Rank #1: 005 | How To Learn Data Visualization (with Andy Kirk)
We received many requests from people who wanted to know how to learn visualization in the past. So, here we are with a more than one hour long podcast with the three of us talking about it. We just hope you’ll find the time to listen to the entire episode. If not, the breakdown below can help you chunking it into a few sessions. Have fun!
Breakdown of the episode
00:00:00 Intro, Andy Kirk (http://visualisingdata.com) is again our guest
00:01:15 Topic: How to learn visualization
00:06:31 Reports from teaching practice
00:09:21 Theory and practice – rules vs, free exploration
00:12:24 Do you need to start with a question?
00:15:43 What is the basic skill set to learn?
00:16:15 Visual variables
00:18:53 Statistics and data analytics
00:19:32 Gestalt laws
00:20:32 The journalistic sense – what is an interesting angle?
00:22:19 Position is everything
00:23:38 Color is difficult
Process and tools
00:26:18 Data types and repertoire
00:31:27 The role of design
00:32:57 How to get started?
Learning options and books
00:39:46 Everybody should have a datavis course!
00:41:32 How to learn it yourself? Books, lectures, …
00:42:39 Stephen Few: Show me the numbers
00:43:20 Andy’s first book, and mo is the cinderella of datavis
00:43:52 Readings in Information Visualization: Using vision to think
00:45:09 Edward Tufte: Visual display of quantitative information
00:46:05 Ware: Information Visualization – Perception for Design
00:49:23 Our scoop!
00:52:03 Google for “information visualization lecture pdf”
The craft of visualization design
00:53:43 Now that you know everything – how to do it in practice?
00:55:01 DIY vs. template-based tools
00:57:01 Do you need to learn how to program? Yes, yep, yes, yeah. Me too.
01:00:17 Finding data
01:02:28 Put it out there
01:04:08 The pathetic misery that is creating data visualizations
01:05:52 Trying to wrap it up
01:07:13 see conference – and see+
01:08:44 Trying to wrap it up – again!
Resources and Links
- visualisingdata’s resource paper (including books)
- fellinlovewithdata’s data visualization beginner’s toolkit: books and tools
- “making a map together“, perfecting a visualization from the guardian’s data blog
- Ben Shneiderman’s Visual Information Seeking Mantra (overview first, …)
- Lakoff’s metaphors we live by (if you need metaphors to use in vis)
- New notable vis books:
- Noah Illinsky’s Designing Data Visualizations
- Nathan Yau’s Visualize This
- Tamara Munzner’s Information Visualization: Principles, Methods, and Practice (early incomplete draft)
- The Why Axis: vis criticism blog
That’s all folks. Let us know how you like it and feel free to ask more questions if you have.
Rank #2: 067 | ggplot2, R, and data toolmaking with Hadley Wickham
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!
- 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:
Rank #3: 000 |
Hi Folks, great news … we are experimenting with a new format for Data Stories that includes … that includes … that includes … guess whaaaaaat? Video!
After having heard many many times that it’s hard to imagine how a visualization looks like when we are talking about it, we have decided to experiment with a new format.
This is for now just a pilot to see how you guys react, so we would love to hear your feedback about how you like it and how we can improve.
To be clear: we are not planning to substitute our regular podcast with this, we are trying to build a parallel channel.
Here’s the video!
Gregor shows us where the idea originated from, all the crazy details about how to create a 3D chart that people can actually read, and how to calculate optimal views and a good narrative out of it.
Enjoy the new TV show! We are looking forward to hearing from you.
P.S. A big big thank you to Gregor for accepting to shoot this video with these two totally unexperienced video editors! Thanks Gregor, that was awesome!
Rank #4: 056 | Amanda Cox on Working With R, NYT Projects, Favorite Data
“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!
- 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
Rank #5: 134 | Visualizing Uncertainty with Jessica Hullman and Matthew Kay
What is uncertainty? Why is it important to take it into account when designing data visualizations? And how do you actually do so? We explore these and other questions with Jessica Hullman of Northwestern University and Matthew Kay of the University of Michigan. Jessica and Matt have written many publications on the topic that help orient us to the intricate world of uncertainty, probabilities, and their relevance to data visualization.
