Welcome to the final episode of Season #12 of the PolicyViz Podcast! Thanks so much for checking out the show this season and I hope you enjoy your summer. I’ll be back this fall with more great episodes.

On this episode of the show, I’m joined by David Aerne, a freelance developer and designer based in Zurich who has spent years building a remarkable collection of open-source color tools. We dig into the difference between color models, color spaces, and gamuts, and David explains why thinking about color in three dimensions—like navigating a cylinder—can make choosing palettes so much more intuitive. We talk through several of his projects, including Color Names (a curated list of nearly 32,000 community-contributed color names), Rampensau for generating color ramps, and the playful RYB-inspired explainer that simulates how physical, “printy” colors look on screen. David shares his philosophy that we should integrate the systems that generate colors into our work, rather than freezing a static palette and losing the creativity along the way. Whether you build dashboards, design slides, or just love playing with color, this conversation will change how you think about picking your next palette.

Keywords: color theory, color palettes, data visualization, color tools, HSL, HSV, RGB, color models, color spaces, open source, generative art, color ramps, design tools, JavaScript, web development, pixel art, PolicyViz Podcast, David Aerne

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Follow David Aerne on Bluesky and X (@meodai) and explore his open-source projects at elastiq.ch

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Email: jon@policyviz.com

The Math Behind Beautiful Color: David Aerne on Building Open-Source Color Tools

Welcome back to the show! In this week’s episode, I chat with Christian Martinez, a faculty member at Brooklyn College and several other CUNY schools, and Shannon Joyce, a newly minted master’s graduate in psychological research—who, as we note at the top, literally graduated the day before we recorded. Christian shares how he redesigned his graduate stats and R course around NYC Open Data, building what he calls an “accidental author” process that transforms students’ weekly homework into portfolio books and, ultimately, chapters in a published student gallery. Shannon walks us through her own project exploring the relationship between mold complaints and domestic violence rates in New York City, and reflects on what it means to learn to code by asking questions you actually care about. We also dig into the NYC Open Data R package Christian and his students built together—now streamlined from 40 functions down to three and approaching 2,000 installs—and close with a lively conversation about whether open data skews too negative and what a truly positive city dataset might look like.

Keywords: NYC open data, R programming, data visualization, teaching data science, open data, CUNY Brooklyn College, R package, data education, open educational resources, data storytelling, Quarto, RStudio, graduate education, data literacy, public data

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Find Christian Martinez and all student work at NYCOpenDataLab.org. Find Shannon Joyce on GitHub (github.com/ShannonJoyce) and LinkedIn.

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Email: jon@policyviz.com

From Homework to Portfolio: NYC Open Data in the Classroom

Episode #310! This week I sit down with Jennifer Roscoe and Shrishti Vaish, two of the key organizers behind Outlier 2026, the annual data visualization conference hosted by the Data Visualization Society. We talked about what it takes to pull off a fully virtual, global conference, and why going virtual this year was a strategic choice, not a compromise. Jennifer and Shrishti walked me through the conference dates (June 23–26), the brand-new pre-conference data challenge in partnership with the United Nations, and the exciting new feedback and career clinic designed to give attendees a safe space for honest critique and professional growth. We also get into the behind-the-scenes logistics: the 30-person volunteer committee, the technology stack (mostly Google Sheets, if you were wondering), and the delicate art of playing Tetris with 34 talks across a 12-hour global schedule. Whether you’re a first-time attendee or a longtime DVS community member, this episode is your guide to making the most of Outlier 2026.

Keywords: data visualization, data viz, Outlier conference, Data Visualization Society, DVS, data viz conference, Jennifer Roscoe, Shrishti Vaish, virtual conference, data storytelling, dataviz community, conference planning, career clinic, information is beautiful, data challenge, United Nations data, PolicyViz podcast

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Check out the 2026 Outlier Conference [https://www.datavisualizationsociety.org/outlier].

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Email: jon@policyviz.com

Outlier 2026: What to Expect at This Year’s Data Visualization Society Conference

I talk with Ramon Perez, Executive Director of the Digital Democracy Project this week. DDP is a nonpartisan nonprofit using secure mobile voting technology to give citizens a real-time voice in legislation. Ramon explains how the platform lets verified, registered voters weigh in on bills being debated in Congress and their state house—and then scores legislators on how closely their votes match what their districts wanted. We dig into how AI, including a RAG-powered chatbot called VoteBot, helps everyday citizens parse thousands of pages of complex legislative text. We also discuss digital security, participatory budgeting, and Ramon’s ambitious goal of expanding the platform to all 50 state legislatures by 2027.

