https://www.edwardtufte.com/tufte/books_visex</a>&gt;</li> <li> Fourth book “Beautiful Evidence” &lt;<a href="https://www.edwardtufte.com/tufte/books_visex" rel="nofollow" target="_blank">https://www.edwardtufte.com/tufte/books_visex</a>&gt;</li> <li>Fifth book “Seeing with Fresh Eyes: Meaning, Space, Data, Truth“ &lt;<a href="https://www.edwardtufte.com/tufte/seeing-with-fresh-eyes" rel="nofollow" target="_blank">https://www.edwardtufte.com/tufte/seeing-with-fresh-eyes</a>&gt;</li> <li>Robert Kosara’s review of Tufte’s workshops &lt;<a href="https://eagereyes.org/criticism/edward-tufte-one-day-course" rel="nofollow" target="_blank">https://eagereyes.org/criticism/edward-tufte-one-day-course</a>&gt;</li></ul>

164  |  Edward Tufte's complete work with Sandra Rendgen

Amelia Wattenberger

This week, we are joined by Amelia Wattenberger, journalist-engineer at the Pudding and book author. We discuss the exciting Svelte framework for web development, which is especially well suited for developing interactive data visualizations. Hear how it compares to other frameworks like react, why web development nowadays seems so complicated, and finally, hear a few ideas for last minute dataviz-related present ideas for the holiday season  Links  Svelte tutorial svelte.recipes Svelte Radio Mathias Stahl: How you setup data visualization with Svelte Layercake “I am a book. I am a portal to the universe.” Pilot G-Tec C4  https://www.madefromdata.com/products https://frontendmasters.com/courses/d3/ https://frontendmasters.com/courses/svelte/    Remember: our podcast is listener-supported, please consider making a donation! Using Patreon or Paypal. Thanks  Related episodes NYT Graphics and D3 with Mike Bostock and Shan CarterThe Pudding with Matt Daniels

This week, we are joined by <a href="https://wattenberger.com" rel="nofollow" target="_blank">Amelia Wattenberger</a>, journalist-engineer at the <a href="https://pudding.cool" rel="nofollow" target="_blank">Pudding </a>and <a href="https://www.newline.co/fullstack-d3" rel="nofollow" target="_blank">book author</a>. We discuss the exciting <a href="http://svelte.dev/" rel="nofollow" target="_blank">Svelte</a> framework for web development, which is especially well suited for developing interactive data visualizations. Hear how it compares to other frameworks like react, why web development nowadays seems so complicated, and finally, hear a few ideas for last minute dataviz-related present ideas for the holiday season Links <ul> <li><a href="https://svelte.dev/tutorial/basics" rel="nofollow" target="_blank">Svelte tutorial</a></li> <li><a href="https://svelte.recipes" rel="nofollow" target="_blank">svelte.recipes</a></li> <li><a href="https://www.svelteradio.com" rel="nofollow" target="_blank">Svelte Radio</a></li> <li>Mathias Stahl: <a href="https://www.youtube.com/watch?v=xtTrcCp2aVU" rel="nofollow" target="_blank">How you setup data visualization with Svelte</a></li> <li><a href="https://layercake.graphics" rel="nofollow" target="_blank">Layercake</a></li> <li><a href="https://www.penguin.co.uk/books/314/314526/i-am-a-book--i-am-a-portal-to-the-universe-/9780241408759.html" rel="nofollow" target="_blank">“I am a book. I am a portal to the universe.”</a></li> <li><a href="https://www.pilotpen.eu/en/g-tec-c4-extra-fine-tip.html" rel="nofollow" target="_blank">Pilot G-Tec C4 </a></li> <li><a href="https://www.madefromdata.com/products" rel="nofollow" target="_blank">https://www.madefromdata.com/products</a></li> <li><a href="https://frontendmasters.com/courses/d3/" rel="nofollow" target="_blank">https://frontendmasters.com/courses/d3/</a></li> <li><a href="https://frontendmasters.com/courses/svelte/" rel="nofollow" target="_blank">https://frontendmasters.com/courses/svelte/</a></li> </ul> Remember: our podcast is listener-supported, please consider making a donation! Using <a href="https://www.patreon.com/datastories" rel="nofollow" target="_blank">Patreon</a> or <a href="https://www.paypal.com/paypalme/datastories" rel="nofollow" target="_blank">Paypal</a>. Thanks <h3>Related episodes</h3> <ul><li><a href="https://datastori.es/data-stories-22-nyt-graphics-and-d3-with-mike-bostock-and-shan-carter/" rel="nofollow" target="_blank">NYT Graphics and D3 with Mike Bostock and Shan Carter</a></li><li><a href="https://datastori.es/the-pudding-with-matt-daniels/" rel="nofollow" target="_blank">The Pudding with Matt Daniels</a></li></ul>

163  |  svelte.js for web-based dataviz with Amelia Wattenberger

Miriah Meyer

Hey all, we are back! In this classic episode we go over highlights from the IEEE VIS’20 conference. We cover a broad set of themes with Danielle Szafir from University of Colorado and Miriah Meyer from University of Utah, who helped us explore latest trends in visualization. See the main links and details in the show notes below. There is a lot to explore! Remember: our podcast is listener-supported, please consider making a donation! Using Patreon or Paypal. Links Topic: IEEE VIS conference &lt;http://ieeevis.org/year/2020/welcome&gt; Miriah Meyer &lt;http://www.cs.utah.edu/~miriah/&gt; Danielle &lt;https://danielleszafir.com&gt; PolicyViz episode on IEEE VIS 2020: &lt;https://policyviz.com/podcast/episode-184-ieeevis-recap/&gt; Short paper: Why Shouldn’t All Charts Be Scatter Plots? Beyond Precision-Driven Visualizations: &lt;https://arxiv.org/abs/2008.11310&gt; John Burn-Murdoch’s BELIV workshop keynote: &lt;https://youtu.be/xlN_QUdT6os&gt; Short paper: Designing for Ambiguity: Visual Analytics in Avalanche Forecasting: &lt;https://arxiv.org/abs/2009.02800&gt; Vis Psychology workshop: &lt;https://sites.google.com/view/vispsych/&gt; Barbara Tversky’s keynote: &lt;https://youtu.be/GLiFg3M70Mk?t=1090&gt; Paper: Visual reasoning strategies for effect size judgments and decisions: &lt;https://arxiv.org/abs/2007.14516&gt; Paper: Insight Beyond Numbers: The Impact of Qualitative Factors on Visual Data Analysis: &lt;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9241426&gt; Paper: A Design Space of Vision Science Methods for Visualization Research: &lt;https://arxiv.org/abs/2009.06855&gt; Paper: Communicative Visualizations as a Learning Problem: &lt;https://arxiv.org/abs/2009.07095&gt; Sheelagh Carpendale’s Capstone: &lt;https://youtu.be/XQhBHnPIsRk&gt; Paper: Introducing Layers of Meaning (LoM): A Framework to Reduce Semantic Distance of Visualization In Humanistic Research: &lt;https://projectcornelia.be/uploads/lamqaddam_vis_2020_preprint.pdf&gt;  Paper: Insights From Experiments With Rigor in an EvoBio Design Study: &lt;https://arxiv.org/abs/2008.11564&gt; Paper: Data Comics for Reporting Controlled User Studies in Human-Computer Interaction: &lt;https://osf.io/unmyj&gt; Paper: Uplift: A Tangible and Immersive Tabletop System for Casual Collaborative Visual Analytics: &lt;https://ialab.it.monash.edu/~dwyer/papers/uplift.pdf&gt; Short paper: The Anatomical Edutainer: &lt;https://arxiv.org/abs/2010.09850&gt; Paper: Chemicals in the Creek: designing a situated data physicalization of open government data with the community: &lt;https://arxiv.org/abs/2009.06155&gt; Druid &lt;https://renecutura.eu/pdfs/Druid.pdf&gt; Calliope &lt;https://ieeexplore.ieee.org/abstract/document/9222368&gt; Data GIFs &lt;https://data-gifs.github.io&gt; Related episodes Highlights from IEEE VIS'22 with Tamara Munzner

Hey all, we are back! In this classic episode we go over highlights from the IEEE VIS’20 conference. We cover a broad set of themes with <a href="https://danielleszafir.com/" rel="nofollow" target="_blank">Danielle Szafir</a> from University of Colorado and <a href="https://www.cs.utah.edu/~miriah/" rel="nofollow" target="_blank">Miriah Meyer</a> from University of Utah, who helped us explore latest trends in visualization. See the main links and details in the show notes below. There is a lot to explore! Remember: our podcast is listener-supported, please consider making a donation! Using <a href="https://www.patreon.com/datastories" rel="nofollow" target="_blank">Patreon</a> or <a href="https://www.paypal.com/paypalme/datastories" rel="nofollow" target="_blank">Paypal</a>. Links Topic: IEEE VIS conference &lt;<a href="http://ieeevis.org/year/2020/welcome" rel="nofollow" target="_blank">http://ieeevis.org/year/2020/welcome</a>&gt; Miriah Meyer &lt;<a href="http://www.cs.utah.edu/~miriah/" rel="nofollow" target="_blank">http://www.cs.utah.edu/~miriah/</a>&gt; Danielle &lt;<a href="https://danielleszafir.com" rel="nofollow" target="_blank">https://danielleszafir.com</a>&gt; PolicyViz episode on IEEE VIS 2020: &lt;<a href="https://policyviz.com/podcast/episode-184-ieeevis-recap/" rel="nofollow" target="_blank">https://policyviz.com/podcast/episode-184-ieeevis-recap/</a>&gt; Short paper: Why Shouldn’t All Charts Be Scatter Plots? Beyond Precision-Driven Visualizations: &lt;<a href="https://arxiv.org/abs/2008.11310" rel="nofollow" target="_blank">https://arxiv.org/abs/2008.11310</a>&gt; John Burn-Murdoch’s BELIV workshop keynote: &lt;<a href="https://youtu.be/xlN_QUdT6os" rel="nofollow" target="_blank">https://youtu.be/xlN_QUdT6os</a>&gt; Short paper: Designing for Ambiguity: Visual Analytics in Avalanche Forecasting: &lt;<a href="https://arxiv.org/abs/2009.02800" rel="nofollow" target="_blank">https://arxiv.org/abs/2009.02800</a>&gt; Vis Psychology workshop: &lt;<a href="https://sites.google.com/view/vispsych/" rel="nofollow" target="_blank">https://sites.google.com/view/vispsych/</a>&gt; Barbara Tversky’s keynote: &lt;<a href="https://youtu.be/GLiFg3M70Mk?t=1090" rel="nofollow" target="_blank">https://youtu.be/GLiFg3M70Mk?t=1090</a>&gt; Paper: Visual reasoning strategies for effect size judgments and decisions: &lt;<a href="https://arxiv.org/abs/2007.14516" rel="nofollow" target="_blank">https://arxiv.org/abs/2007.14516</a>&gt; Paper: Insight Beyond Numbers: The Impact of Qualitative Factors on Visual Data Analysis: &lt;<a href="https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9241426" rel="nofollow" target="_blank">https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9241426</a>&gt; Paper: A Design Space of Vision Science Methods for Visualization Research: &lt;<a href="https://arxiv.org/abs/2009.06855" rel="nofollow" target="_blank">https://arxiv.org/abs/2009.06855</a>&gt; Paper: Communicative Visualizations as a Learning Problem: &lt;<a href="https://arxiv.org/abs/2009.07095" rel="nofollow" target="_blank">https://arxiv.org/abs/2009.07095</a>&gt; Sheelagh Carpendale’s Capstone: &lt;<a href="https://youtu.be/XQhBHnPIsRk" rel="nofollow" target="_blank">https://youtu.be/XQhBHnPIsRk</a>&gt; Paper: Introducing Layers of Meaning (LoM): A Framework to Reduce Semantic Distance of Visualization In Humanistic Research: &lt;<a href="https://projectcornelia.be/uploads/lamqaddam_vis_2020_preprint.pdf" rel="nofollow" target="_blank">https://projectcornelia.be/uploads/lamqaddam_vis_2020_preprint.pdf</a>&gt;  Paper: Insights From Experiments With Rigor in an EvoBio Design Study: &lt;<a href="https://arxiv.org/abs/2008.11564" rel="nofollow" target="_blank">https://arxiv.org/abs/2008.11564</a>&gt; Paper: Data Comics for Reporting Controlled User Studies in Human-Computer Interaction: &lt;<a href="https://osf.io/unmyj" rel="nofollow" target="_blank">https://osf.io/unmyj</a>&gt; Paper: Uplift: A Tangible and Immersive Tabletop System for Casual Collaborative Visual Analytics: &lt;<a href="https://ialab.it.monash.edu/~dwyer/papers/uplift.pdf" rel="nofollow" target="_blank">https://ialab.it.monash.edu/~dwyer/papers/uplift.pdf</a>&gt; Short paper: The Anatomical Edutainer: &lt;<a href="https://arxiv.org/abs/2010.09850" rel="nofollow" target="_blank">https://arxiv.org/abs/2010.09850</a>&gt; Paper: Chemicals in the Creek: designing a situated data physicalization of open government data with the community: &lt;<a href="https://arxiv.org/abs/2009.06155" rel="nofollow" target="_blank">https://arxiv.org/abs/2009.06155</a>&gt; Druid &lt;<a href="https://renecutura.eu/pdfs/Druid.pdf" rel="nofollow" target="_blank">https://renecutura.eu/pdfs/Druid.pdf</a>&gt; Calliope &lt;<a href="https://ieeexplore.ieee.org/abstract/document/9222368" rel="nofollow" target="_blank">https://ieeexplore.ieee.org/abstract/document/9222368</a>&gt; Data GIFs &lt;<a href="https://data-gifs.github.io" rel="nofollow" target="_blank">https://data-gifs.github.io</a>&gt; <h3>Related episodes</h3> <ul><li><a href="https://datastori.es/168-highlights-from-ieee-vis22-with-tamara-munzner/" rel="nofollow" target="_blank">Highlights from IEEE VIS'22 with Tamara Munzner</a></li></ul>

162  |  Highlights from IEEE VIS'20 with Miriah Meyer and Danielle Szafir

Shirley Wu

We have renowned data visualizer Shirley Wu with us again (we had her before in episode 98) to talk about a new project she and her team developed to help people reason about the covid19 pandemic at a local community level. The team developed a simulation game that shows you what happens when you make certain sets of decisions over time that may affect the spread of the virus. You can play with others and your goal is to cooperate.Needless to say the tool uses some really interesting visualizations also but this is not the main point. It’s interesting to see the intersection between data visualization, simulation and gaming. With Shirley we talk about how the project started, specific challenges they faced, how it was received, and future developments.Other simulations:    WaPo: Why outbreaks like coronavirus spread exponentially, and how to “flatten the curve” Nicky Case: What Happens Next? Melting Asphalt: Outbreak    https://datastori.es/wp-content/uploads/2020/06/161_Made_by_Headliner.mp4 Related episodes Data Sketches with Nadieh Bremer and Shirley Wu

We have renowned data visualizer <a href="https://sxywu.com/" rel="nofollow" target="_blank">Shirley Wu</a> with us again (we had her before in episode 98) to talk about a new project she and her team developed to help people reason about the covid19 pandemic at a local community level. The team developed a simulation game that shows you what happens when you make certain sets of decisions over time that may affect the spread of the virus. You can play with others and your goal is to cooperate. Needless to say the tool uses some really interesting visualizations also but this is not the main point. It’s interesting to see the intersection between data visualization, simulation and gaming. With Shirley we talk about how the project started, specific challenges they faced, how it was received, and future developments. Other simulations: <ul> <li> <ul> <li>WaPo: <a href="https://www.washingtonpost.com/graphics/2020/world/corona-simulator/" rel="nofollow" target="_blank">Why outbreaks like coronavirus spread exponentially, and how to “flatten the curve”</a></li> <li><a href="https://ncase.me/covid-19/" rel="nofollow" target="_blank">Nicky Case: What Happens Next?</a></li> <li><a href="https://meltingasphalt.com/outbreak/" rel="nofollow" target="_blank">Melting Asphalt: Outbreak</a></li> </ul> </li> </ul> <a href="https://datastori.es/wp-content/uploads/2020/06/161_Made_by_Headliner.mp4" rel="nofollow" target="_blank">https://datastori.es/wp-content/uploads/2020/06/161_Made_by_Headliner.mp4</a> <h3>Related episodes</h3> <ul><li><a href="https://datastori.es/98-data-sketches-with-nadieh-bremer-and-shirley-wu/" rel="nofollow" target="_blank">Data Sketches with Nadieh Bremer and Shirley Wu</a></li></ul>

161  |  People of the Pandemic with Shirley Wu

A podcast on data and how it affects our lives — with Enrico Bertini and Moritz Stefaner

Useful

Great guests, thoughtful discussions, and nerdy fun.