We hope you enjoy the show!
- National Institute for Standards (NIST): “Measurement Error”
- Useful material to learn about uncertainty visualization:
- Hypothetical Outcome Plots
- Hypothetical Outcome Plots: Experiencing the Uncertain
- Paper: Hypothetical Outcome Plots Outperform Error Bars and Violin Plots for Inferences about Reliability of Variable Ordering
- Paper: Hypothetical Outcome Plots Help Untrained Observers Judge Trends in Ambiguous Data
- Gregor Aisch on: “Why we used jittery gauges in our live election forecast”
- Ensembles – Visualizing storms
- Visual variables used to show probability/confidence
- Static depictions of outcomes (quantile dotplot)
- Paper: When (ish) is My Bus? User-centered Visualizations of Uncertainty in Everyday, Mobile Predictive Systems.
- Paper: Uncertainty Displays Using Quantile Dotplots or CDFs Improve Transit Decision-Making
- Paper: Imagining Replications: Graphical Prediction & Discrete Visualizations Improve Recall & Estimation of Effect Uncertainty
Rank #6: 022 | NYT Graphics and D3 with Mike Bostock and Shan Carter
We have graphic editors Mike Bostock and Shan Carter in this dense and long episode. It’s great to finally have someone from the New York Times!
We talk about many practical and more philosophical aspects of publishing interactive visualizations on the web. We also spend quite some time discussing the past, present and future of D3.js.
(On a side note: apologies for starting a bit abruptly and for the weird noises. Enrico was desperately and unsuccessfully trying to find a quiet and calm spot at the CHI conference.)
Enrico & Mo.
P.S. Many thanks to all of you guys who sent us Twitter questions for Mike and Shan.
00:00:12 Our guests today: New York Times graphics editors Mike Bostocks and Shan Carter
00:01:54 About the NYT graphics department
00:06:56 Map wrangling
00:08:47 QA, evaluation, fact checking,…
00:11:23 Twitter question: Post the data set along with the graphic?
00:15:51 Exploratory or explanatory?
00:19:56 User tracking, user feedback
00:25:53 Balance of familiarity vs. new visual vocabularies
00:29:52 Workflow, on the example of the 512 paths graphic
00:38:05 Hybrid workflows between automation and manual layout
00:45:49 History and philosophy
00:56:19 Value of examples
00:57:31 Community adoption
01:04:53 More d3 books or tutorials for advanced users?
01:08:15 Developer community
01:11:51 Future development
01:15:10 Enrico is back!
01:16:13 Is d3 complete?
01:18:52 When does Mike sleep?
01:19:45 Wrapping it up
Links to discussed NYT projects
Rank #7: 003 | How do you evaluate visualization?
In this episode we first answer to some of the questions we received and then we move on to the main topic: how do you evaluate visualization? We have been discussing some contests in episode #2 and thought evaluation is really a key issue there.
Breakdown of the episode
[01:34] Listener question: Terms and conditions in competitions
[03:46] Listener question: Connect research and practitioners
[07:43] Listener question: How to stay objective about your own work?
[10:23] Listener question: Do we criticize each other?
[11:15] Listener question: How to introduce business people to benefits of visualization beyond Excel?
[13:58] News: Visualizing sprint
[15:54] News: Kartograph
[19:40] SxSW Panel: Intent and Impact: How Visualization Makes a Change
[21:36] Quality criteria and evaluating information visualizations: traditional academic approach
[28:08] Evaluation beyond simple, clear-cut tasks
[33:13] Enrico admits his secret love of David MacCandless
[33:58] Andrew Vande Moere and Helen Purchase: On the role of design in information visualization
[35:00] Truth and Beauty or: “I know it when I see it”
[38:36] Data politics and importance of how the end product came about
[40:36] Tamara Munzner’s nested model for visualization evaluation and design
[44:25] Code of ethics
[45:59] Wrap up and outlook
Links and images
- Visualizing.org sprint
- SxSW panel: Intent and Impact
- Force-Directed Edge Bundling for Graph Visualization
- Hippocratic Oath (see towards the end of the post)
- A Code of Ethics for Data Visualization Professionals
Research papers mentioned in the episode
- On the role of design in information visualization. Andrew Vande Moere and Helen Purchase.