Keywords: digital democracy, mobile voting, civic tech, legislative transparency, AI in government, Ramon Perez, Digital Democracy Project, VoteBot, participatory budgeting, voter engagement, legislator accountability, PolicyViz podcast, civic engagement, govtech

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Follow Ramon Perez and the Digital Democracy Project at digitaldemocracyproject.org and download the Votes (VOATZ) app to participate.

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Email: jon@policyviz.com

Reimagining Civic Participation: The Digital Democracy Project

Welcome back to the show! This week, I sit down with three co-authors of the Atlas of Macroscopes—Katy Borner, Elizabeth Record, and Todd Theriault from the Cyberinfrastructure for Network Science Center at Indiana University—to explore what a macroscope actually is and how it differs from a standard interactive visualization. We trace the 20-year journey of the Places and Spaces: Mapping Science exhibit, from two-dimensional wall maps to the 40 richly interactive pieces featured in this stunning 11×14-inch MIT Press book. Along the way, we talk about design strategies for making complex systems legible to general audiences, the role of AI in data visualization, and what it takes to grab and hold attention on a museum floor. Each guest shares a personal favorite from the book—ranging from Smelly Maps to an Appalachian opioid overdose tool to a skills-landscape explorer—and we close with a look at the exhibit’s exciting third decade, focused on visualizing intelligences.

Keywords

data visualization, macroscope, atlas of macroscopes, interactive visualization, Katy Borner, Indiana University, Places and Spaces, complex systems, information visualization, scrollytelling, AI and data visualization, opioid epidemic mapping, data communication, science exhibit, data science podcast

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Find the Atlas of Macroscopes [https://amzn.to/3PoaITJ] and explore the Places and Spaces exhibit at scimaps.org. Follow Katy Borner, Elizabeth Record, and Todd Theriault through Indiana University’s CNS Center.

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Email: jon@policyviz.com

Mapping the Invisible: Inside the Atlas of Macroscopes

In this episode, I sat down with Jen Ray and Jason Forrest—the married duo behind Data Vandals—to talk about their remarkable approach to bringing data visualization off the screen and into the physical world. What started as a pandemic-era poster campaign in New York City evolved into street theater, interactive gallery installations, and a Piaggio Ape three-wheeler touring London with opinion surveys. We talked about how they use isotypes, stickers, and hand-painted signs to spark real conversations between strangers about everything from gun violence to foxes to billionaires. We also got into their recent workshops in the Netherlands and Budapest, and their stunning new installation at Los Angeles Union Station about the city’s native wildlife. If you’ve ever wondered whether people will actually stop and engage with data—even on a cold March day in the East Village—this episode will convince you they will.

Keywords: data visualization, data vandals, Jen Ray, Jason Forrest, physical data visualization, data art, community engagement, isotype, street data, data physicalization, data communication, PolicyViz podcast, data storytelling, interactive data, data literacy, public data, data journalism, data design

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Follow Data Vandals on Instagram @datavandals and visit their website at datavandals.com

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Email: jon@policyviz.com

Data Vandals: Taking Data Visualization Off the Screen and Into the Streets

In this episode, I chat with Don Moynihan, professor of public policy at the University of Michigan and author of the widely-read Substack newsletter Can We Still Govern? Don’s research focuses on administrative burdens—the learning, compliance, and psychological costs people experience when interacting with government—and how those frictions shape public trust. We talk about the data challenges involved in measuring these experiences, how the shift to digital services changes the picture, and why governments historically have ignored the costs they impose on the people they serve. We also get into Don’s own journey as a public communicator: how a rejected op-ed about Joe Manchin and the child tax credit sparked his newsletter, what it took to retrain himself to write for a general audience, and how he thinks about balancing timeliness with depth. If you’re a researcher wondering whether public communication is worth the risk—or just curious about what makes government work (or not)—this one is for you.

Keywords

administrative burden, public policy, government services, bureaucracy, policy communication, Substack newsletter, academic writing, public administration, government trust, policy research, data visualization, civic engagement, open government, policy podcast

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Read Don’s newsletter Can We Still Govern? [https://donmoynihan.substack.com/]

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Email: jon@policyviz.com

Why Government Makes Things Hard: Don Moynihan on Administrative Burden

In this week’s episode, I talk with Melanie Tory, Professor of the Practice at Northeastern University, about how people actually use dashboards in the real world — and why that use often looks very different from what designers intend. Her research reveals that dashboards frequently serve as a starting point for accessing data rather than tools for answering questions directly, with many users simply exporting data to Excel to do their real analytical work. We also explore her work on AI-enabled healthcare systems designed to help clinicians monitor patient risk in intensive care units, including how to visualize uncertainty in ways that busy medical teams can process quickly. And we close with a look at her emerging research on how people are beginning to use generative AI tools for data visualization tasks. It's a thought-provoking conversation about the gap between the tools we build and the ways people actually work with data.