Insightful conversations with industry pros

Data Stories

Here we go with another great episode. This time more on the data side. We have Kate Crawford, Principal Researcher at Microsoft Research, on the show talking about the other face of big data. That is, after all the excitement, hype, and buzz, she is the one who is asking the tough questions: Is more data always better? Is there any objective truth in it? Is big data really making us smarter? Papers and articles from Kate  Boyd, D. and Crawford, K. 2012 ‘Critical Questions for Big Data‘, Information, Communication and Society, Volume 15, no 5, pp 662-679. Crawford, K. and Schultz, J. 2014 ‘Big Data and Due Process: Toward a Framework to Redress Predictive Privacy Harms‘, Boston College Law Review, Vol. 55, No. 1. “The Hidden Biases in Big Data” (Harvard Business Review) “Think Again: Big Data” (Foreign Policy)  Some of Kate’s Talks  The Raw and the Cooked: The Mythologies of Big Data Strata 2013: Kate Crawford, “Algorithmic Illusions: Hidden Biases of Big Data“  Links  Book: Objectivity by Lorraine J. Daston (How recent is it?) Paper: Private traits and attributes are predictable from digital records of human behavior (how big data and algorithms can discriminate). Paper: Unique in the Crowd: The privacy bounds of human mobility (only 4 data points are needed to identify a person) When Google got flu wrong (Google failing to predict flu) The End of Theory: “The Data Deluge Makes the Scientific Method Obsolete” (Chris Anderson on the end of theory, correlation vs. causation, etc.) How a Map Is Like an Op-Ed (“Maps are arguments, just like a piece of written journalism is an argument.”) Mislove, Alan, et al. “Understanding the Demographics of Twitter Users.” ICWSM. 2011.  — Enjoy it, there’s lots of food for thoughts here!			Related episodes Data Ethics and Privacy with Eleanor SaittaCalling Bullshit with Carl Bergstrom and Jevin WestVisualization and Statistics with Andrew Gelman and Jessica Hullman

Here we go with another great episode. This time more on the data side. We have <a href="http://www.katecrawford.net/" rel="nofollow" target="_blank">Kate Crawford</a>, Principal Researcher at Microsoft Research, on the show talking about the other face of big data. That is, after all the excitement, hype, and buzz, she is the one who is asking the tough questions: Is more data always better? Is there any objective truth in it? Is big data really making us smarter? Papers and articles from Kate <ul> <li>Boyd, D. and Crawford, K. 2012 ‘<a href="http://www.tandfonline.com/doi/full/10.1080/1369118X.2012.678878" rel="nofollow" target="_blank">Critical Questions for Big Data</a>‘, Information, Communication and Society, Volume 15, no 5, pp 662-679.</li> <li>Crawford, K. and Schultz, J. 2014 ‘<a href="http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2325784&amp;download=yes" rel="nofollow" target="_blank">Big Data and Due Process: Toward a Framework to Redress Predictive Privacy Harms</a>‘, Boston College Law Review, Vol. 55, No. 1.</li> <li><a href="http://blogs.hbr.org/2013/04/the-hidden-biases-in-big-data/" rel="nofollow" target="_blank">“The Hidden Biases in Big Data”</a> (Harvard Business Review)</li> <li><a href="http://www.foreignpolicy.com/articles/2013/05/09/think_again_big_data" rel="nofollow" target="_blank">“Think Again: Big Data”</a> (Foreign Policy)</li> </ul> Some of Kate’s Talks <ul> <li><a href="https://www.youtube.com/watch?v=h_WScJu40mU" rel="nofollow" target="_blank">The Raw and the Cooked: The Mythologies of Big Data</a></li> <li>Strata 2013: Kate Crawford, “<a href="http://www.youtube.com/watch?v=irP5RCdpilc" rel="nofollow" target="_blank">Algorithmic Illusions: Hidden Biases of Big Data</a>“</li> </ul> Links <ul> <li>Book: <a href="http://www.amazon.com/Objectivity-Lorraine-J-Daston/dp/189095179X" rel="nofollow" target="_blank">Objectivity</a> by Lorraine J. Daston (How recent is it?)</li> <li>Paper: <a href="http://www.pnas.org/content/early/2013/03/06/1218772110.full.pdf" rel="nofollow" target="_blank">Private traits and attributes are predictable from digital records of human behavior</a> (how big data and algorithms can discriminate).</li> <li>Paper: <a href="http://www.nature.com/srep/2013/130325/srep01376/full/srep01376.html" rel="nofollow" target="_blank">Unique in the Crowd: The privacy bounds of human mobility</a> (only 4 data points are needed to identify a person)</li> <li><a href="http://www.nature.com/news/when-google-got-flu-wrong-1.12413" rel="nofollow" target="_blank">When Google got flu wrong</a> (Google failing to predict flu)</li> <li><a href="http://www.wired.com/science/discoveries/magazine/16-07/pb_theory" rel="nofollow" target="_blank">The End of Theory: “The Data Deluge Makes the Scientific Method Obsolete”</a> (Chris Anderson on the end of theory, correlation vs. causation, etc.)</li> <li><a href="http://www.theatlanticcities.com/technology/2013/04/how-map-op-ed/5143/" rel="nofollow" target="_blank">How a Map Is Like an Op-Ed</a> (“Maps are arguments, just like a piece of written journalism is an argument.”)</li> <li>Mislove, Alan, et al. “<a href="http://www.aaai.org/ocs/index.php/ICWSM/ICWSM11/paper/viewFile/2816/3234" rel="nofollow" target="_blank">Understanding the Demographics of Twitter Users.</a>” ICWSM. 2011.</li> </ul> — Enjoy it, there’s lots of food for thoughts here! 			<h3>Related episodes</h3> <ul><li><a href="https://datastori.es/74-data-ethics-and-privacy-with-eleanor-saitta/" rel="nofollow" target="_blank">Data Ethics and Privacy with Eleanor Saitta</a></li><li><a href="https://datastori.es/97-calling-bullshit-with-carl-bergstrom-and-jevin-west/" rel="nofollow" target="_blank">Calling Bullshit with Carl Bergstrom and Jevin West</a></li><li><a href="https://datastori.es/167-visualization-and-statistics-with-andrew-gelman-and-jessica-hullman/" rel="nofollow" target="_blank">Visualization and Statistics with Andrew Gelman and Jessica Hullman</a></li></ul>

027  |  Big Data Skepticism w/ Kate Crawford

“I’d give two of my left fingers for this data” – Amanda Cox on the show  We have the great Amanda Cox from the New York Times on the show this time! Amanda is a graphic editor at NYT and she is behind many of the amazing data graphics that the New York Times has produced in recent years. In the show we talk about her background in statistics and how she ended up at the Times. We discuss how she uses R software to collect, analyze, and visualize data, and her thoughts on other tools. We also talk about how data graphics are produced at NYT, with lots of funny stories. Don’t miss the parts about the “what, where, when” of data and the “net joy” concept. Lots a data wisdom in this show! — This episode is sponsored by Tableau Software,  helping people connect to any kind of data, and visualize it on the fly – You can download a free trial at http://tableau.com/datastories – check the new Tableau 9! — LINKS  Hadley Wickham – http://had.co.nz/ R Studio – http://shiny.rstudio.com/ Jake Barton: Local Projects – http://localprojects.net/about/ NYT Project: The Best and Worst Places to Grow Up: How Your Area Compares NYT Project: You Draw It: How Family Income Predicts Children’s College Chances Amanda and Kevin’s NYU Data Journalism Course Quadrigram – http://www.quadrigram.com/ (tool for data-driven web sites) Jeff Heer and his IDL Lab at UW – http://idl.cs.washington.edu/ FiveThirtyEight – http://fivethirtyeight.com/ The Upshot – http://www.nytimes.com/upshot/?_r=0 

“I’d give two of my left fingers for this data” – Amanda Cox on the show We have the great Amanda Cox from the New York Times on the show this time! Amanda is a graphic editor at NYT and she is behind many of the amazing data graphics that the New York Times has produced in recent years. In the show we talk about her background in statistics and how she ended up at the Times. We discuss how she uses R software to collect, analyze, and visualize data, and her thoughts on other tools. We also talk about how data graphics are produced at NYT, with lots of funny stories. Don’t miss the parts about the “what, where, when” of data and the “net joy” concept. Lots a data wisdom in this show! — This episode is sponsored by <a href="http://tableau.com/datastories" rel="nofollow" target="_blank">Tableau Software</a>,  helping people connect to any kind of data, and visualize it on the fly – You can download a free trial at <a href="http://tableau.com/datastories" rel="nofollow" target="_blank">http://tableau.com/datastories</a> – check the new Tableau 9! — LINKS <ul> <li>Hadley Wickham – <a href="http://had.co.nz/" rel="nofollow" target="_blank">http://had.co.nz/</a></li> <li>R Studio – <a href="http://shiny.rstudio.com/" rel="nofollow" target="_blank">http://shiny.rstudio.com/</a></li> <li>Jake Barton: Local Projects – <a href="http://localprojects.net/about/" rel="nofollow" target="_blank">http://localprojects.net/about/</a></li> <li>NYT Project: <a href="http://www.nytimes.com/interactive/2015/05/03/upshot/the-best-and-worst-places-to-grow-up-how-your-area-compares.html?_r=0&amp;abt=0002&amp;abg=1" rel="nofollow" target="_blank">The Best and Worst Places to Grow Up: How Your Area Compares</a></li> <li>NYT Project: <a href="http://www.nytimes.com/interactive/2015/05/28/upshot/you-draw-it-how-family-income-affects-childrens-college-chances.html?abt=0002&amp;abg=1" rel="nofollow" target="_blank">You Draw It: How Family Income Predicts Children’s College Chances</a></li> <li>Amanda and Kevin’s <a href="http://kpq.github.io/nyu-data-journalism-2014/" rel="nofollow" target="_blank">NYU Data Journalism Course</a></li> <li>Quadrigram – <a href="http://www.quadrigram.com/" rel="nofollow" target="_blank">http://www.quadrigram.com/</a> (tool for data-driven web sites)</li> <li>Jeff Heer and his IDL Lab at UW – <a href="http://idl.cs.washington.edu/" rel="nofollow" target="_blank">http://idl.cs.washington.edu/</a></li> <li>FiveThirtyEight – <a href="http://fivethirtyeight.com/" rel="nofollow" target="_blank">http://fivethirtyeight.com/</a></li> <li>The Upshot – <a href="http://www.nytimes.com/upshot/?_r=0" rel="nofollow" target="_blank">http://www.nytimes.com/upshot/?_r=0</a></li> </ul>

56 | Amanda Cox on Working With R, NYT Projects, Favorite Data

Petra Isenberg

Hi Folks! We are back after a relaxing summer with a brand new episode! We have Petra Isenberg, from the Aviz team at INRIA (we’ve had other guests from the same lab in the past) to talk about visualization on non-standard devices and environments. Yes, stuff like display walls, surfaces, tabletops, and people collaborating around them. It feels like the future is here and there’s a ton of potentially interesting applications for visualization! Petra gives us hints about what works and what does not work, what the research says, what has been tried already, and what needs to be explored, etc. She also gives practical recommendations at the end about how to start doing visualization on these devices. Really cool stuff! Take care, Enrico &amp; Mo. — Chapters  00:00 Back from summer break 02:41 Our guest today: Petra Isenberg 05:59 Moving beyond the desktop 11:55 New challenges in collaborative settings 22:25 Interactions with very large screens 38:14 Practical use and how to get started 48:53 More resources  — Links and papers:  Petra’s Web Site: http://petra.isenberg.cc/ Surface work from Moritz  http://mace-project.eu/maeve/ http://max-planck-research-networks.net   Statusboard Bezerianos, Anastasia, and Petra Isenberg. “Perception of visual variables on tiled wall-sized displays for information visualization applications.“Visualization and Computer Graphics, IEEE Transactions on 18.12 (2012): 2516-2525. Scott, Stacey D., et al. “Territoriality in collaborative tabletop workspaces.” Proceedings of the 2004 ACM conference on Computer supported cooperative work. ACM, 2004. APA  Resource list from Petra Research links:  Papercollection: Literature review including papers at the intersection of visualization+interactive surfaces (research article to appear) Book: Tabletops – Horizontal Interactive Surfaces Conference on Interactive Tabletops and Surfaces  Technology links:  Interactive Multimedia Technology (blog by lynnmarentette) Multitouch google group (managed by Johannes Schöning), email Johannes to be added to the mailing list  Software frameworks/libraries for developing vis on surfaces:  Most Pixels Ever (Processing for very large wall displays – I forgot to mention this one during the podcast) kivy (Python framework for developing multi-touch applications) libavg (maintained by Ulrich von Zadow who has worked on several visualization + interactive surface installations) ZVTM (Java toolkit for developing ZUIs, includes possibilities to run visualizations on a cluster) Microsoft Surface SDK (for mobile check out iOS and Android SDKs) 

