Shame on me, I didn't keep my word on reporting from EuroVis. Anyway here is a very small selection of the remarkable things I have seen during the conference.
Pat Hanrahan's talk was really deep and thoughtful. A lot of new basic material to think about visualization under a new lens.
Then I forced myself to select only 3 paper out of the long program. They are engaging and new in some sense. Obviously this is totally personal. And there were many other good ones worth reading.
Pat Hanrahan's Keynote
As I expected the talk was really great, but in a very special way that I couldn't imagine. The talk was titled "Systems of Thought" and was totally based on a deep retrospective of the basic scientific notions underlying visualization.Hanrahan started his talk putting visual thinking in the context of various systems of thoughts, that is, the tools we humans have to reason and communicate, like: natural language, logic, mathematics, etc. It was kind of shocking to see how in this context visual thinking seems less developed and weaker than the other systems.
Then the talk went on by discussing when and how visualization is better than other forms of thinking, introducing basic studies from people like Herb Simon and Donald Norman, and demonstrating that a change in representation can greatly affect the way we perceive a problem and our ability to solve it.
The talk ended with a series of key questions suggested as a way to proceed when designing a new visualization:
- What is the problem you are trying to solve?
- How do you think about the problem? What are the semantic objects and their relationships?
- What visual representations are already used? How does the visualization represent those objects and support reasoning about them?
- How can the manipulation of the representation be embodied in the interaction?
- How can visualization be coupled with other systems of thought?
They are meant to be asked in the given order and interestingly they offer a viable plan on how to proceed in visualization design. Asking about the problem first is really fundamental in my opinion because we still have too many solutions in search of problems around.
Thinking about the semantic objects in the domain of the intended users is also a key point, as well as the related need to see how currently people solve the problem.
The manipulation of the representation puts interaction at the center of the problem and give it its due role. Visualization is not only visual representation but also the great power of visual manipulation.
Last, coupling visualization with other systems of thought is really a great advice. When designing visualization there is always the risk to focus too much on the tools and overlook the whole system, tasks, and processes happening off of the screen. I'm not sure if this is what Pat intended but I think that reasoning on how visualization can be coupled with other system is in part a way to take a broader look and include the whole ecology of reasoning artifacts found around a problem.
If you want to know more I suggest to give a look the the slides (pdf). Just collecting the cited references and reading those paper would be an excellent exercise to deepen our thoughts around visualization.
Papers
This is a very short and personal selection of the papers I really liked.
Visualisation of Sensor Data from Animal Movement (pdf link), by: Edward Grundy, Mark W. Jones, Robert S. Laramee, Rory P. Wilson and Emily L.C. Shepard - This also won the best paper award. These guys have developed a system to analyze the movement of animals around the world taking data from accelerometer sensors. The quality of the final images is surprising. Lots of interesting patterns can be seen and it is not hard to imagine how useful it is for researchers using these data.
Visualization of Vessel Movements (pdf link), by: Niels Willems, Huub van de Wetering, Jarke J. van Wijk - I have to admit it, I like this paper for the beauty of the images. GPS data from vessels is collected and used to create a sort of map of water highways. A clever rendering technique is used to represent both high level overview patterns and fine details of specific routes.
The Chinese Room: Visualization and Interaction to Understand and Correct Ambiguous Machine Translation (pdf link), by: Joshua Albrecht, Rebecca Hwa, G. Elisabeta Marai - I included this paper because it is a very good example of integration between machine intelligence and human intelligence. The system uses the output of an automatic Chinese to English translator to visualize the structure of the result. The user can better understand this structure visually and rearrange the items on the screen to create better results.
