So welcome to (my) day 2 of Visweek! Today was even more exciting than yesterday (day 1 review here)! As the BioVis folk filtered out and the InfoVis people filtered in, there was a palpable change in energy in the conference area. It could have been more people, or the soda served at the first break, or the break from the rain, but there is definitely a higher energy here today.
In the MorningToday marked my first Visweek Keynote address, given this morning by Mary Czerwinski of Microsoft Research. All three ballrooms were open, the room was packed, and people seemed excited. The talk was interesting, but I was not inspired. She spoke about a number interesting projects Microsoft is working on (and has worked on) and showed some entertaining videos of projects that they worked on back in the day of IE4, as well as some various survey design techniques. Gauging by the number of questions at the end, many people seemed to find it interesting, but I was looking for something bit broader, a sentiment that was shared by a few other conference attendees I spoke with. I then turned to my first InfoVis session (in case you’re confused about the differences between all of these “Vis” sessions, I’ll spend some time discussing them in my final post). This session included the “best paper” of the conference by Steve Haroz and David Whitney about how to use color to encode information. Steve did a great job presenting—the authors made three general conclusions, which I adapt below to be a bit more practical:
- Minimize the use of bins (i.e., color) for categorical data;
- If possible, require interactivity in your design; and
- Group like items together.
In the AfternoonI had a great lunch with some graduate students, Jerome Cukier, and Drew Skau (from Tableau), and followed that up with some additionally interesting sessions. I will say that the afternoon InfoVis sessions (I did not try the SciVis or VAST sessions today) were a bit more technical than the morning session, so I got a bit less out of them. The paper by Anastasia Bezarios and Petra Isenberg, which tested how well people perceive visual variables from different perspectives in front of a large wall display was really interesting, and I enjoyed the description of the actual experiment. I also spent a bit of time in Marek Kultys’ tutorial on Good Practice of Visual Communication Design in Scientific and Data Visualization. Marek had a really nice basic-level data visualization course in his 4 hours or so of lecture, including a practical design period in which students were given a design challenge and asked to do some sketches (unfortunately, I didn’t stay to see how it turned out). I always find it interesting to see how different people try to teach basic data visualization principles and though I found his slides hard to read, I think his “6 Principles of Information Design” - borrowed from Edward Tufte's "The Visual Display of Quantitative Information" book - are well worth repeating::
- Have a properly chosen format;
- Show comprehensive information in true context—that is, do not lie;
- Use words, numbers, and drawing together;
- Avoid content-free information, including chart junk—in in other words, avoid redundant visual elements;
- Display an accessible complexity of detail; and
- Have a narrative quality—tell a story about your data.