Hi Folks! We are back after a relaxing summer with a brand new episode! We have <a href="http://petra.isenberg.cc/" rel="nofollow" target="_blank">Petra Isenberg</a>, from the <a href="http://www.aviz.fr/" rel="nofollow" target="_blank">Aviz</a> team at INRIA (we’ve had <a href="http://datastori.es/episode17-data-sculptures/" rel="nofollow" target="_blank">other guests from the same lab</a> in the past) to talk about visualization on non-standard devices and environments. Yes, stuff like display walls, surfaces, tabletops, and people collaborating around them. It feels like the future is here and there’s a ton of potentially interesting applications for visualization! Petra gives us hints about what works and what does not work, what the research says, what has been tried already, and what needs to be explored, etc. She also gives practical recommendations at the end about how to start doing visualization on these devices. Really cool stuff! Take care, Enrico &amp; Mo. — Chapters <ul> <li>00:00 Back from summer break</li> <li>02:41 Our guest today: Petra Isenberg</li> <li>05:59 Moving beyond the desktop</li> <li>11:55 New challenges in collaborative settings</li> <li>22:25 Interactions with very large screens</li> <li>38:14 Practical use and how to get started</li> <li>48:53 More resources</li> </ul> — Links and papers: <ul> <li>Petra’s Web Site: <a href="http://petra.isenberg.cc/" rel="nofollow" target="_blank">http://petra.isenberg.cc/</a></li> <li>Surface work from Moritz <ul> <li><a href="http://mace-project.eu/maeve/" rel="nofollow" target="_blank">http://mace-project.eu/maeve/</a></li> <li><a href="http://max-planck-research-networks.net" rel="nofollow" target="_blank">http://max-planck-research-networks.net</a></li> </ul> </li> <li><a href="http://panic.com/statusboard/" rel="nofollow" target="_blank">Statusboard</a></li> <li>Bezerianos, Anastasia, and Petra Isenberg. “<a href="http://hal.inria.fr/docs/00/71/92/03/PDF/WallEncodings-article.pdf" rel="nofollow" target="_blank">Perception of visual variables on tiled wall-sized displays for information visualization applications.</a>“Visualization and Computer Graphics, IEEE Transactions on 18.12 (2012): 2516-2525.</li> <li>Scott, Stacey D., et al. “<a href="http://pages.cpsc.ucalgary.ca/~sheelagh/wiki/uploads/Main/Publications/scott_cscw2004.pdf" rel="nofollow" target="_blank">Territoriality in collaborative tabletop workspaces.</a>” Proceedings of the 2004 ACM conference on Computer supported cooperative work. ACM, 2004. APA</li> </ul> Resource list from Petra Research links: <ul> <li>Papercollection: <a href="https://docs.google.com/spreadsheet/ccc?key=0AmuGsrlucvWQdGtzVjZlWG5waDMyUkRrUVZFM0txTkE&amp;usp=sharing" rel="nofollow" target="_blank">Literature review including papers at the intersection of visualization+interactive surfaces</a> (research article to appear)</li> <li>Book: <a href="http://www.springer.com/computer/hci/book/978-1-84996-112-7" rel="nofollow" target="_blank">Tabletops – Horizontal Interactive Surfaces</a></li> <li><a href="http://its2013.org/" rel="nofollow" target="_blank">Conference on Interactive Tabletops and Surfaces</a></li> </ul> Technology links: <ul> <li><a href="http://interactivemultimediatechnology.blogspot.fr/" rel="nofollow" target="_blank">Interactive Multimedia Technology</a> (blog by <a href="https://twitter.com/lynnmarentette" rel="nofollow" target="_blank">lynnmarentette</a>)</li> <li><a href="https://groups.google.com/forum/#!forum/multi-touch" rel="nofollow" target="_blank">Multitouch google group</a> (managed by Johannes Schöning), email <a href="http://www.johannesschoening.de/website/Johannes_Schoning.html" rel="nofollow" target="_blank">Johannes</a> to be added to the mailing list</li> </ul> Software frameworks/libraries for developing vis on surfaces: <ul> <li><a href="https://github.com/shiffman/Most-Pixels-Ever-Processing" rel="nofollow" target="_blank">Most Pixels Ever</a> (Processing for very large wall displays – I forgot to mention this one during the podcast)</li> <li><a href="http://kivy.org/#home" rel="nofollow" target="_blank">kivy</a> (Python framework for developing multi-touch applications)</li> <li><a href="https://www.libavg.de/site/projects/libavg/wiki/Showcase" rel="nofollow" target="_blank">libavg</a> (maintained by Ulrich von Zadow who has worked on several visualization + interactive surface installations)</li> <li><a href="http://zvtm.sourceforge.net/" rel="nofollow" target="_blank">ZVTM</a> (Java toolkit for developing ZUIs, includes possibilities to run visualizations on a cluster)</li> <li><a href="http://msdn.microsoft.com/en-us/library/ff727815.aspx" rel="nofollow" target="_blank">Microsoft Surface SDK</a></li> <li>(for mobile check out iOS and Android SDKs)</li> </ul>

026  |  Visualization Beyond the Desktop w/ Petra Isenberg

Hadley Wickham

We have Hadley Wickham on the show, Chief Scientist at RStudio and Adjunct Professor of Statistics at Rice University and the University of Auckland. Hadley created a number of hugely popular libraries for the R language, including ggplot2, which is used throughout the world to analyze and present data. On the show we talk about his creative process to develop ggplot2, its growing popularity, other libraries he has built in the R ecosystem, and strategies for creating popular software for data analysis and visualization. Enjoy listening to Hadley Wickham, or read the transcript from our interview here! Data Stories is brought to you by Qlik, which allows you to explore the hidden relationships within your data that lead to meaningful insights. Take part in the Open Data Challenge for a chance to win $10,000 for an app created with Qlik Sense! LINKS  Project Ukko: http://www.project-ukko.net/ Hadley Wickham: http://hadley.nz/ | https://github.com/hadley/ ggplot2: http://ggplot2.org/ ggplot extensions: http://ggplot2-exts.github.io Hadley’s R packages for data analysis (ggplot2, plyr, reshape2) R: https://www.r-project.org/ tidyr: http://blog.rstudio.org/2014/07/22/introducing-tidyr/ Visualizing travel data with TripIt: https://www.tripit.com/ RStudio Shiny (interactive web graphics with R): http://shiny.rstudio.com/ Functional Reactive Programming: https://en.wikipedia.org/wiki/Functional_reactive_programming Beautiful data visualization done with ggplot2: http://spatial.ly/2014/09/london-information-capital/ Mike LaCour’s scandalous graphs (clearly done with ggplot2): http://science.sciencemag.org/content/346/6215/1366.full Wilkinson’s The Grammar of Graphics: http://www.amazon.com/The-Grammar-Graphics-Statistics-Computing/dp/0387245448 Tableau: http://www.tableau.com/ d3.js: http://d3js.org/ ggvis and shiny: http://ggvis.rstudio.com/ | http://shiny.rstudio.com/ R tutorials: https://www.datacamp.com/ https://www.coursera.org/learn/r-programming http://swirlstats.com/  

We have <a href="http://hadley.nz/" rel="nofollow" target="_blank">Hadley Wickham</a> on the show, Chief Scientist at <a href="https://www.rstudio.com/" rel="nofollow" target="_blank">RStudio</a> and Adjunct Professor of Statistics at Rice University and the University of Auckland. Hadley created a number of hugely popular libraries for the R language, including <a href="http://ggplot2.org/" rel="nofollow" target="_blank">ggplot2</a>, which is used throughout the world to analyze and present data. On the show we talk about his creative process to develop <a href="http://ggplot2.org/" rel="nofollow" target="_blank">ggplot2,</a> its growing popularity, other libraries he has built in the R ecosystem, and strategies for creating popular software for data analysis and visualization. Enjoy listening to Hadley Wickham, or read the transcript from our interview <a href="http://bit.ly/1QRC49p" rel="nofollow" target="_blank">here</a>! Data Stories is brought to you by <a href="http://www.qlik.de/datastories" rel="nofollow" target="_blank">Qlik</a>, which allows you to explore the hidden relationships within your data that lead to meaningful insights. Take part in the <a href="http://global.qlik.com/us/blog/posts/evan-siff/open-data-challenge" rel="nofollow" target="_blank">Open Data Challenge</a> for a chance to win $10,000 for an app created with Qlik Sense! LINKS <ul> <li>Project Ukko: <a href="http://www.project-ukko.net/" rel="nofollow" target="_blank">http://www.project-ukko.net/</a></li> <li>Hadley Wickham: <a href="http://hadley.nz/" rel="nofollow" target="_blank">http://hadley.nz/</a> | <a href="https://github.com/hadley/" rel="nofollow" target="_blank">https://github.com/hadley/</a></li> <li>ggplot2: <a href="http://ggplot2.org/" rel="nofollow" target="_blank">http://ggplot2.org/</a></li> <li>ggplot extensions: <a href="http://ggplot2-exts.github.io" rel="nofollow" target="_blank">http://ggplot2-exts.github.io</a></li> <li>Hadley’s R packages for data analysis (<a href="http://ggplot2.org/" rel="nofollow" target="_blank">ggplot2</a>, <a href="http://cran.r-project.org/web/packages/plyr/index.html" rel="nofollow" target="_blank">plyr</a>, <a href="http://cran.r-project.org/web/packages/reshape2/index.html" rel="nofollow" target="_blank">reshape2</a>)</li> <li>R: <a href="https://www.r-project.org/" rel="nofollow" target="_blank">https://www.r-project.org/</a></li> <li>tidyr: <a href="http://blog.rstudio.org/2014/07/22/introducing-tidyr/" rel="nofollow" target="_blank">http://blog.rstudio.org/2014/07/22/introducing-tidyr/</a></li> <li>Visualizing travel data with TripIt: <a href="https://www.tripit.com/" rel="nofollow" target="_blank">https://www.tripit.com/</a></li> <li>RStudio Shiny (interactive web graphics with R): <a href="http://shiny.rstudio.com/" rel="nofollow" target="_blank">http://shiny.rstudio.com/</a></li> <li>Functional Reactive Programming: <a href="https://en.wikipedia.org/wiki/Functional_reactive_programming" rel="nofollow" target="_blank">https://en.wikipedia.org/wiki/Functional_reactive_programming</a></li> <li>Beautiful data visualization done with ggplot2: <a href="http://spatial.ly/2014/09/london-information-capital/" rel="nofollow" target="_blank">http://spatial.ly/2014/09/london-information-capital/</a></li> <li>Mike LaCour’s scandalous graphs (clearly done with ggplot2): <a href="http://science.sciencemag.org/content/346/6215/1366.full" rel="nofollow" target="_blank">http://science.sciencemag.org/content/346/6215/1366.full</a></li> <li>Wilkinson’s The Grammar of Graphics: <a href="http://www.amazon.com/The-Grammar-Graphics-Statistics-Computing/dp/0387245448" rel="nofollow" target="_blank">http://www.amazon.com/The-Grammar-Graphics-Statistics-Computing/dp/0387245448</a></li> <li>Tableau: <a href="http://www.tableau.com/" rel="nofollow" target="_blank">http://www.tableau.com/</a></li> <li>d3.js: <a href="http://d3js.org/" rel="nofollow" target="_blank">http://d3js.org/</a></li> <li>ggvis and shiny: <a href="http://ggvis.rstudio.com/" rel="nofollow" target="_blank">http://ggvis.rstudio.com/</a> | <a href="http://shiny.rstudio.com/" rel="nofollow" target="_blank">http://shiny.rstudio.com/</a></li> <li>R tutorials: <ul> <li><a href="https://www.datacamp.com/" rel="nofollow" target="_blank">https://www.datacamp.com/</a></li> <li><a href="https://www.coursera.org/learn/r-programming" rel="nofollow" target="_blank">https://www.coursera.org/learn/r-programming</a></li> <li><a href="http://swirlstats.com/" rel="nofollow" target="_blank">http://swirlstats.com/</a></li> </ul> </li></ul>

67 | ggplot2, R, and data toolmaking with Hadley Wickham

Jeremy Boy

Helen Kennedy

Andy Kirk

We have a nice trio on the show for this episode: Jeremy Boy is a postdoctoral researcher at NYU School of Engineering, Helen Kennedy is Professor of Digital Society at University of Sheffield, and Andy Kirk is our beloved editor at visualisingdata.com.  We talk with these three experts about Data Visualization Literacy — that is, how people read data visualizations. We ask, how do we measure literacy? How do we improve it? And how do we even define literacy when we’re asking our viewers to read images? Jeremy talks about his research on methods to measure visualization literacy, while Helen and Andy discuss their Seeing Data project, which studies how people read visualizations. If you prefer reading to listening, you can find the transcript of our episode here. Enjoy the show!  Data Stories is brought to you by Qlik, which allows you to explore the hidden relationships within your data that lead to meaningful insights. Let your instincts lead the way to create personalized visualizations and dynamic dashboards with Qlik Sense. Download Qlik Sense for free at www.qlik.de/datastories. This week, the Qlik blog features a great post on maps and the data literacy required to read them called “Here Be Dragons.” LINKS  Andy Kirk: visualisingdata.com Helen Kennedy: http://www.sheffield.ac.uk/socstudies/staff/staff-profiles/helen-kennedy Jeremy Boy: http://jyby.eu/ Seeing Data Project: http://seeingdata.org    Seeing Data Results:  http://www.visualisingdata.com/2015/10/views-from-seeing-data-research-part-1/ http://www.visualisingdata.com/2015/12/views-from-seeing-data-research-part-2/ http://www.visualisingdata.com/2016/02/views-from-seeing-data-research-part-3/ Three funded PhD Studentships at University of Sheffield: http://www.sheffield.ac.uk/socstudies/prospt/ppr/scholarships/datanetwork    Some research papers on data visualization literacy:  Boy, Jeremy, et al. “A principled way of assessing visualization literacy.“Visualization and Computer Graphics, IEEE Transactions on 20.12 (2014): 1963-1972. Lee, Sukwon, et al. “How do People Make Sense of Unfamiliar Visualizations?: A Grounded Model of Novice’s Information Visualization Sensemaking.” Visualization and Computer Graphics, IEEE Transactions on 22.1 (2016): 499-508. Börner, Katy, et al. “Investigating aspects of data visualization literacy using 20 information visualizations and 273 science museum visitors.” Information Visualization (2015): 1473871615594652.    Some other interesting projects:  Vis Literacy Workshop (at InfoVis): http://visualizationliteracy.org/workshop Vis Literacy at Purdue: https://engineering.purdue.edu/HIVELab/wiki/pmwiki.php/VisualizationLiteracy Vis Literacy Workshop (at EuroVis): https://www.kth.se/profile/178785/page/eurovis-2014-workshop-towards-visualiza/  Related episodes Information+ Conference ReviewVisualization Literacy in Elementary School with Basak Alper and Nathalie RicheData Is Personal with Evan Peck

