Nathan Yau: With client work, you must hear “innovative”, “compelling”, and “engaging” often. Personally, I get a lot of this, and potential clients often don’t have data to work with. What makes a project interesting to you and worth your time?
Moritz Stefaner: In hindsight, the most satisfying projects for me were the ones, where the client or project partners were able to follow me in exploring, questioning, and extending the original data basis and project, sometimes going far away from the original project idea. Some ideas sound really good in the beginning, but turn out bland or much too complicated once executed with real data. Other ideas sound boring beforehand, but become exciting in a specific context. And other ideas you just develop by getting inspired from the data material itself. So, I realize this approach is a lot about trust and also flexibility on side of the client, but is the only way to get your visualization on point, ultimately.
NY: For people like us, the data is interesting as a CSV file, but most don’t get that luxury. What role does aesthetics play in making data interesting to a wider audience? What about truth? (You are after all, the truth and beauty operator :).
MS: I honestly hope, and sometimes think, that the playfulness and organic nature of some of my visualizations does actually get people excited about a topic they would not have been interested in beforehand. I do like to dig in data and be a little “data detective” myself, and if my work can contribute to getting more people excited about querying and questioning data, and, most importantly, come up with new questions to ask, than I am happy :) Aesthetics and appeal are of course a big part of the equation here, besides, of course, relevance of the information presented and truthfulness of the representation. But to me, aesthetics is very little about “decoration” — in my world, a clearly pronounced, rigorous, characteristic, “on point” representation of data lets the inner beauty of a compelling data set shine, instead of trying to “sex up” bland lists of facts.
NY: When getting started with visualization, everyone seems to want to know the “rules” of turning data into geometry. Are there any rules?
MS: There are no hard rules, but, as in any skill-based profession, there are some things that work better than others, and as for any cultural activity, you are not acting in the void, but in an established set of conventions, expectations and common knowledge. In my experience, great works are not strictly adhering to “the rules”, but, at the same time, are very sensitive to these two types of contexts, and are able to refer to, and sometimes even play with them.
NY: What’s the first thing you do when you have your data and get started on a project?
MS: Get a coffee, put on a DJ set, fire up Tableau and or Gephi, and Sublime Text for Python and data massaging and plot the sh*t out of the data. Then inspect, take a day to do something else, and follow up on the interesting perspectives. To continue, I might transform the existing data, get some new data, or take one of the interesting, but still very generic views and start to tailor it more to the specific issue at hand.
Looking forward to having a copy of the book in my hands! And thanks, Nathan!
Btw, a few weeks ago, iCharts interviewed me, too. Good times!
So, I made this thing on how many women speakers we have on stage at the type of conferences I like to go to. Personally, I think our field is probably already quite grown-up in respect of diversity and balance, but I think we could still do much better. I hope my small data collection and visualization helps a bit for organizers to reflect where they would like to land on my x-axis :) Relatedly, if somebody has good intentions, but trouble finding good female speakers, drop me a line, I know plenty.
This semester, I taught a master course on information visualization at HfK Bremen. It was quite fun and I think I was able improve a bit on the teaching side compared to the first full course I taught two years ago.
The topic was “Weltbilder” — “World views” which has become sort of a theme for my work lately. Here are the introductory slides and reference projects:
The course took place on 8 full days over the course of four weeks in February and March 2013. Overall, I had more than 20 students in the course (although some were only listening in without handing in a final project). The first few sessions were partly filled with me teaching basic craftmanship (slides—30MB) and establishing context, while the students gave presentations on some of my favorite scientific papers and articles (dropbox) and practitioners (such as Nathalie Miebach, Stefanie Posavec, Density Design, Santiago Ortiz, Nicholas Felton, Periscopic, Stamen, Ben Fry, Martin Wattenberg & Fernanda Viegas and the NYT graphics desk). We also had a few practical exercises on drawing family trees and fixing broken charts.
The second half of the course was much concerned with the student’s projects, and I did mostly 1:1 consultations. You can find a few of the final projects here. I like how the course results reflect the diversity of the students themselves — we had artists, computer scientists, journalists, people from humanities — quite a mixed bunch. Overall, I am quite happy with how things worked out and hope I could excite a few of my students to keep doing things in this field :)
Here are two of my favorite projects:
but in sum, they were all pretty nice in one way or the other :) Here’s the gallery
Storytelling has been one of the big buzzwords in data visualization the last year. By now, there are even whole conferences about the topic and I heard even some podcasts carry the word in their name :D
So, one could be tempted to think that storytelling is the magical ingredient to turn boring charts into killer visuals, make the blind see and save the world at large.
But, as so often, the pure and simple truth is rarely pure and never simple.
In fact, some of my favorite visualizations have no story to them.
Look at the legendary map of the market. A fantastic tool to understand the state of the stock market at one glance.
Consider Aaron Koblin’s Flight Patterns.
The brilliant map of optimal tic-tac-toe moves by xkcd.
And so on.
Tools have no stories to them. Tools can reveal stories, help us tell stories, but they are neither the story itself nor the storyteller.
Portraits have no story to them either. Like a photo portrait of a person, a visualization portrait of a data set can allow you to capture many facets of a bigger whole, but there is not a single story there, either.
Let us not forget about these important genres. There is more to information visualization than punchlines.
Update: After a few twitter discussions, here is a clarification: I argue against the often heard claim “every good visualization tells a story”. I would agree that, in a loose reading of the word, you could say that some of the above visualizations “reveal stories” or might “trigger stories” in the viewer’s mind.
Resonet is an attempt to map the twitter community around the resonate festival, using a technique similar to the vizosphere I made earlier. This time around, I used a zoomable SVG map, which makes text labels searchable. Make sure to also check out the data files and analysis, and feel free to remix the data!
Together with Lutz Bornmann, Rüdiger Mutz and Felix de Moya Anegon, I have been looking into which institutions (universities or research-focused institutions) are most active in different subject areas of science and which have published the most excellent papers. Based on my colleagues data analysis, we produced a small web application which allows to browse and explore the data set. The application is password protected, so you will need to end an email to password-request at excellencemapping.net to request access.
As you know, I was never too fond of awards — until I won two of them in one night :)
We just finished the documentation for emoto – a data art project visualising the online response to the Olympics London 2012.
In many ways, the crowning piece of the project, and a conceptual counterpoint to the ephemeral web activities, our data sculpture preserved the more than 12 million tweets we collected in physical form. We had 17 plates CNC-milled — one for each day of the games — with a relief heatmap indicating the emotional highs and lows of each day. Overlay projections highlighted individual stories, and visitors could scroll through the most retweeted tweets per hour for each story using a control knob.
The tweets and topics displayed in the installation can also be investigated in interactive heatmaps. Rollover the rows to see a tooltip display of the most retweeted tweet on the given topic at the respective point in time.
Find a brief documentation at moritz.stefaner.eu/projects/emoto/
or read more on the project here:
Article and interview on Creators Project
Data Stories podcast episode #11 with Stephan Thiel on emoto