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Keywords: data visualization, dashboards, dashboard design, dashboard usability, data analysis workflows, Tableau dashboards, Power BI dashboards, human data interaction, Melanie Tory, data communication, dashboard research, analytics tools, business intelligence dashboards, data storytelling, data workflows, PolicyViz Podcast

Become a patron of the PolicyViz Podcast [https://patreon.com/policyviz?utm_medium=unknown&utm_source=join_link&utm_campaign=creatorshare_creator&utm_content=copyLink] for as little as a buck a month

Visit Melanie's webpage at Northeastern University [https://roux.northeastern.edu/people/melanie-tory/]

Follow me on Instagram [https://www.instagram.com/jschwabish/?hl=en],  LinkedIn [https://www.linkedin.com/in/jonathanschwabish/],  Substack [https://jschwabish.substack.com/],  Twitter [https://twitter.com/jschwabish],  Website [https://policyviz.com/],  YouTube [https://www.youtube.com/c/JonSchwabish]

Email: jon@policyviz.com [jschwabish@gmail.com]

AI, Dashboards, and Human Decisions: A Conversation with Melanie Tory

In this week’s episode of the PolicyViz Podcast, I chat with Michael Gethers, former Head of Data & Strategy for the McLaren IndyCar team, about how a personal side project analyzing IndyCar timing PDFs turned into a job building real-time data tools for a professional race team. We dig into what it’s like to design data products for engineers, strategists, and drivers who need to understand information instantly while a car is on track. Michael shares how he moved from making public visualizations on Twitter to building an internal analytics application from scratch, why “pretty charts” weren’t enough for the engineers, and how user feedback shaped the product. We also talk about race strategy as a probabilistic data science problem, the difference between dashboards and data products, and what he learned about designing for cognition under extreme time pressure. If you care about dashboards, data storytelling, or building tools people truly use, this conversation is a goldmine.

Keywords: data dashboards, data product design, data visualization, motorsports analytics, race strategy, McLaren IndyCar, telemetry data, timing data, data science in sports, user centered design, dashboard design, real time analytics, D3 visualization, data engineering, analytics application

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Follow me on Instagram [https://www.instagram.com/jschwabish/?hl=en],  LinkedIn [https://www.linkedin.com/in/jonathanschwabish/],  Substack [https://jschwabish.substack.com/],  Twitter [https://twitter.com/jschwabish],  Website [https://policyviz.com/],  YouTube [https://www.youtube.com/c/JonSchwabish]

Email: jon@policyviz.com [jschwabish@gmail.com]

From PDFs to Pit Lane: Building a Real-Time Data Product for McLaren Racing

In this episode, I talk with Nick Hart, President and CEO of the Data Foundation, about the rapidly changing landscape of federal data, statistical agencies, and evidence-based policymaking. We explore how the Evidence Act reshaped government data infrastructure, why privacy protections and data governance matter more than ever, and what’s been happening behind the scenes over the last year as agencies faced staffing cuts, data removals, and unprecedented political pressure. Nick explains how government data systems actually work, why the U.S. model is both admired and strained, and what a “Data System 2.0” might look like in the future. We also discuss state and local data roles, the risks of politicizing data, and two public-facing initiatives from the Data Foundation: the Evidence Act Hub and the People’s Data 100. This is a wide-ranging conversation about trust, transparency, and why government data quietly underpins far more of our lives than most people realize.

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Become a patron of the PolicyViz Podcast [https://patreon.com/policyviz?utm_medium=unknown&utm_source=join_link&utm_campaign=creatorshare_creator&utm_content=copyLink] for as little as a buck a month

Check out the Data Foundation [https://datafoundation.org/] and their People's Data 100 [https://datafoundation.org/pages/the-people-s-data-100] project! 

Follow me on Instagram [https://www.instagram.com/jschwabish/?hl=en],  LinkedIn [https://www.linkedin.com/in/jonathanschwabish/],  Substack [https://jschwabish.substack.com/],  Twitter [https://twitter.com/jschwabish],  Website [https://policyviz.com/],  YouTube [https://www.youtube.com/c/JonSchwabish]

Email: jon@policyviz.com [jschwabish@gmail.com]

The People’s Data: Why Federal Data Matters More Than Ever with Nick Hart

Learn how to be a great data communicator and visualizer with host Jon Schwabish. Hear from experts in the fields of data science, data visualization, and presentation skills to improve how you and your organization collect, analyze, and communicate your data in better, more efficient, and more effective ways.

The PolicyViz Podcast

Jon's Show

Helping you do a better job processing, analyzing, sharing, and presenting your data.