We have a nice trio on the show for this episode: <a href="http://jyby.eu/" rel="nofollow" target="_blank">Jeremy Boy</a> is a postdoctoral researcher at NYU School of Engineering, <a href="http://www.sheffield.ac.uk/socstudies/staff/staff-profiles/helen-kennedy" rel="nofollow" target="_blank">Helen Kennedy</a> is Professor of Digital Society at University of Sheffield, and <a href="http://www.visualisingdata.com/" rel="nofollow" target="_blank">Andy Kirk</a> is our beloved editor at <a href="http://www.visualisingdata.com/" rel="nofollow" target="_blank">visualisingdata.com</a>. We talk with these three experts about Data Visualization Literacy — that is, how people read data visualizations. We ask, how do we measure literacy? How do we improve it? And how do we even define literacy when we’re asking our viewers to read images? Jeremy talks about his research on methods to measure visualization literacy, while Helen and Andy discuss their <a href="http://seeingdata.org/" rel="nofollow" target="_blank">Seeing Data</a> project, which studies how people read visualizations. If you prefer reading to listening, you can find the transcript of our episode <a href="https://docs.google.com/document/d/1GUPWgZW_8ppm1iHwNxM2xgrYeHa01cDG3JoWjszINz0/edit?usp=sharing" rel="nofollow" target="_blank">here</a>. Enjoy the show! Data Stories is brought to you by Qlik, which allows you to explore the hidden relationships within your data that lead to meaningful insights. Let your instincts lead the way to create personalized visualizations and dynamic dashboards with Qlik Sense. Download Qlik Sense for free at <a href="http://www.qlik.de/datastories" rel="noopener noreferrer nofollow" target="_blank">www.qlik.de/datastories</a>. This week, the Qlik blog features a great post on maps and the data literacy required to read them called “<a href="http://global.qlik.com/us/blog/posts/murray-grigo-mcmahon/here-be-dragons" rel="nofollow" target="_blank">Here Be Dragons</a>.” LINKS <ul> <li>Andy Kirk: <a href="http://www.visualisingdata.com/" rel="nofollow" target="_blank">visualisingdata.com</a></li> <li>Helen Kennedy: <a href="http://www.sheffield.ac.uk/socstudies/staff/staff-profiles/helen-kennedy" rel="nofollow" target="_blank">http://www.sheffield.ac.uk/socstudies/staff/staff-profiles/helen-kennedy</a></li> <li>Jeremy Boy: <a href="http://jyby.eu/" rel="nofollow" target="_blank">http://jyby.eu/</a></li> <li>Seeing Data Project: <a href="http://seeingdata.org" rel="nofollow" target="_blank">http://seeingdata.org</a></li> </ul> Seeing Data Results: <ul> <li><a href="http://www.visualisingdata.com/2015/10/views-from-seeing-data-research-part-1/" rel="nofollow" target="_blank">http://www.visualisingdata.com/2015/10/views-from-seeing-data-research-part-1/</a></li> <li><a href="http://www.visualisingdata.com/2015/12/views-from-seeing-data-research-part-2/" rel="nofollow" target="_blank">http://www.visualisingdata.com/2015/12/views-from-seeing-data-research-part-2/</a></li> <li><a href="http://www.visualisingdata.com/2016/02/views-from-seeing-data-research-part-3/" rel="nofollow" target="_blank">http://www.visualisingdata.com/2016/02/views-from-seeing-data-research-part-3/</a></li> <li>Three funded PhD Studentships at University of Sheffield: <a href="http://www.sheffield.ac.uk/socstudies/prospt/ppr/scholarships/datanetwork" rel="nofollow" target="_blank">http://www.sheffield.ac.uk/socstudies/prospt/ppr/scholarships/datanetwork</a></li> </ul> Some research papers on data visualization literacy: <ul> <li>Boy, Jeremy, et al. “<a href="https://hal.inria.fr/hal-01027582/document" rel="nofollow" target="_blank">A principled way of assessing visualization literacy.</a>“Visualization and Computer Graphics, IEEE Transactions on 20.12 (2014): 1963-1972.</li> <li>Lee, Sukwon, et al. “How do People Make Sense of Unfamiliar Visualizations?: A Grounded Model of Novice’s Information Visualization Sensemaking.” Visualization and Computer Graphics, IEEE Transactions on 22.1 (2016): 499-508.</li> <li>Börner, Katy, et al. “<a href="http://cns.slis.indiana.edu/docs/publications/2015-borner-investigating.pdf" rel="nofollow" target="_blank">Investigating aspects of data visualization literacy using 20 information visualizations and 273 science museum visitors.</a>” Information Visualization (2015): 1473871615594652.</li> </ul> Some other interesting projects: <ul> <li>Vis Literacy Workshop (at InfoVis): <a href="http://visualizationliteracy.org/workshop" rel="nofollow" target="_blank">http://visualizationliteracy.org/workshop</a></li> <li>Vis Literacy at Purdue: <a href="https://engineering.purdue.edu/HIVELab/wiki/pmwiki.php/VisualizationLiteracy" rel="nofollow" target="_blank">https://engineering.purdue.edu/HIVELab/wiki/pmwiki.php/VisualizationLiteracy</a></li> <li>Vis Literacy Workshop (at EuroVis): <a href="https://www.kth.se/profile/178785/page/eurovis-2014-workshop-towards-visualiza/" rel="nofollow" target="_blank">https://www.kth.se/profile/178785/page/eurovis-2014-workshop-towards-visualiza/</a></li> </ul> <h3>Related episodes</h3> <ul><li><a href="https://datastori.es/82-information-plus-review/" rel="nofollow" target="_blank">Information+ Conference Review</a></li><li><a href="https://datastori.es/104-visualization-literacy-in-elementary-school-with-basak-alper-and-nathalie-riche/" rel="nofollow" target="_blank">Visualization Literacy in Elementary School with Basak Alper and Nathalie Riche</a></li><li><a href="https://datastori.es/data-is-personal-with-evan-peck/" rel="nofollow" target="_blank">Data Is Personal with Evan Peck</a></li></ul>

069  |  Data Visualization Literacy with Jeremy Boy, Helen Kennedy and Andy Kirk

David Sheldon-Hicks

In this episode we talk about “future interfaces” with David Sheldon-Hicks: interfaces that are developed in futuristic movies. David is the founder and creative director of Territory Studio. They are the people behind the screen design of a lot of iconic movies such as The Martian, Blade Runner and Ex Machina. On the show, we talk about what it takes to develop this kind of interfaces and how they interact with film directors. We also talk about interaction paradigms and classic movies from the past. David also provides a few tips on how to get started in this space. Note: they are hiring! Enjoy the show! [Our podcast is fully listener-supported. That’s why you don’t have to listen to ads! Please consider becoming a supporter on Patreon or sending us a one-time donation through Paypal. And thank you!] Films in which Territory Studio was involved (in the order of their mentioning): The Martian (2015, Ridley Scott) Guardians of the Galaxy (2014, James Gunn) Blade Runner 2049 (2017, Denis Villeneuve) Ex Machina (2015, Alex Garland) James Bond – No Time To Die (forthcoming 2020, Cary Fukunaga) Prometheus (2012, Ridley Scott) Legends of the past: Minority Report (2002, Steven Spielberg) War Games (1983, John Badham) Star Wars Episode IV: A New Hope (1977, George Lucas)    https://datastori.es/wp-content/uploads/2019/12/151_video.mp4

In this episode we talk about “future interfaces” with David Sheldon-Hicks: interfaces that are developed in futuristic movies. David is the founder and creative director of Territory Studio. They are the people behind the screen design of a lot of iconic movies such as The Martian, Blade Runner and Ex Machina. On the show, we talk about what it takes to develop this kind of interfaces and how they interact with film directors. We also talk about interaction paradigms and classic movies from the past. David also provides a few tips on how to get started in this space. Note: they are hiring! Enjoy the show! [Our podcast is fully listener-supported. That’s why you don’t have to listen to ads! Please consider <a href="https://www.patreon.com/datastories" rel="nofollow" target="_blank">becoming a supporter on Patreon</a> or sending us a one-time donation through <a href="https://www.paypal.me/datastories" rel="nofollow" target="_blank">Paypal</a>. And thank you!] Films in which Territory Studio was involved (in the order of their mentioning): The Martian (2015, Ridley Scott) Guardians of the Galaxy (2014, James Gunn) Blade Runner 2049 (2017, Denis Villeneuve) Ex Machina (2015, Alex Garland) James Bond – No Time To Die (forthcoming 2020, Cary Fukunaga) Prometheus (2012, Ridley Scott) Legends of the past: Minority Report (2002, Steven Spielberg) War Games (1983, John Badham) Star Wars Episode IV: A New Hope (1977, George Lucas) <a href="https://datastori.es/wp-content/uploads/2019/12/151_video.mp4" rel="nofollow" target="_blank">https://datastori.es/wp-content/uploads/2019/12/151_video.mp4</a>

151  |  Future Data Interfaces with David Sheldon-Hicks

Krist Wongsuphasawat

[Help us run the show by supporting us on Patreon!] This week we have Krist Wongsuphasawat on Data Stories to talk about visualization projects at Twitter. Krist has a Ph.D. in Computer Science from the University of Maryland, where he worked with Ben Shneiderman. Most recently, he has been a Data Visualization Scientist at Twitter since 2012. On the show, Krist describes the kinds of projects that the visualization team at Twitter develops. He also walks us through a few of the most popular of these projects, including their famous visualization of Game of Thrones. Also, don’t miss Krist’s masterpiece post “How I carefully crafted a truly terrible data visualization”  Enjoy the show! Data Stories is brought to you by Qlik. Are you missing out on meaningful relationships hidden in your data? Unlock the whole story with Qlik Sense through personalized visualizations and dynamic dashboards which you can download for free at qlik.de/datastories.  Links  Wahl 2Q17  Enrico’s website Krist’s website  The Twitter interactive page “How every #GameOfThrones episode has been discussed on Twitter” Twitter platform for developers  Labella.js Twitter D3Kit  Krist’s post: “How I carefully crafted a truly terrible data visualization”   Related Episodes  Data Stories 11: emoto with Stephan Thiel from Studio NAND Data Stories 54: Designing Exploratory Data Visualization Tools with Miriah Meyer Data Stories 62: Text Visualization: Past, Present and Future with Chris Collins Data Stories 95: Challenges of Being a Vis Professional in Industry with Elijah Meeks  http://datastori.es/wp-content/uploads/2017/09/krist-promo.m4v

[Help us run the show by <a href="https://www.patreon.com/datastories" rel="nofollow" target="_blank">supporting us on Patreon!</a>] This week we have <a href="http://kristw.yellowpigz.com/" rel="nofollow" target="_blank">Krist Wongsuphasawat</a> on Data Stories to talk about visualization projects at Twitter. Krist has a Ph.D. in Computer Science from the University of Maryland, where he worked with Ben Shneiderman. Most recently, he has been a Data Visualization Scientist at Twitter since 2012. On the show, Krist describes the kinds of projects that the visualization team at Twitter develops. He also walks us through a few of the most popular of these projects, including their famous visualization of<a href="https://interactive.twitter.com/game-of-thrones/#?episode=66" rel="nofollow" target="_blank"> Game of Thrones.</a> Also, don’t miss Krist’s masterpiece post “<a href="https://medium.freecodecamp.org/how-i-carefully-crafted-a-terrible-visualization-2c8e06d50ebb" rel="nofollow" target="_blank">How I carefully crafted a truly terrible data visualization</a>” Enjoy the show! Data Stories is brought to you by Qlik. Are you missing out on meaningful relationships hidden in your data? Unlock the whole story with Qlik Sense through personalized visualizations and dynamic dashboards which you can download for free at <a href="http://qlik.de/datastories" rel="nofollow" target="_blank">qlik.de/datastories</a>. Links <ul> <li><a href="http://2Q17.de/" rel="nofollow" target="_blank">Wahl 2Q17 </a></li> <li><a href="http://enrico.bertini.io/" rel="nofollow" target="_blank">Enrico’s website</a></li> <li><a href="http://kristw.yellowpigz.com/" rel="nofollow" target="_blank">Krist’s website </a></li> <li><a href="https://interactive.twitter.com/" rel="nofollow" target="_blank">The Twitter interactive page</a></li> <li><a href="https://interactive.twitter.com/game-of-thrones/#?episode=66" rel="nofollow" target="_blank">“How every #GameOfThrones episode has been discussed on Twitter”</a></li> <li><a href="https://dev.twitter.com/" rel="nofollow" target="_blank">Twitter platform for developers </a></li> <li><a href="http://twitter.github.io/labella.js/" rel="nofollow" target="_blank">Labella.js</a></li> <li><a href="https://github.com/twitter/d3kit" rel="nofollow" target="_blank">Twitter D3Kit </a></li> <li><a href="https://medium.freecodecamp.org/how-i-carefully-crafted-a-terrible-visualization-2c8e06d50ebb" rel="nofollow" target="_blank">Krist’s post: “How I carefully crafted a truly terrible data visualization” </a></li> </ul> Related Episodes <ul> <li><a href="http://datastori.es/data-stories-11-emoto-with-stephan-thiel/" rel="nofollow" target="_blank">Data Stories 11: emoto with Stephan Thiel from Studio NAND</a></li> <li><a href="http://datastori.es/data-stories-54-designing-exploratory-data-visualization-tools-w-miriah-meyer/" rel="nofollow" target="_blank">Data Stories 54: Designing Exploratory Data Visualization Tools with Miriah Meyer</a></li> <li><a href="http://datastori.es/text-visualization-past-present-and-future-with-chris-collins-ds62/" rel="nofollow" target="_blank">Data Stories 62: Text Visualization: Past, Present and Future with Chris Collins</a></li> <li><a href="http://datastori.es/95-challenges-of-being-a-vis-professional-in-industry-with-elijah-meeks/" rel="nofollow" target="_blank">Data Stories 95: Challenges of Being a Vis Professional in Industry with Elijah Meeks</a></li> </ul> <a href="http://datastori.es/wp-content/uploads/2017/09/krist-promo.m4v" rel="nofollow" target="_blank">http://datastori.es/wp-content/uploads/2017/09/krist-promo.m4v</a>