- An Insight-Based Methodology for Evaluating Bioinformatics Visualizations. Purvi Saraiya, Chris North, and Karen Duca.
- A nested process model for visualization design and validation. Tamara Munzner.
Have fun and, as usual, let us know what you think!
Rank #8: 069 | Data Visualization Literacy with Jeremy Boy, Helen Kennedy and Andy Kirk
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.”
- 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:
- 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/
- Information+ Conference Review
- VizKidz: Books on Data Visualization for Kids
- Re-designing Visualizations on #MakeoverMonday with Andy Kriebel and Andy Cotgreave
- Visualization Literacy in Elementary School with Basak Alper and Nathalie Riche
- What's Going On In This Graph? with Michael Gonchar and Sharon Hessney
- Researching the Boundaries of InfoVis with Sheelagh Carpendale
- Data Is Personal with Evan Peck
Rank #9: 120 | Data Science and Visualization with David Robinson
This week we have David Robinson on the show to talk about data science, in particular the role of data visualization in data science. David is Chief Scientist at Data Camp and author of multiple data science books and R packages. He also writes a great blog called “Variance Explained.”
On the show we talk about visualization as a data analysis tool, the problem of validation in exploratory data analysis, and David’s opinion on programming versus GUI interfaces. Also, don’t miss his great advice — and very generous offer! — on how to get started in data science!
Enjoy the show!
- David Robinson
- David’s blog Variance Explained
- Data Camp
- Analyzing networks of characters in ‘Love Actually’
- Using and Abusing Data Visualization: Anscombe’s Quartet and Cheating Bonferroni
- Advice to aspiring data scientists: start a blog
- David Robinson on Twitter
- Introduction to the Tidyverse course
Rank #10: 118 | Making Data Visual with Miriah Meyer and 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!
Rank #11: 105 | Data Visualization at Twitter with 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.
- 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
- Twitter D3Kit
- Krist’s post: “How I carefully crafted a truly terrible data visualization”
- 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
Rank #12: 035 | Visual Storytelling w/ Alberto Cairo and Robert Kosara
Hot topic today! We invited Alberto Cairo and Robert Kosara to discuss the role of storytelling in visualization. What is storytelling? Is all visualization storytelling? Should we always strive for telling a story? How does storytelling match with exploratory visualization? Should we aim more for worlds and macroscopes than stories as Moritz advocated a while back at Visualized? We went on a somewhat lengthy discussion on these topics and I think we all ended up agreeing on a lot of things and developed a much more nuanced view of storytelling. As you can see from the picture we had lots of fun (thanks Robert for taking the screenshot). Fantastic chat!
Note: Alberto had a lot more to say after the episode so he decided to publish a follow up post that clarifies some of the things he said on the show. But — spoiler alert — listen to the episode first!
P.S. Big, big thanks to Fabricio Tavares for taking care of the audio editing of this episode!
- Lynn Cherny on Implied Stories (and Data Vis)
- Periscopic’s Dino Citraro on A Framework for Talking About Data Narration
- Book cited by Alberto: The Unpersuadables: Adventures with the Enemies of Science
- Great visualizations without stories (proposed by Moritz):
- Moritz position on stories: Look ma, no story! | Worlds, not stories
- Enrico’s position on stories: Telling a story doesn’t tell the whole story
- Robert series on storytelling: Stories Are Gateways Into Worlds | Story: A Definition
- Robert’s mention of visualization on Copenhagen: Emissions, Treaties and Impacts
- Jessica Hallman’s VIS’13 paper on: Deeper Understanding of Sequence in Visualization
Rank #13: 062 | Text Visualization: Past, Present and Future with Chris Collins
We have Assistant Professor Chris Collins from University of Ontario Institute of Technology on the show to talk about text visualization. Chris explains what Text Vis is, provides examples from his and others’ work, describes tools and knowledge to get started, and looks into the future of the field, including its challenges and opportunities.
And here’s a really cool new thing — we have a transcript of the whole show! Browse the text, search for quotes and chapters, and maybe even… visualize it? Let us know if it’s useful!
Enjoy the show!
