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“Would you define this as a dashboard?” The question provoked quite a reaction!
In this episode, we talk about Peak Spotting, a new data visualization tool designed to help capacity managers at the German railway Deutsche Bahn handle passenger loads within the train system.
We recorded the episode live in Berlin, all together in the same room, with Moritz, the creative lead of the project, as well as the project’s other collaborators: project director Christian Au, technical lead Stephan Thiel, and designer Christian Laesser.
We talk about how the project started, the process the team followed to design the tool, how people at the German railway are using it, finding innovation within big companies, and the role of visualization in the movement towards automation.
Enjoy the show!
Links



Christian Au






Christian Laesser






Stephan Thiel






Moritz’s OpenVisConf keynote






Moritz’s writeup of the project






Studio NAND’s writeup of the project
Christian Laesser’s writeup of the project






Fast Company’s coverage of the project





http://datastori.es/wp-content/uploads/2018/11/Untitled-Project-Made-by-Headliner-3.mp4


131  |  Peak Spotting

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

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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!


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	Challenges of Being a Vis Professional in Industry with Elijah MeeksData Visualization at Capital One with Kim Rees and Steph Hay

170  |  Formalizing Design with Gabrielle Mérite and Alan Wilson


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

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			Related episodes
	
	Text Visualization: Past, Present and Future with Chris Collins

169  |  Data Conversations with Vidya Setlur

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

168  |  Highlights from IEEE VIS'22 with Tamara Munzner


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”

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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

167  |  Visualization and Statistics with Andrew Gelman and Jessica Hullman


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 & 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

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131 | Peak Spotting

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