105 | Data Visualization at Twitter with Krist Wongsuphasawat

Michelle Borkin

It’s a whole new year! Consider supporting Data Stories on Patreon! Michelle Borkin is Assistant Professor at Northeastern University where she studies the use of visualization in science research, in particular how it impacts human perception and cognition. On the show we talk about how the data viz community can better support the work of scientists, her popular research on data visualization memorability and, of course, the infamous data viz dinosaur.  LINKS  Michelle Borkin Michelle’s paper: “Evaluation of artery visualizations for heart disease diagnosis” Michelle’s research on data visualization memorability  Michelle’s TED Talk NUVis Consortium MassVis Data Set of Charts  http://datastori.es/wp-content/uploads/2018/01/borkin-promo.m4v 

It’s a whole new year! Consider <a href="https://www.patreon.com/datastories" rel="nofollow" target="_blank">supporting Data Stories on Patreon</a>! <a href="https://www.ccis.northeastern.edu/people/michelle-borkin/" rel="nofollow" target="_blank">Michelle Borkin</a> is Assistant Professor at Northeastern University where she studies the use of visualization in science research, in particular how it impacts human perception and cognition. On the show we talk about how the data viz community can better support the work of scientists, her popular research on data visualization memorability and, of course, the infamous data viz dinosaur. LINKS <ul> <li><a href="https://www.ccis.northeastern.edu/people/michelle-borkin/" rel="nofollow" target="_blank">Michelle Borkin</a></li> <li>Michelle’s paper: “<a href="http://iis.seas.harvard.edu/papers/2011/borkin11-infoviz.pdf" rel="nofollow" target="_blank">Evaluation of artery visualizations for heart disease diagnosis</a>”</li> <li>Michelle’s research on <a href="https://vcg.seas.harvard.edu/files/pfister/files/infovis_submission251-camera.pdf" rel="nofollow" target="_blank">data visualization memorability</a> </li> <li>Michelle’s <a href="https://www.ted.com/talks/michelle_borkin_can_astronomers_help_doctors" rel="nofollow" target="_blank">TED Talk</a></li> <li><a href="https://nuvis.northeastern.edu/" rel="nofollow" target="_blank">NUVis Consortium</a></li> <li><a href="http://massvis.mit.edu/" rel="nofollow" target="_blank">MassVis Data Set of Charts</a></li> </ul> <a href="http://datastori.es/wp-content/uploads/2018/01/borkin-promo.m4v" rel="nofollow" target="_blank">http://datastori.es/wp-content/uploads/2018/01/borkin-promo.m4v</a>

113 | What Makes A Visualization Memorable? with Michelle Borkin

Carl Bergstrom

In this episode we have Carl Bergstrom and Jevin West, two professors at the University of Washington, who talk about a fantastic new course they have designed called “Calling Bullshit“. The course aims to teach students what bullshit is, how to spot it, and how to deal with it. Needless to say, it’s timely. It’s also gotten a lot of attention lately. Of course there are plenty of bullshit examples in data analysis and visualization. Carl and Jevin discuss many of them in their course. On the show we talk about how they developed the course, what bullshit actually is and what distinguishes it from other types of misinformation, how to recognize examples of bullshit, and how to ‘call bullshit’ in an ethical way. Enjoy this “bullshitty” episode!  Data Stories is brought to you by Qlik. Are you missing out on meaningful relationships hidden in your data? Unlock the whole story with Qlik Sense through personalized visualizations and dynamic dashboards which you can download for free at qlik.de/datastories. Links  Course home page: http://callingbullshit.org Video series of the course Carl Bergstrom Jevin West Feynman on “not fooling yourself“ Harry Frankfurt’s definition of bullshit Two case studies of bullshit: Caffeine Free and Foodstamp Fraud The Fine Art of Baloney Detection How to Spot Fake News Brandolini’s Bullshit Asymmetry Principle   http://datastori.es/wp-content/uploads/2017/05/bullshit-promo.m4v Help us fund Data Stories by donating on Patreon! We’re counting on you to switch to a crowdfunding model. Please visit our Patreon page for more details! Related episodes Big Data Skepticism w/ Kate CrawfordData Ethics and Privacy with Eleanor SaittaCognitive Bias and Visualization with Evanthia DimaraVisualizing COVID-19 with Carl BergstromVisualization and Statistics with Andrew Gelman and Jessica Hullman

In this episode we have <a href="http://octavia.zoology.washington.edu/" rel="nofollow" target="_blank">Carl Bergstrom</a> and <a href="http://www.jevinwest.org/" rel="nofollow" target="_blank">Jevin West</a>, two professors at the University of Washington, who talk about a fantastic new course they have designed called “<a href="http://callingbullshit.org/" rel="nofollow" target="_blank">Calling Bullshit</a>“. The course aims to teach students what bullshit is, how to spot it, and how to deal with it. Needless to say, it’s timely. It’s also gotten a lot of attention lately. Of course there are plenty of bullshit examples in data analysis and visualization. Carl and Jevin discuss many of them in their course. On the show we talk about how they developed the course, what bullshit actually is and what distinguishes it from other types of misinformation, how to recognize examples of bullshit, and how to ‘call bullshit’ in an ethical way. Enjoy this “bullshitty” episode! Data Stories is brought to you by Qlik. Are you missing out on meaningful relationships hidden in your data? Unlock the whole story with Qlik Sense through personalized visualizations and dynamic dashboards which you can download for free at <a href="http://qlik.de/datastories" rel="nofollow" target="_blank">qlik.de/datastories</a>. Links <ul> <li>Course home page: <a href="http://callingbullshit.org" rel="nofollow" target="_blank">http://callingbullshit.org</a></li> <li><a href="https://www.youtube.com/watch?v=A2OtU5vlR0k&amp;feature=youtu.be&amp;list=PLPnZfvKID1Sje5jWxt-4CSZD7bUI4gSPS" rel="nofollow" target="_blank">Video</a> series of the course</li> <li><a href="http://octavia.zoology.washington.edu/" rel="nofollow" target="_blank">Carl Bergstrom</a></li> <li><a href="http://www.jevinwest.org/" rel="nofollow" target="_blank">Jevin West</a></li> <li>Feynman <a href="https://www.brainyquote.com/quotes/quotes/r/richardpf137642.html" rel="nofollow" target="_blank">on “not fooling yourself</a>“</li> <li>Harry Frankfurt’s <a href="https://www.stoa.org.uk/topics/bullshit/pdf/on-bullshit.pdf" rel="nofollow" target="_blank">definition of bullshit</a></li> <li>Two case studies of bullshit: <a href="http://callingbullshit.org/case_studies/case_study_caffeine_free.html" rel="nofollow" target="_blank">Caffeine Free</a> and <a href="http://callingbullshit.org/case_studies/case_study_foodstamp_fraud.html" rel="nofollow" target="_blank">Foodstamp Fraud</a></li> <li><a href="http://www.inf.fu-berlin.de/lehre/pmo/eng/Sagan-Baloney.pdf" rel="nofollow" target="_blank">The Fine Art of Baloney Detection</a></li> <li><a href="http://www.factcheck.org/2016/11/how-to-spot-fake-news/" rel="nofollow" target="_blank">How to Spot Fake News</a></li> <li><a href="http://ordrespontane.blogspot.de/2014/07/brandolinis-law.html" rel="nofollow" target="_blank">Brandolini’s Bullshit Asymmetry Principle</a></li> </ul> <a href="http://datastori.es/wp-content/uploads/2017/05/bullshit-promo.m4v" rel="nofollow" target="_blank">http://datastori.es/wp-content/uploads/2017/05/bullshit-promo.m4v</a> Help us fund Data Stories by donating on<a href="https://www.patreon.com/datastories" rel="nofollow" target="_blank"> Patreon</a>! We’re counting on you to switch to a crowdfunding model. Please visit our <a href="http://www.patreon.com/datastories" rel="nofollow" target="_blank">Patreon page</a> for more details! <h3>Related episodes</h3> <ul><li><a href="https://datastori.es/data-stories-27-big-data-skepticism-w-kate-crawford/" rel="nofollow" target="_blank">Big Data Skepticism w/ Kate Crawford</a></li><li><a href="https://datastori.es/74-data-ethics-and-privacy-with-eleanor-saitta/" rel="nofollow" target="_blank">Data Ethics and Privacy with Eleanor Saitta</a></li><li><a href="https://datastori.es/116-cognitive-bias-and-visualization-with-evanthia-dimara/" rel="nofollow" target="_blank">Cognitive Bias and Visualization with Evanthia Dimara</a></li><li><a href="https://datastori.es/160-visualising-covid-19-with-carl-bergstrom/" rel="nofollow" target="_blank">Visualizing COVID-19 with Carl Bergstrom</a></li><li><a href="https://datastori.es/167-visualization-and-statistics-with-andrew-gelman-and-jessica-hullman/" rel="nofollow" target="_blank">Visualization and Statistics with Andrew Gelman and Jessica Hullman</a></li></ul>

097  |  Calling Bullshit with Carl Bergstrom and Jevin West

Paul Slovic

We have Professor Paul Slovic from University of Oregon on the show to talk about “Statistical Numbing.” Professor Slovic is a renowned expert on the effect of numbers and statistics on empathy (or lack thereof). His fascinating, if not depressing, experiments have consistently shown how hard it is for statistics to elicit any sense of scale in human tragedies and how numbers can often even be detrimental if the goal is to elicit compassion and generous actions from an audience. On the show, we talk about “Statistical Numbing” and it psychological underpinnings. Professor Slovic also describes his experiments and their implications. And we address one of the most important questions: Is there hope? Is there something we, as practitioners, can do to counteract these negative effects? Enjoy this deeply scientific episode and let us know what you think! This episode of Data Stories is sponsored by FreshBooks, the small business accounting software that makes your accounting tasks easy, fast and secure. FreshBooks is offering a month of free unrestricted use to all of our listeners. To claim your free month of FreshBooks, go to http://freshbooks.com/datastories and sign up for free without the use of a credit card. Note: Remember to enter “Data Stories” in the section titled “I heard about FreshBooks from…”  http://datastori.es/wp-content/uploads/2016/10/Paul-Slovic-promo.mp4     LINKS  Prof. Paul Slovic’s homepage Prof. Slovic’s Latest Book: “Numbers and Nerves” Paper: “If I look at the mass I will never act”: Psychic numbing and genocide NYT Article: “The Arithmetic of Compassion” Wikipedia Page on Psychic Numbing Psychology Today: “Statistical Numbing: Why Millions Can Die and We Don’t Care” Daniel Kahnemann’s Book: “Thinking, Fast and Slow” Weber’s Law James Andreoni’s Warm-Glow Giving xkcd: “A Timeline of Earth’s Average Temperature”   Related episodes Visualization and Statistics with Andrew Gelman and Jessica Hullman

We have <a href="http://www.decisionresearch.org/researcher/paul-slovic-ph-d/" rel="nofollow" target="_blank">Professor Paul Slovic</a> from University of Oregon on the show to talk about “Statistical Numbing.” Professor Slovic is a renowned expert on the effect of numbers and statistics on empathy (or lack thereof). His fascinating, if not depressing, experiments have consistently shown how hard it is for statistics to elicit any sense of scale in human tragedies and how numbers can often even be detrimental if the goal is to elicit compassion and generous actions from an audience. On the show, we talk about “Statistical Numbing” and it psychological underpinnings. Professor Slovic also describes his experiments and their implications. And we address one of the most important questions: Is there hope? Is there something we, as practitioners, can do to counteract these negative effects? Enjoy this deeply scientific episode and let us know what you think! This episode of Data Stories is sponsored by <a href="http://freshbooks.com/datastories" rel="nofollow" target="_blank">FreshBooks</a>, the small business accounting software that makes your accounting tasks easy, fast and secure. FreshBooks is offering a month of free unrestricted use to all of our listeners. To claim your free month of FreshBooks, go to <a href="http://freshbooks.com/datastories" rel="nofollow" target="_blank">http://freshbooks.com/datastories</a> and sign up for free without the use of a credit card. Note: Remember to enter “Data Stories” in the section titled “I heard about FreshBooks from…” <a href="http://datastori.es/wp-content/uploads/2016/10/Paul-Slovic-promo.mp4" rel="nofollow" target="_blank">http://datastori.es/wp-content/uploads/2016/10/Paul-Slovic-promo.mp4</a> LINKS <ul> <li>Prof. Paul Slovic’s <a href="http://www.decisionresearch.org/researcher/paul-slovic-ph-d/" rel="nofollow" target="_blank">homepage</a></li> <li>Prof. Slovic’s Latest Book: “<a href="http://www.osupress.oregonstate.edu/book/numbers-and-nerves" rel="nofollow" target="_blank">Numbers and Nerves</a>”</li> <li>Paper: <a href="http://journal.sjdm.org/7303a/jdm7303a.htm" rel="nofollow" target="_blank">“If I look at the mass I will never act”: Psychic numbing and genocide</a></li> <li>NYT Article: “<a href="http://www.nytimes.com/2015/12/06/opinion/the-arithmetic-of-compassion.html?_r=0" rel="nofollow" target="_blank">The Arithmetic of Compassion</a>”</li> <li>Wikipedia Page on <a href="https://en.wikipedia.org/wiki/Psychic_numbing" rel="nofollow" target="_blank">Psychic Numbing</a></li> <li>Psychology Today: “<a href="https://www.psychologytoday.com/blog/how-risky-is-it-really/201108/statistical-numbing-why-millions-can-die-and-we-don-t-care" rel="nofollow" target="_blank">Statistical Numbing: Why Millions Can Die and We Don’t Care</a>”</li> <li>Daniel Kahnemann’s Book: “<a href="https://www.amazon.com/Thinking-Fast-Slow-Daniel-Kahneman/dp/0374533555" rel="nofollow" target="_blank">Thinking, Fast and Slow</a>”</li> <li><a href="https://en.wikipedia.org/wiki/Weber%E2%80%93Fechner_law " rel="nofollow" target="_blank">Weber’s Law</a></li> <li>James Andreoni’s <a href="https://en.wikipedia.org/wiki/Warm-glow_giving " rel="nofollow" target="_blank">Warm-Glow Giving</a></li> <li>xkcd: “<a href="http://xkcd.com/1732/" rel="nofollow" target="_blank">A Timeline of Earth’s Average Temperature</a>”</li> </ul> <h3>Related episodes</h3> <ul><li><a href="https://datastori.es/167-visualization-and-statistics-with-andrew-gelman-and-jessica-hullman/" rel="nofollow" target="_blank">Visualization and Statistics with Andrew Gelman and Jessica Hullman</a></li></ul>