- Chris Collins and His Lab
- FluxFlow (twitter rumors detection and visualization) | See also “How riot rumours spread on Twitter” (from the Guardian)
- Probing Projections Project
- Patterns in Passwords
- Book: “Graphs, Maps, and Trees”
- Lexichrome (visualizing the color of words)
- Literature Fingerprinting (showing how different authors write) (PDF)
- Visualizing Text Readability (PDF)
- Text visualization browser (collection/taxonomy of text vis projects) [good place to start looking into text vis!]
- NLTK (Natural Language Toolkit)
This episode is sponsored by Qlik who allows you to explore hidden relationships within data that lead to insights. Check out the virtual event on Nov 18: Are you seeing the whole story that lives within your data? You can download Qlik Sense for free at: www.qlik.de/datastories.
Rank #14: 132 | A New Generation of DataViz Tools
We have data visualization freelancer and old friend-of-the-podcast Andy Kirk with us to talk about a new generation of data viz tools. You may not have noticed yet, but there are a quite a few nice new tools in development — and they all seem to have one thing in common: granting more artistic freedom to users while requiring less programming.
On the show we start by talking about the precursors to this generation of tools, such as Lyra and Data Driven Guides. We then pivot to the latest developments including Charticulator, Adobe’s Data Illustrator, and Lincoln.
What do these tools make possible that is still impossible or not so easy to do with the existing tools? What are their more exciting features? How do they differ in the way that they work? Why are we observing this trend now? And are they ultimately going to become real products? We ponder these and other questions on the show with Andy.
- Multiple Views: Visualization Research Explained
- Andy Kirk
- Visualisingdata’s list of data visualization tools
- Data Driven Guides
- Brett Victor’s Drawing Dynamic Visualizations
- Data Stories episode on Lyra
- Adobe’s Data Illustrator
- Open Refine
Rank #15: 135 | The "Dashboard Conspiracy" with Lyn Bartram and Alper Sarikaya
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!
Rank #16: 066 | "I Quant NY" Finding Surprising Stories in NYC Open Data with Ben Wellington
Happy New Year everyone, we are back!
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.
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/
Rank #17: 065 | What Happened in Vis in 2015? Year Review with Andy Kirk and Robert Kosara
Another turn of the year is approaching and we take some time to reflect with our classic guests Andy Kirk and Robert Kosara on what has happened in 2015: “What where the major trends? Big debates? Best visualizations? New tools? Etc.” We’ve even put our predictions in writing — you can read them in our transcript of this episode here.
This was a great year for Data Stories, with a total of 22 episodes (our record so far!). We want to thank our fantastic collaborators Destry and Florian for their great support with running the show, our guests for spending time talking with us, and of course all of you for listening to Data Stories!
Happy 2016! Enjoy the holidays and we’ll see you on January with a ton of new stuff from our side. Stay tuned!
Data Stories is brought to you by Qlik, who allows you to explore the hidden relationships within your data that lead to meaningful insights. Check out a new blog post from the Qlik Blog called “People Are Smart: Data Literacy and Broad Audiences”. As you may know Data Literacy is a subject we love to talk about!
Most popular episodes
- Data Stories #56: Amanda Cox on Working With R, NYT Projects, Favorite Data
- Data Stories #52: Science Communication at SciAm w/ Jen Christiansen
- Data Stories #57: Visualizing Human Development w/ Max Roser[a]
Major Trends Of 2015
- Cartograms, gridded maps (Collection of links in first item here, Hexmaps, London map, Bear map)
- Machine learning / image processing, etc. (e.g. use of satellite images)
- 3D and VR (NYT Cardboard Experiment)
- Better storytelling
- Data podcasts
- Mobile vis
- Vis ethics: debate on aesthetizing negative data — and Sarah Slobin’s recommendations
- Data visualization criticism – Design/redesign article
- The Stephen Few / Alberto Cairo / David Mccandleuss debate
- Stephen Few’s Visualization research a pseudoscience
- Dogmatic rules vs. flexibility
Great New Visualizations
understanding neural networks through deep visualization
- Dear Data
- Hear our episode with Dear Data
- Pace of social change
- 100 years of Tax Brackets
- Draw how family income affects children’s college chances
- Visualization of what neural networks see “Inceptionism: Going Deeper into Neural Networks” and “Understanding Neural Networks Through Deep Visualization”
- What’s really warming the world?
