Do you keep getting recommendations for data vis books, maybe even buy them, but don’t make it a priority to read them? Let’s read these books together – and let’s discuss them, to get more out of them. That’s what the Data Vis Book Club is about. Join us! Here’s what we’ll read next.
After a winter break, we’re back! I’m very happy to announce that our next book…well, won’t be a book at all, but a tour into the wonderful and strange world of data visualization research:
We will discuss six data vis research papers
on Tuesday, 17th of March at 6pm UTC here: notes.datawrapper.de/p/bookclub-papers
6pm UTC is 11am on the US west coast, 2pm on the US east coast, 6pm for readers in the UK & Portugal, 7pm for most other Europeans and 10.30pm in India.
Like always, everyone is welcomed to join! Just open the notepad at the correct date and time and start typing. Many participants will be new to the conversation – we’ll figure it out as we go.
Data vis papers we’ll read
I chose six papers (thanks for everyone’s suggestions!) that hopefully will give us a good idea of the variety of research written on data vis that communicates insights to a broader public. You’ll read “old” and fresh papers, papers on visualization details (choropleth maps!) and overviews, papers that focus on the process and papers that focus on the results. Let’s have a look:
1. Narrative Visualization: Telling Stories with Data (2010)
by Edward Segel and Jeffrey Heer: “Data visualization is regularly promoted for its ability to reveal stories within data, yet these “data stories” differ in important ways from traditional forms of storytelling. […] Drawing on case studies from news media to visualization research, we identify distinct genres of narrative visualization…" Find the PDF here.
2. Visualization Rhetoric: Framing Effects in Narrative Visualization (2011)
by Jessica Hullman and Nicholas Diakopoulos: “We demonstrate visualization rhetoric as an analytical framework for understanding how design techniques that prioritize particular interpretations in visualizations that “tell a story” can significantly affect end-user interpretation…" Find the PDF here.
3. Beyond Memorability: Visualization Recognition and Recall (2015)
by Michelle A. Borkin, Nam Wook Kim, Constance May Bainbridge,
Chelsea S. Yeh, Daniel Borkin, Hanspeter Pfister, and Aude Oliva: “In this paper we move beyond memorability and investigate how visualizations are recognized and recalled. For this study we labeled a dataset of 393 visualizations and analyzed the eye movements of 33 participants…” Find the PDF here or listen to Michelle talk about her findings in this Data Stories episode.
4. Improving information design practice (2016)
by Sheila Pontis and Michael Babwahsingh: “We assert that ineffective information design results primarily from a lack of rigor in the conceptual stage of the design process, when critical decisions determine the end result. We propose 23 methods information designers may adopt to reinforce their conceptual design activities.” Find the PDF here.
5. Empirical Studies on the Visual Perception of Spatial Patterns in Choropleth Maps (2019)
by Jochen Schiewe: “An essential purpose of choropleth maps is the visual perception of spatial patterns (such as the detection of hot spots or extreme values). […] Due to the lack of empirical evidence regarding some elementary design aspects, an online study with 260 participants was conducted. Three closely related effects were examined…” Find the PDF here.
6. Data is Personal: Attitudes and Perceptions of Data Visualization in Rural Pennsylvania (2019)
by Evan M. Peck, Sofia E. Ayuso, and Evan M. Peck: “We explore which factors may drive attention and trust in rural populations with diverse economic and educational backgrounds - a segment that is largely underrepresented in the data visualization literature. In 42 semistructured interviews in rural Pennsylvania (USA), we find that a complex set of factors intermix to inform attitudes and perceptions about data visualization…” Find the PDF here or listen to Evan talk about his findings in this Data Stories episode.
“Should I read data vis papers?”
If you’re invested in data vis, the answer is yes. “I was frustrated with how academic research works,” Data vis researcher Robert Kosara explained in his talk at Tapestry in 2013. “A lot of the work we do is really interesting, but nobody knows about it because our publications are just done in this little circle of peers. There is very little that gets out.” But there should be. Practitioners can benefit hugely from the research in data visualization.
Since 2013, things have improved. Conferences like the Information+ conference (this year in Atlanta), VisInPractice at the IEEE VIS (this year in Salt Lake City) and the blog Multiple Views (big recommendation!) bridge the gap between data vis practice and data vis research. In this book club session, we will do the same.
Read data vis papers with us if you want to
- explore the strange, under-explored world of data vis research
- get to know a new way of thinking about data vis
- see your work in a broader context
- learn new terminology to talk about data visualization
Don’t read data vis papers with us if you want to learn how to visualize data, get to know specific tools or if you want simple rules to follow.
“But wait, aren’t scientific papers hard to read?”
Not gonna lie, they’re not easy reads and you can’t skim them like you can your Twitter feed. So take your time reading these papers. Don’t read all at once, but one at a time. Get an overview first. Read them with a (digital) pen. Add big ❓ signs if you don’t understand something, then ask us on Twitter if you still don’t get it after reading the whole thing, or bring your questions into the discussion.
If you feel more frustrated than curious reading a paper, stop and get to the next one. You don’t need to read all of them to participate in the discussion. This is not a university course, but your free time.
“How does the book club work?”
1. You download the papers. They’re all free to download. (Scroll up to find the links!) I’m excited that money or delivery time won’t be important when deciding if you want to attend the discussion or not.
2. We all read the papers. That’s where the fun begins! Please mention @datavisclub or use the hashtag #datavisclub if you want to share your process, insights, and surprises – I’ll make sure to tweet them out as @datavisclub, as motivation for us all.
3. We get together to talk about the book. This will happen digitally on Tuesday, 17th of March 2020 at 6pm UTC over at notes.datawrapper.de/p/bookclub-papers.
It won’t be a call or a video chat; we’ll just write down our thoughts. We’ll go through all papers (10min per paper on average) and talk about our impressions, what we liked, what was hard to understand and our thoughts while reading these papers.
“I have more questions.”
Here’s a short FAQ for you:
“So what will happen exactly during the book club?”
A digital book club is a new experience for many of us. See how our book club discussions have looked like in the past:
You can also read the review of the first book club, to learn how people found the experience.
This is what others have said about the last book club discussions:
- “Just wanted to say this was my first time joining the book club and I JUST LOVED IT! Thank you everyone! This experience was incredible.”
- “Great experience! It was fun reading all of the questions and answers as they popped up and to scroll up and down the screen to check out any new comments.”
- “OMG! First time that I do it and I just loved it!!! I like that I can write everything I’m thinking about live and comment on other people’s ideas easily.”
“Why don’t we do a call? Why the notepad?”
Because it works well for introverts and people who prefer to stay anonymous in the discussion. Plus, the documentation of our meeting writes itself.
“I can’t make it on this date / at this time.”
Lunch date? Vacation? Need to bring the kids to bed? No problem! The conversation will be archived in the notes and can still be extended over the next day(s).
I’m very, very much looking forward to working through these six data vis papers with all of you. Thanks to everyone who has helped me figure out which papers to choose and gave useful tips, especially Wendy Kallina and Anton Ninkov, but also Adina Renner, Enrico Bertini, Michael Babwahsingh, Tobias Kauer, Christopher Collins, Ariel Aizemberg and Michael Neutze.
If you have any more questions, write in the comments, at firstname.lastname@example.org or to Lisa / the Datawrapper account on Twitter. Also, make sure to follow @datavisclub to stay up-to-date and get a dose of motivation from time to time.