84 | Statistical Numbing with Paul Slovic

Hi Folks, We have Santiago Ortiz with us today. Santiago has an impressive array of data visualization projects he has been pouring out during the last year and a very unique style. See for yourself in his portfolio website: http://moebio.com/. We talk about the Tapestry Conference, mathematics, the business of data visualization and much much more. Enjoy it! Chapters 00:00:00 Start 00:00:01 Intro: our guest today: Santiago Ortiz (@moebio) 00:01:55 Tapestry conference 00:08:40 Santiago: how it all began: Flash, math and teaching 00:11:34 Bestiario 00:13:23 Impure/Quadrigram 00:14:17 Freelance since 2012 00:17:12 Yay for self-inititated projects! 00:20:56 Knowledge visualization 00:25:11 “Santiago style” 00:26:36 Client work 00:31:18 Tools, frameworks, open source 00:40:52 On process 00:51:47 Non-information-based projects 00:55:23 The role of math 01:06:41 Regional differences in the data visualization scenes? 01:17:13 Wrapping it up Episode’s Links Tapestry Conference Scott McCloud Pat Hanrahan Nigel Holmes Enrico’s live notes from tapestry Jonathan Corum’s slides Santiago and his work his portfolio: http://moebio.com/ his past company: http://www.bestiario.org/ Lostalgic (ABC’s LOST TV show): http://intuitionanalytics.com/other/lostalgic/ Love is patient (merging faces with voronoi shapes): http://moebio.com/loveispatient/ http://moebio.com/research/faces/ Processing library giCenterUtils: http://gicentre.org/utils/ Vis people with math background Jason Davies: http://www.jasondavies.com/ Jen Lowe: http://www.datatelling.com/ Hilbert Curves and Vis Wikipedia page on HC Martin Wattemberg’s Jigsaw Maps Daniel Keim’s Pixel-Oreinted Visualizations 

Hi Folks, We have <a href="http://moebio.com/" rel="nofollow" target="_blank">Santiago Ortiz</a> with us today. Santiago has an impressive array of data visualization projects he has been pouring out during the last year and a very unique style. See for yourself in his portfolio website: <a href="http://moebio.com/" rel="nofollow" target="_blank">http://moebio.com/</a>. We talk about the <a href="http://www.tapestryconference.com/" rel="nofollow" target="_blank">Tapestry Conference</a>, mathematics, the business of data visualization and much much more. Enjoy it! Chapters 00:00:00 Start 00:00:01 Intro: our guest today: Santiago Ortiz (@moebio) 00:01:55 Tapestry conference 00:08:40 Santiago: how it all began: Flash, math and teaching 00:11:34 Bestiario 00:13:23 Impure/Quadrigram 00:14:17 Freelance since 2012 00:17:12 Yay for self-inititated projects! 00:20:56 Knowledge visualization 00:25:11 “Santiago style” 00:26:36 Client work 00:31:18 Tools, frameworks, open source 00:40:52 On process 00:51:47 Non-information-based projects 00:55:23 The role of math 01:06:41 Regional differences in the data visualization scenes? 01:17:13 Wrapping it up Episode’s Links Tapestry Conference <a href="http://scottmccloud.com/" rel="nofollow" target="_blank">Scott McCloud</a> <a href="http://graphics.stanford.edu/~hanrahan/" rel="nofollow" target="_blank">Pat Hanrahan</a> <a href="http://nigelholmes.com/" rel="nofollow" target="_blank">Nigel Holmes</a> Enrico’s live <a href="https://docs.google.com/document/d/15NScjdF24GqQU_tjsPlizYst-Y5DtFXrfmHSlrsM1NM/edit?usp=sharing" rel="nofollow" target="_blank">notes from tapestry</a> Jonathan Corum’s <a href="http://style.org/tapestry/" rel="nofollow" target="_blank">slides</a> Santiago and his work his portfolio: <a href="http://moebio.com/" rel="nofollow" target="_blank">http://moebio.com/</a> his past company: <a href="http://www.bestiario.org/" rel="nofollow" target="_blank">http://www.bestiario.org/</a> Lostalgic (ABC’s LOST TV show): <a href="http://intuitionanalytics.com/other/lostalgic/" rel="nofollow" target="_blank">http://intuitionanalytics.com/other/lostalgic/</a> Love is patient (merging faces with voronoi shapes): <a href="http://moebio.com/loveispatient/" rel="nofollow" target="_blank">http://moebio.com/loveispatient/</a> <a href="http://moebio.com/research/faces/" rel="nofollow" target="_blank">http://moebio.com/research/faces/</a> Processing library giCenterUtils: <a href="http://gicentre.org/utils/" rel="nofollow" target="_blank">http://gicentre.org/utils/</a> Vis people with math background Jason Davies: <a href="http://www.jasondavies.com/" rel="nofollow" target="_blank">http://www.jasondavies.com/</a> Jen Lowe: <a href="http://www.datatelling.com/" rel="nofollow" target="_blank">http://www.datatelling.com/</a> Hilbert Curves and Vis <a href="http://en.wikipedia.org/wiki/Hilbert_curve" rel="nofollow" target="_blank">Wikipedia page on HC</a> Martin Wattemberg’s <a href="http://hint.fm/papers/158-wattenberg-final3.pdf" rel="nofollow" target="_blank">Jigsaw Maps</a> <a href="http://www.vis.uni-konstanz.de/mitglieder/keim/" rel="nofollow" target="_blank">Daniel Keim</a>’s <a href="http://www.sdml.info/library/Keim00.pdf" rel="nofollow" target="_blank">Pixel-Oreinted Visualizations</a>

19 | With Santiago Ortiz

Hey yo! We are back! We have a very researchy kind of episode this time. Jessica Hullman is on the show to talk about her research on narrative visualization. Jessica is a Postdoctoral Fellow at Berkeley and soon to be Assistant Professor at University of Washington iSchool. In the show we talk about lots of interesting basic visualization research issues like visualization literacy, bias and saliency, uncertainty, and some interesting automated annotation systems that Jessica has developed. We also talk about Jessica’s background in experimental poetry! Have fun. — Links  School of poetic computation Rudolf Arnheim (Art and Visual Perception) Zacks and Tversky’s study on line charts and bar charts interpretation Jessica’s paper on the role of sequence in vis (potential for order effects): Jessica’s paper on Benefitting InfoVis with Visual Difficulties Stephen Few’s criticism of the paper Paper on “What makes a data visualization memorable?” Paper on how perceptually difficult stimuli help us think more analytically Paper on “Animation: Can It Facilitate?” (criticising the value of animation) Having to explain things to yourself is useful for learning (from graphs) (in general) Enrico’s paper on “The Persuasive Power of Visualization” Kahneman’s book “Thinking fast and slow” Paper on graphs making information more visually salient NYT graphics: FIFA worldcup draws (representing uncertainty) Economist’s Blog Graphic Detail Contextifier and NewsViews (Jessica’s systems for generating visualizations to go with news articles) Ellipsis and Lyra (Authoring systems for narrative visualizations from Arvind Satyanarayan and Jeff Heer) Tableau Story Points

Hey yo! We are back! We have a very researchy kind of episode this time. <a href="http://www-personal.umich.edu/~jhullman/" rel="nofollow" target="_blank">Jessica Hullman</a> is on the show to talk about her research on narrative visualization. Jessica is a Postdoctoral Fellow at Berkeley and soon to be Assistant Professor at University of Washington iSchool. In the show we talk about lots of interesting basic visualization research issues like visualization literacy, bias and saliency, uncertainty, and some interesting automated annotation systems that Jessica has developed. We also talk about Jessica’s background in experimental poetry! Have fun. — Links <ul> <li><a href="http://sfpc.io/" rel="nofollow" target="_blank">School of poetic computation</a></li> <li><a href="http://en.wikipedia.org/wiki/Rudolf_Arnheim" rel="nofollow" target="_blank">Rudolf Arnheim</a> (Art and Visual Perception)</li> <li>Zacks and Tversky’s <a href="http://aaaipress.org/Papers/Symposia/Fall/1997/FS-97-03/FS97-03-018.pdf" rel="nofollow" target="_blank">study on line charts and bar charts interpretation</a></li> <li>Jessica’s <a href="http://www-personal.umich.edu/~jhullman/story_sequence_infovis_final.pdf" rel="nofollow" target="_blank">paper on the role of sequence</a> in vis (potential for order effects):</li> <li>Jessica’s paper on <a href="http://misc.si.umich.edu/media/papers/difficulties_infovis.pdf" rel="nofollow" target="_blank">Benefitting InfoVis with Visual Difficulties</a></li> <li>Stephen Few’s <a href="http://www.perceptualedge.com/articles/visual_business_intelligence/visual_difficulties.pdf" rel="nofollow" target="_blank">criticism of the paper</a></li> <li>Paper on “<a href="http://www.seas.harvard.edu/news/2013/10/what-makes-data-visualization-memorable" rel="nofollow" target="_blank">What makes a data visualization memorable?</a>”</li> <li>Paper on <a href="http://web.princeton.edu/sites/opplab/papers/JEPG%20Intuitive%20Correction%20Paper.pdf" rel="nofollow" target="_blank">how perceptually difficult stimuli help us think more analytically</a></li> <li>Paper on “<a href="https://web.cs.dal.ca/~sbrooks/csci4166-6406/seminars/readings/Tversky_AnimationFacilitate_IJHCS02.pdf" rel="nofollow" target="_blank">Animation: Can It Facilitate?</a>” (criticising the value of animation)</li> <li>Having to explain things to yourself is useful for learning (<a href="http://onlinelibrary.wiley.com/doi/10.1002/acp.1068/abstract" rel="nofollow" target="_blank">from graphs</a>) (<a href="http://alumni.media.mit.edu/~bsmith/courses/mas964/readings/Glaser.pdf" rel="nofollow" target="_blank">in general</a>)</li> <li>Enrico’s paper on “<a href="http://lsr.nellco.org/cgi/viewcontent.cgi?article=1476&amp;context=nyu_plltwp" rel="nofollow" target="_blank">The Persuasive Power of Visualization</a>”</li> <li>Kahneman’s book “<a href="http://www.amazon.com/Thinking-Fast-Slow-Daniel-Kahneman/dp/0374533555" rel="nofollow" target="_blank">Thinking fast and slow</a>”</li> <li>Paper on <a href="http://psycnet.apa.org/journals/xap/3/4/243/" rel="nofollow" target="_blank">graphs making information more visually salient</a></li> <li>NYT graphics: <a href="http://www.nytimes.com/interactive/2014/06/03/upshot/world-cup-draw-simulation.html" rel="nofollow" target="_blank">FIFA worldcup draws</a> (representing uncertainty)</li> <li>Economist’s Blog <a href="http://www.economist.com/blogs/graphicdetail" rel="nofollow" target="_blank">Graphic Detail</a></li> <li><a href="http://misc.si.umich.edu/media/papers/vis_messaging_CHI_20130120_submit.pdf" rel="nofollow" target="_blank">Contextifier</a> and <a href="http://misc.si.umich.edu/media/papers/NewsViews_20140112_CR.pdf" rel="nofollow" target="_blank">NewsViews</a> (Jessica’s systems for generating visualizations to go with news articles)</li> <li><a href="http://idl.cs.washington.edu/files/2014-Ellipsis-EuroVis.pdf" rel="nofollow" target="_blank">Ellipsis</a> and <a href="http://idl.cs.washington.edu/files/2014-Lyra-EuroVis.pdf" rel="nofollow" target="_blank">Lyra</a> (Authoring systems for narrative visualizations from <a href="http://arvindsatya.com/" rel="nofollow" target="_blank">Arvind Satyanarayan</a> and Jeff <a href="http://homes.cs.washington.edu/~jheer/" rel="nofollow" target="_blank">Hee</a>r)</li> <li>Tableau <a href="http://www.tableausoftware.com/about/blog/2014/5/82-preview-tell-story-your-data-story-points-30761" rel="nofollow" target="_blank">Story Points</a></li></ul>

040  |  Narrative Visualization Research w/ Jessica Hullman

Simon Rogers

[Thanks to our audio editor Nathan Griffiths (twitter.com/njgriffiths) for taking care of this episode] Hi everyone! After a long while … we have a real British voice on the show again! In this episode we have the pleasure to host data journalist Simon Rogers. Simon has been leading data journalism initiatives at The Guardian for many years and he recently moved to Twitter (with the official role of Data Editor) where he takes care of creating visual stories out of Twitter data. In the show we talk about his past experience at The Guardian as well as the more recent and exciting developments at Twitter. Links  The debate of Gregor &amp; Moritz with Simon on colors (and Simon pissed off by it :)) Creative tools: CartoDB and DataWrapper‎ Twitter Data Blog (where new projects are announced) Overview page of Twitter visualizations Simon’s post: Data Journalism as Punk [very interesting concept!] Simon’s infographics kid books: Animal Kingdom and Human Body

[Thanks to our audio editor Nathan Griffiths (<a href="https://twitter.com/njgriffiths" rel="nofollow" target="_blank">twitter.com/njgriffiths</a>) for taking care of this episode] Hi everyone! After a long while … we have a real British voice on the show again! In this episode we have the pleasure to host data journalist <a href="http://simonrogers.net/" rel="nofollow" target="_blank">Simon Rogers</a>. Simon has been leading data journalism initiatives at The Guardian for many years and he recently moved to Twitter (with the official role of Data Editor) where he takes care of creating visual stories out of Twitter data. In the show we talk about his past experience at The Guardian as well as the more recent and exciting developments at Twitter. Links <ul> <li>The <a href="http://www.theguardian.com/news/datablog/2012/apr/13/mapping-colours-open-journalism-storify" rel="nofollow" target="_blank">debate</a> of Gregor &amp; Moritz with Simon on colors (and Simon pissed off by it :))</li> <li>Creative tools: <a href="http://cartodb.com/" rel="nofollow" target="_blank">CartoDB</a> and D<a href="https://datawrapper.de/" rel="nofollow" target="_blank">ataWrapper‎</a></li> <li><a href="https://blog.twitter.com/tags/twitter-data?blog=company" rel="nofollow" target="_blank">Twitter Data Blog</a> (where new projects are announced)</li> <li><a href="http://twitter.github.io/interactive/" rel="nofollow" target="_blank">Overview page of Twitter visualizations</a></li> <li>Simon’s post: <a href="http://www.theguardian.com/news/datablog/2012/may/24/data-journalism-punk" rel="nofollow" target="_blank">Data Journalism as Punk</a> [very interesting concept!]</li> <li>Simon’s infographics kid books: <a href="http://www.amazon.com/Information-Graphics-Kingdom-Simon-Rogers/dp/0763671223/" rel="nofollow" target="_blank">Animal Kingdom</a> and <a href="http://www.amazon.com/Infographics-Human-Body-Simon-Rogers/dp/1848776551/" rel="nofollow" target="_blank">Human Body</a></li></ul>

034  |  Data journalism w/ Simon Rogers

Giorgia Lupi

Hi folks, We have Giorgia Lupi from Accurat on the show with us this time in our first real face-to-face episode ever — yes Moritz and Enrico in the same room! Giorgia’s work, and generally the work done by her agency, has been super popular lately. You might have seen, for instance, their work visualizing Nobel Prizes or visualizing painters’ lives. Giorgia kindly hosted us in the Accurat’s studio in New York where we had a nice chat on hand-crafted visualization, high-density designs, design studios, and much much more. Here is us arguing even before starting the recording     Enjoy the show! — Links  Famous Writers’ Sleep Habits vs. Literary Productivity, Visualized Accurat’s Flickr data stream Accurat’s fashion analytics tool Giorgia’s sketches on Pinterest Research paper on the benefit of visual difficulties: “Hullman, Jessica, Eytan Adar, and Priti Shah. “Benefitting InfoVis with visual difficulties.” Visualization and Computer Graphics, IEEE Transactions on 17.12 (2011): 2213-2222.”