- Network effect
- Seagull sky trails
- What Happens When the Fed Raises Rates, In One Rube Goldberg Machine
CONNECTED SCATTER PLOT STUDY BY HAROZ, KOSARA AND FRANCONERI
- Papers on presentation-related topics (ISOTYPE, Connected Scatterplot, Bar chart embellishments)
- ISOTYPE: http://steveharoz.com/research/isotype/
- Connected Scatterplot: http://steveharoz.com/research/connected_scatterplot/
- Bar chart Embellishments: http://kosara.net/papers/2015/Skau-EuroVis-2015.pdf
- Enrico’s deceiving vis paper at CHI
- Borkin et al. on Memorability at VIS
- Hear our episode on the IEEE VIS ’15 Conference
- Seeing Data – Visualisation Literacy
- How do People Make Sense of Unfamiliar Visualization? A Grounded Model of Novice’s Information Visualization Sensemaking by Sukwon Lee, Sung-Hee Kim, Ya-Hsin Hung, Heidi Lam, Youn-ah Kang, and Ji Soo Yi
- Personal visualization: e.g. http://hcitang.org/papers/2015-tvcg-pva.pdf and http://www.computer.org/csdl/mags/cg/preprint/07106391.pdf
Notable People, Companies, Studios
Domestic Data streamers
- Bostock leaving NYT, Shan Carter, the rising star of Gregor Aisch
- Chad Skelton leaving Vancouver Sun
- Notable appointments at FT (Alan Smith OBE)
- London: After the flood, Signal/Noise, Tekja
- Domestic Data Streamers
- Hear our episode on Domestic Data Streamers
- Tamara Munzner, Visualization Analysis and Design
- Hear our episode with Tamara Munzner
- Stephanie Evergreen, Presenting Data Effectively: Communicating Your Findings for Maximum Impact
- Cole Nussbaumer Knaflic, Storytelling with Data
New titles coming up:
- Andy Kirk’s new book “Data Visualisation: A Handbook for Data-Driven Design”, May 2016
- Alberto Cairo’s new book “The Truthful Art”
- Hear our episode with Alberto Cairo and Robert Kosara
- Dear Data book (September 2016)
visualising data BLOG
- This guy Andy’s website (Kantar Information Is Beautiful Award)
- Visual Complexity – 10 years! 1000 projects!
- Reddit AMAs (Alberto, Tamara, Robert, Nate Silver, Hadley Wickham, David McCandless, Nathan Yau, Mike Bostock)
- Eagereyes (not new but still awesome)
Software / Libraries / Tools
- The end of Many Eyes
- Vega, Vegalite, etc. vs. D3
- Voyager and related tools
- Trifacta Data Wrangling tool
- Mapzen, CartoDB, Mapbox
Events and specific talks
What was your highlight?
What’s next in 2016? Wishes?
- Our expectations from last year’s edition
Happy New Year Everyone!
Rank #18: 116 | Cognitive Bias and Visualization with Evanthia Dimara
[This podcast is fully supported by our listeners. If you enjoy listening to Data Stories, consider supporting us on Patreon!]
We have Evanthia Dimara on the show to talk about cognitive bias and the role it plays in visualization. Evanthia has a PhD from INRIA and is now a postdoctoral researcher at the Institute for Intelligent Systems and Robotics (ISIR) in Paris. Her work focuses on data visualization and decision-making, and she specializes in understanding how bias affects our decisions when they are supported by visual representations.
On the show we talk about cognitive biases in general, introducing some of the most popular and funny examples. We then switch gears and Evanthia describes how the effects of specific biases translate to the world of data visualization and whether visualization can play a role in reducing bias.
Enjoy the show!
- Evanthia Dimara
- Daniel Kahneman’s book: “Thinking Fast and Slow“
- Epic list of cognitive biases
- Evanthia’s paper on: “The Attraction Effect in Information Visualization”.
- The cognitive bias song!
Rank #19: 032 | High Density Infographics and Data Drawing w/ Giorgia Lupi
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!
- 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.”