Hi folks, We have <a href="http://giorgialupi.net/" rel="nofollow" target="_blank">Giorgia Lupi</a> from <a href="http://www.accurat.it/" rel="nofollow" target="_blank">Accurat</a> on the show with us this time in our first real face-to-face episode ever — yes Moritz and Enrico in the same room! Giorgia’s work, and generally the work done by her agency, has been super popular lately. You might have seen, for instance, their work <a href="http://www.brainpickings.org/index.php/2012/11/29/giorgia-lupi-noble-prizes-visualization/" rel="nofollow" target="_blank">visualizing Nobel Prizes</a> or <a href="http://www.brainpickings.org/index.php/2013/06/07/painters-lives-accurat-giorgia-lupi/" rel="nofollow" target="_blank">visualizing painters’ lives</a>. Giorgia kindly hosted us in the Accurat’s studio in New York where we had a nice chat on hand-crafted visualization, high-density designs, design studios, and much much more. Here is us arguing even before starting the recording <a href="http://datastori.es/wp-content/uploads/2014/02/IMG_5784.jpg" rel="nofollow" target="_blank"></a> Enjoy the show! — Links <ul> <li><a href="http://www.brainpickings.org/index.php/2013/12/16/writers-wakeup-times-literary-productivity-visualization/" rel="nofollow" target="_blank">Famous Writers’ Sleep Habits vs. Literary Productivity, Visualized</a></li> <li><a href="http://www.flickr.com/photos/accurat/" rel="nofollow" target="_blank">Accurat’s Flickr data stream</a></li> <li><a href="https://www.behance.net/gallery/Next-Atlas/14152411" rel="nofollow" target="_blank">Accurat’s fashion analytics tool</a></li> <li><a href="http://www.pinterest.com/giorgialupi/sketches/" rel="nofollow" target="_blank">Giorgia’s sketches on Pinterest</a></li> <li>Research paper on the benefit of visual difficulties: “Hullman, Jessica, Eytan Adar, and Priti Shah. “<a href="http://www.google.com/url?q=http%3A%2F%2Fwww-personal.umich.edu%2F~jhullman%2Fhullman_adar_shah_infovis11.pdf&amp;sa=D&amp;sntz=1&amp;usg=AFQjCNGvHVXEB9BGj7UF8dnN7wwH5iYDOg" rel="nofollow" target="_blank">Benefitting InfoVis with visual difficulties.</a>” Visualization and Computer Graphics, IEEE Transactions on 17.12 (2011): 2213-2222.”</li></ul>

032  |  High Density Infographics and Data Drawing w/ Giorgia Lupi

Jeff Larson

ProPublica – Jeff Larsonhttp://www.propublica.org On the show this week we have Jeff Larson, Data Editor at ProPublica, to talk about his team’s recent work on “Machine Bias“. Jeff and his colleagues have analyzed the automated scoring decisions made by COMPAS, one of the systems American judges use to assess the likelihood that a convicted criminal will re-offend. By looking at the COMPAS data, Jeff and his colleagues sought to determine the accuracy of the algorithm and whether it introduces significant biases into the criminal justice system — racial or otherwise. (Their finding: Yes, it seems that it does.) On the show we talk about how the software is used by judges, how the ProPublica analysis was carried out, what the team found, and what can be done to improve the situation. Jeff also gives us a small preview of other stories his team is working on and how you can go about developing similar projects. Enjoy the show! This episode of Data Stories is sponsored by Qlik, which allows you to explore the hidden relationships within your data that lead to meaningful insights. Take a look at their Presidential Election app to analyze the TV network coverage for every mention of both Donald Trump and Hillary Clinton. And make sure to try out Qlik Sense for free at: qlik.de/datastories.  http://datastori.es/wp-content/uploads/2016/10/Larson-promo_v2.mp4   Links  Data analysis on GitHub: https://github.com/propublica/compas-analysis Article: “Machine Bias” Article: “Discrimination By Design” Article: “ProPublica Responds to Company’s Critique of Machine Bias Story” Article: “Technical Response to Northpointe” Article: “What Algorithmic Injustice Looks Like in Real Life” Article: “How We Analyzed the COMPAS Recidivism Algorithm” Article: “How Machines Learn to Be Racist“ Workshop: FAT ML 2016: Fairness, Accountability, and Transparency in Machine Learning   Related episodes Visualization and Statistics with Andrew Gelman and Jessica Hullman

ProPublica – Jeff Larson <a href="http://www.propublica.org" rel="nofollow" target="_blank">http://www.propublica.org</a> On the show this week we have <a href="https://www.propublica.org/site/author/jeff_larson" rel="nofollow" target="_blank">Jeff Larson</a>, Data Editor at <a href="https://www.propublica.org/" rel="nofollow" target="_blank">ProPublica</a>, to talk about his team’s recent work on “<a href="https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing" rel="nofollow" target="_blank">Machine Bias</a>“. Jeff and his colleagues have analyzed the automated scoring decisions made by <a href="https://www.propublica.org/article/how-we-analyzed-the-compas-recidivism-algorithm" rel="nofollow" target="_blank">COMPAS</a>, one of the systems American judges use to assess the likelihood that a convicted criminal will re-offend. By looking at the COMPAS data, Jeff and his colleagues sought to determine the accuracy of the algorithm and whether it introduces significant biases into the criminal justice system — racial or otherwise. (Their finding: Yes, it seems that it does.) On the show we talk about how the software is used by judges, how the ProPublica analysis was carried out, what the team found, and what can be done to improve the situation. Jeff also gives us a small preview of other stories his team is working on and how you can go about developing similar projects. Enjoy the show! This episode of Data Stories is sponsored by <a href="http://qlik.com" rel="nofollow" target="_blank">Qlik</a>, which allows you to explore the hidden relationships within your data that lead to meaningful insights. Take a look at their <a href="http://qlik.com/USPresElection" rel="nofollow" target="_blank">Presidential Election app</a> to analyze the TV network coverage for every mention of both Donald Trump and Hillary Clinton. And make sure to try out Qlik Sense for free at: <a href="http://qlik.de/datastories" rel="nofollow" target="_blank">qlik.de/datastories</a>. <a href="http://datastori.es/wp-content/uploads/2016/10/Larson-promo_v2.mp4" rel="nofollow" target="_blank">http://datastori.es/wp-content/uploads/2016/10/Larson-promo_v2.mp4</a> Links <ul> <li>Data analysis on GitHub: <a href="https://github.com/propublica/compas-analysis" rel="nofollow" target="_blank">https://github.com/propublica/compas-analysis</a></li> <li>Article: “<a href="https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing" rel="nofollow" target="_blank">Machine Bias</a>”</li> <li>Article: “<a href="https://www.propublica.org/article/discrimination-by-design" rel="nofollow" target="_blank">Discrimination By Design</a>”</li> <li>Article: “<a href="https://www.propublica.org/article/propublica-responds-to-companys-critique-of-machine-bias-story" rel="nofollow" target="_blank">ProPublica Responds to Company’s Critique of Machine Bias Story</a>”</li> <li>Article: “<a href="https://www.propublica.org/article/technical-response-to-northpointe" rel="nofollow" target="_blank">Technical Response to Northpointe</a>”</li> <li>Article: “<a href="https://www.propublica.org/article/what-algorithmic-injustice-looks-like-in-real-life" rel="nofollow" target="_blank">What Algorithmic Injustice Looks Like in Real Life</a>”</li> <li>Article: “<a href="https://www.propublica.org/article/how-we-analyzed-the-compas-recidivism-algorithm" rel="nofollow" target="_blank">How We Analyzed the COMPAS Recidivism Algorithm</a>”</li> <li>Article: “<a href="https://www.propublica.org/article/breaking-the-black-box-how-machines-learn-to-be-racist?word=Clinton" rel="nofollow" target="_blank">How Machines Learn to Be Racist</a>“</li> <li>Workshop: <a href="http://www.fatml.org/" rel="nofollow" target="_blank">FAT ML 2016: Fairness, Accountability, and Transparency in Machine Learning</a></li> </ul> <h3>Related episodes</h3> <ul><li><a href="https://datastori.es/167-visualization-and-statistics-with-andrew-gelman-and-jessica-hullman/" rel="nofollow" target="_blank">Visualization and Statistics with Andrew Gelman and Jessica Hullman</a></li></ul>

85 | Machine Bias with Jeff Larson

Lyn Bartram

Alper Sarikaya

[Our podcast is fully supported by our listeners. Please consider becoming a supporter on Patreon or sending us a one-time donation through Paypal. And thanks!]Oh dashboards… dashboards… what are they? For some, they are just ugly examples of bad visualization design (speed dials anyone?). For others, they are a first citizen of the data visualization world that deserve to be learned, studied, and understood.To dig into this debate, we have Lyn Bartram of Simon Fraser University and Alper Sarikaya of Microsoft Power BI on the show to talk about an exciting research project they developed. Their research seeks to build a better picture of what dashboard are and how they are used “in the wild.” The results are summarized in a paper they wrote with their colleagues from Tableau and Honeycomb.io: What Do We Talk About When We Talk About Dashboards?On the show we talk about how the project got started, what they discovered by analyzing a large corpus of dashboards, and the many ramifications of their research.Enjoy the show!Links Project page Supplemental material with images of all the dashboards the team analyzed (zip) http://datastori.es/wp-content/uploads/2019/02/DS-135-promo.mp4

[Our podcast is fully supported by our listeners. Please consider <a href="https://www.patreon.com/datastories" rel="nofollow" target="_blank">becoming a supporter on Patreon</a> or sending us a one-time donation through <a href="https://www.paypal.me/datastories" rel="nofollow" target="_blank">Paypal</a>. And thanks!]Oh dashboards… dashboards… what are they? For some, they are just ugly examples of bad visualization design (speed dials anyone?). For others, they are a first citizen of the data visualization world that deserve to be learned, studied, and understood.To dig into this debate, we have <a href="https://www.sfu.ca/~lyn/" rel="nofollow" target="_blank">Lyn Bartram</a> of Simon Fraser University and <a href="https://alper.datav.is/" rel="nofollow" target="_blank">Alper Sarikaya</a> of Microsoft Power BI on the show to talk about an exciting research project they developed. Their research seeks to build a better picture of what dashboard are and how they are used “in the wild.” The results are summarized in a paper they wrote with their colleagues from Tableau and <a href="http://Honeycomb.io" rel="nofollow" target="_blank">Honeycomb.io</a>: <a href="https://alper.datav.is/publications/dashboards/" rel="nofollow" target="_blank">What Do We Talk About When We Talk About Dashboards?</a>On the show we talk about how the project got started, what they discovered by analyzing a large corpus of dashboards, and the many ramifications of their research.Enjoy the show!Links<ul> <li><a href="https://alper.datav.is/publications/dashboards/" rel="nofollow" target="_blank">Project page</a></li> <li>Supplemental material with images of all the dashboards the team analyzed (<a href="https://alper.datav.is/assets/publications/dashboards/dashboards-suppl.zip" rel="nofollow" target="_blank">zip</a>)</li> </ul><a href="http://datastori.es/wp-content/uploads/2019/02/DS-135-promo.mp4" rel="nofollow" target="_blank">http://datastori.es/wp-content/uploads/2019/02/DS-135-promo.mp4</a>

135  |  The "Dashboard Conspiracy" with Lyn Bartram and Alper Sarikaya

Dietmar Offenhuber

We have Dietmar Offenhuber, Assistant Professor at Northeastern University, on the show again to talk about “Indexical Visualizations”: visualizations that reduce the gap between the recorded phenomenon and its representation. In Dietmar’s words: “If we understand ‘data’ as a collection of symbolically encoded observations, could we think of a display that conveys information—without the symbolic encoding of data—through the object itself?” On the show we talk about strategies to define and build indexical visualizations. Dietmar provides numerous examples, including thermometers, tree rings, petri dishes, and the blinking lights in your router. He also offers tips on experimenting with this kind of visualization and connecting to the indexical vis community. If you enjoy this episode you may also want to listen to our previous episode with Dietmar and to our “data sculptures” episode with Domestic Data Streamers. Enjoy the show! This episode is sponsored by Tableau. Tableau helps people see and understand their data. Tableau 10 is the latest version of the company’s rapid fire, easy-to-use visual analytics software. It includes a completely refreshed design, mobile enhancements, new options for preparing, integrating and connecting to data and a host of new enterprise capabilities. You can find more information on the upcoming Tableau 10 here. LINKS  OddOne (who made our new title music) Dietmar Offenhuber: http://offenhuber.net/ Paul Slovic’s “Psychic Numbing” Example: Kamel Makhloufi’s Iraqi casualties Example: Hydrogen sulfide measurement Documentation from Indexical Design Symposium Photoviz book from Nicolas Felton Related Data Stories episodes: DS 51 | Smart Cities w/ Dietmar Offenhuber DS 58 | Data Installations w/ Domestic Data Streamers   Book chapter: Offenhuber, Dietmar, and Orkan Telhan. 2015. “Indexical Visualization—the Data-Less Information Display.” In Ubiquitous Computing, Complexity and Culture, edited by Ulrik Ekman, Jay David Bolter, Lily Diaz, Morten Søndergaard, and Maria Engberg, 288–303. New York: Routledge. Other examples: Standing Waves on a String Bubble Chamber Representations http://www.highres.factum-arte.org/Tutankhamun/ Pinterest’s collection of indexical visualizations Hydrogen Sulfide Measurement Slime Mold Latent Figure Protocol  

We have <a href="http://offenhuber.net/" rel="nofollow" target="_blank">Dietmar Offenhuber</a>, Assistant Professor at Northeastern University, on the show <a href="http://datastori.es/data-stories-51-smart-cities-w-dietmar-offenhuber/" rel="nofollow" target="_blank">again</a> to talk about “Indexical Visualizations”: visualizations that reduce the gap between the recorded phenomenon and its representation. In Dietmar’s words: “If we understand ‘data’ as a collection of symbolically encoded observations, could we think of a display that conveys information—without the symbolic encoding of data—through the object itself?” On the show we talk about strategies to define and build indexical visualizations. Dietmar provides numerous examples, including thermometers, tree rings, petri dishes, and the blinking lights in your router. He also offers tips on experimenting with this kind of visualization and connecting to the indexical vis community. If you enjoy this episode you may also want to listen to our <a href="http://datastori.es/data-stories-51-smart-cities-w-dietmar-offenhuber/" rel="nofollow" target="_blank">previous episode with Dietmar</a> and to our <a href="http://datastori.es/data-stories-58-domestic-data-streamers/" rel="nofollow" target="_blank">“data sculptures” episode with Domestic Data Streamers</a>. Enjoy the show! This episode is sponsored by <a href="http://www.tableau.com/" rel="nofollow" target="_blank">Tableau</a>. <a href="http://www.tableau.com/" rel="nofollow" target="_blank">Tableau</a> helps people see and understand their data. <a href="http://www.tableau.com/coming-soon" rel="nofollow" target="_blank">Tableau 10</a> is the latest version of the company’s rapid fire, easy-to-use visual analytics software. It includes a completely refreshed design, mobile enhancements, new options for preparing, integrating and connecting to data and a host of new enterprise capabilities. You can find more information on the upcoming Tableau 10 <a href="http://www.tableau.com/coming-soon" rel="nofollow" target="_blank">here</a>. LINKS <ul> <li><a href="http://www.oddone.de" rel="nofollow" target="_blank">OddOne</a> (who made our new title music)</li> <li>Dietmar Offenhuber: <a href="http://offenhuber.net/" rel="nofollow" target="_blank">http://offenhuber.net/</a></li> <li><a href="https://en.wikipedia.org/wiki/Paul_Slovic" rel="nofollow" target="_blank">Paul Slovic</a>’s “<a href="https://en.wikipedia.org/wiki/Psychic_numbing" rel="nofollow" target="_blank">Psychic Numbing</a>”</li> <li>Example: Kamel Makhloufi’s <a href="https://www.pinterest.com/pin/522628731739829045/" rel="nofollow" target="_blank">Iraqi casualties</a></li> <li>Example: <a href="https://publiclab.org/wiki/hydrogen-sulfide-sensor" rel="nofollow" target="_blank">Hydrogen sulfide measurement</a></li> <li><a href="http://www.northeastern.edu/indexical/videos.html" rel="nofollow" target="_blank">Documentation from Indexical Design Symposium</a></li> <li><a href="http://shop.gestalten.com/photoviz.html?utm_source=flyer&amp;utm_medium=pp&amp;utm_campaign=campaignall" rel="nofollow" target="_blank">Photoviz book</a> from Nicolas Felton</li> <li>Related Data Stories episodes: <ul> <li><a href="http://datastori.es/data-stories-51-smart-cities-w-dietmar-offenhuber/" rel="nofollow" target="_blank">DS 51 | Smart Cities w/ Dietmar Offenhuber</a></li> <li><a href="http://datastori.es/data-stories-58-domestic-data-streamers/" rel="nofollow" target="_blank">DS 58 | Data Installations w/ Domestic Data Streamers</a></li> </ul> </li> <li>Book chapter: Offenhuber, Dietmar, and Orkan Telhan. 2015. “<a href="https://dl.dropboxusercontent.com/u/823528/Archive/offenhuber_telhan.pdf" rel="nofollow" target="_blank">Indexical Visualization—the Data-Less Information Display.</a>” In <a href="http://ubiquity.dk/" rel="nofollow" target="_blank">Ubiquitous Computing, Complexity and Culture</a>, edited by Ulrik Ekman, Jay David Bolter, Lily Diaz, Morten Søndergaard, and Maria Engberg, 288–303. New York: Routledge.</li> <li>Other examples: <ul> <li><a href="http://web.stanford.edu/dept/astro/dorris/StandingWaves.pdf" rel="nofollow" target="_blank">Standing Waves on a String</a></li> <li><a href="http://web.ihep.su/library/pubs/aconf00/tconf00/ps/c6-4.pdf" rel="nofollow" target="_blank">Bubble Chamber Representations</a></li> <li><a href="http://www.highres.factum-arte.org/Tutankhamun/" rel="nofollow" target="_blank">http://www.highres.factum-arte.org/Tutankhamun/</a></li> <li>Pinterest’s <a href="https://www.pinterest.com/dietmaro/indexical-visualization/%20http://www.factum-arte.com/pag/724/It" rel="nofollow" target="_blank">collection of indexical visualizations</a></li> <li><a href="https://publiclab.org/wiki/hydrogen-sulfide-sensor" rel="nofollow" target="_blank">Hydrogen Sulfide Measurement</a></li> <li><a href="https://www.pinterest.com/pin/522628731731944429/" rel="nofollow" target="_blank">Slime Mold</a></li> <li><a href="http://www.paulvanouse.com/lfp.html" rel="nofollow" target="_blank">Latent Figure Protocol</a></li> </ul> </li></ul>

80 | Indexical Visualization with Dietmar Offenhuber

Ben Wellington

Happy New Year everyone, we are back! In this episode we talk with Ben Wellington about his blog I Quant NY, where he writes about surprising facts he finds analyzing NYC open data. Some of his stories include how he discovered that “… Software in Half of NYC Cabs Generates $5.2 Million a Year in Extra Tips,” ideas on “How to Fix NYC’s No-Cabs-At-4PM Problem” and “How NYC Open Data and Reddit Saved New Yorkers Over $55,000 a Year” by detecting fire hydrants that generate too many parking tickets. On the show Ben talks about how he generates new ideas, how he finds and analyzes the data, and how he turns this into amazing stories for his blog. We also talk about the impact his work had on New York City and the interesting reactions some of his blog posts have generated. Enjoy Ben and his amazing NYC data stories, and read a transcript of our interview here!  This episode of Data Stories is sponsored by Quadrigram, a web based application designed to bring data stories to life. With Quadrigram you can create and share interactive data stories without the need of any coding skills.   LINKS Moritz’s project on place names – http://truth-and-beauty.net/experiments/ach-ingen-zell/ Our Guest Ben Wellington – https://about.me/benwellington I Quant NY – http://iquantny.tumblr.com Some favorite I Quant NY posts:  “You’ll Never Guess the Cleanest Fast Food Joint in NYC” “Half of Manhattan is Within 4 Blocks of a Starbucks” “How Software in Half of NYC Cabs Generates $5.2 Million a Year in Extra Tips” “How to Fix NYC’s No-Cabs-At-4PM Problem” “Success: How NYC Open Data and Reddit Saved New Yorkers Over $55,000 a Year”  Tools Ben uses for I Quant NY:  iPython:  http://ipython.org/ iPython Notebook Pandas: http://pandas.pydata.org/pandas-docs/stable/tutorials.html QGIS: http://www.qgis.org/en/site/ CartoDB: https://cartodb.com/

Happy New Year everyone, we are back! In this episode we talk with <a href="http://iquantny.tumblr.com/about" rel="nofollow" target="_blank">Ben Wellington</a> about his blog <a href="http://iquantny.tumblr.com/" rel="nofollow" target="_blank">I Quant NY</a>, where he writes about surprising facts he finds analyzing NYC open data. Some of his stories include how he discovered that “<a href="http://iquantny.tumblr.com/post/107245431809/how-software-in-half-of-nyc-cabs-generates-52" rel="nofollow" target="_blank">… Software in Half of NYC Cabs Generates $5.2 Million a Year in Extra Tips</a>,” ideas on “<a href="http://iquantny.tumblr.com/post/115096016059/how-to-fix-nycs-no-cabs-at-4pm-problem" rel="nofollow" target="_blank">How to Fix NYC’s No-Cabs-At-4PM Problem</a>” and “<a href="http://iquantny.tumblr.com/post/87573867759/success-how-nyc-open-data-and-reddit-saved-new" rel="nofollow" target="_blank">How NYC Open Data and Reddit Saved New Yorkers Over $55,000 a Year</a>” by detecting fire hydrants that generate too many parking tickets. On the show Ben talks about how he generates new ideas, how he finds and analyzes the data, and how he turns this into amazing stories for his blog. We also talk about the impact his work had on New York City and the interesting reactions some of his blog posts have generated. Enjoy Ben and his amazing NYC data stories, and read a transcript of our interview <a href="https://docs.google.com/document/d/1HRoD_kyOQAtd3X_Ly7t6KxIsirDHtUHNN1038sx8zx4/edit?usp=sharing" rel="nofollow" target="_blank">here</a>! This episode of Data Stories is sponsored by <a href="http://quadrigram.com" rel="nofollow" target="_blank">Quadrigram</a>, a web based application designed to bring data stories to life. With Quadrigram you can create and share interactive data stories without the need of any coding skills. LINKS Moritz’s project on place names – <a href="http://truth-and-beauty.net/experiments/ach-ingen-zell/" rel="nofollow" target="_blank">http://truth-and-beauty.net/experiments/ach-ingen-zell/</a> Our Guest Ben Wellington – <a href="https://about.me/benwellington" rel="nofollow" target="_blank">https://about.me/benwellington</a> I Quant NY – <a href="http://iquantny.tumblr.com" rel="nofollow" target="_blank">http://iquantny.tumblr.com</a> Some favorite I Quant NY posts: <ul> <li>“<a href="http://iquantny.tumblr.com/post/98869218219/youll-never-guess-the-cleanest-fast-food-joint-in" rel="nofollow" target="_blank">You’ll Never Guess the Cleanest Fast Food Joint in NYC</a>”</li> <li>“<a href="http://iquantny.tumblr.com/post/82964955696/half-of-manhattan-is-within-4-blocks-of-a" rel="nofollow" target="_blank">Half of Manhattan is Within 4 Blocks of a Starbucks</a>”</li> <li>“<a href="http://iquantny.tumblr.com/post/107245431809/how-software-in-half-of-nyc-cabs-generates-52" rel="nofollow" target="_blank">How Software in Half of NYC Cabs Generates $5.2 Million a Year in Extra Tips</a>”</li> <li>“<a href="http://iquantny.tumblr.com/post/115096016059/how-to-fix-nycs-no-cabs-at-4pm-problem" rel="nofollow" target="_blank">How to Fix NYC’s No-Cabs-At-4PM Problem</a>”</li> <li>“<a href="http://iquantny.tumblr.com/post/87573867759/success-how-nyc-open-data-and-reddit-saved-new" rel="nofollow" target="_blank">Success: How NYC Open Data and Reddit Saved New Yorkers Over $55,000 a Year</a>”</li> </ul> Tools Ben uses for I Quant NY: <ul> <li>iPython:  <a href="http://ipython.org/" rel="nofollow" target="_blank">http://ipython.org/</a></li> <li>iPython Notebook Pandas: <a href="http://pandas.pydata.org/pandas-docs/stable/tutorials.html" rel="nofollow" target="_blank">http://pandas.pydata.org/pandas-docs/stable/tutorials.html</a></li> <li>QGIS: <a href="http://www.qgis.org/en/site/" rel="nofollow" target="_blank">http://www.qgis.org/en/site/</a></li> <li>CartoDB: <a href="https://cartodb.com/" rel="nofollow" target="_blank">https://cartodb.com/</a></li></ul>

66 | "I Quant NY" Finding Surprising Stories in NYC Open Data with Ben Wellington

Danyel Fisher

[This podcast is fully supported by our listeners. If you enjoy listening to Data Stories, consider supporting us on Patreon. And now we also accept one-time donations through Paypal: just use this link. Thanks so much for your support!]   This week we have Miriah Meyer (University of Utah) and Danyel Fisher (Microsoft Research) on the show to talk about their new book Making Data Visual, which covers areas that other visualization books typically do not address: namely, how to go from formulating questions to building visualizations that solve actual problems that people have. On the show we talk about how the book came to be; some of the concepts introduced by Miriah and Danyel in the book, such as the use of proxy tasks for data;  and how you could use it for your own projects. Enjoy the show!  Links:  Miriah Meyer Danyel Fisher Book: Making Data Visual GitHub page with code  http://datastori.es/wp-content/uploads/2018/04/27fa4389-8b54-423e-9d6b-9360a3a0b8fc_27923.mp4

[This podcast is fully supported by our listeners. If you enjoy listening to Data Stories, consider <a href="https://www.patreon.com/datastories" rel="nofollow" target="_blank">supporting us on Patreon</a>. And now we also accept one-time donations through Paypal: just use <a href="https://www.paypal.me/datastories" rel="nofollow" target="_blank">this link</a><a href="https://www.paypal.me/datastories" rel="nofollow" target="_blank">. </a>Thanks so much for your support!] This week we have <a href="https://www.cs.utah.edu/~miriah/" rel="nofollow" target="_blank">Miriah Meyer</a> (University of Utah) and <a href="https://www.microsoft.com/en-us/research/people/danyelf/" rel="nofollow" target="_blank">Danyel Fisher</a> (Microsoft Research) on the show to talk about their new book <a href="http://shop.oreilly.com/product/0636920041320.do" rel="nofollow" target="_blank">Making Data Visual</a>, which covers areas that other visualization books typically do not address: namely, how to go from formulating questions to building visualizations that solve actual problems that people have. On the show we talk about how the book came to be; some of the concepts introduced by Miriah and Danyel in the book, such as the use of proxy tasks for data;  and how you could use it for your own projects. Enjoy the show! Links: <ul> <li><a href="https://www.cs.utah.edu/~miriah/" rel="nofollow" target="_blank">Miriah Meyer</a></li> <li><a href="https://www.microsoft.com/en-us/research/people/danyelf/" rel="nofollow" target="_blank">Danyel Fisher</a></li> <li>Book: <a href="http://shop.oreilly.com/product/0636920041320.do" rel="nofollow" target="_blank">Making Data Visual</a></li> <li><a href="https://makingdatavisual.github.io/" rel="nofollow" target="_blank">GitHub page with code</a></li> </ul> <a href="http://datastori.es/wp-content/uploads/2018/04/27fa4389-8b54-423e-9d6b-9360a3a0b8fc_27923.mp4" rel="nofollow" target="_blank">http://datastori.es/wp-content/uploads/2018/04/27fa4389-8b54-423e-9d6b-9360a3a0b8fc_27923.mp4</a>

118  |  Making Data Visual with Miriah Meyer and Danyel Fisher

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