This is the last lecture of the introductory part of my course where I give a very broad (and admittedly shallow) overview of some key visualization concepts I hope will stick in my students’ head. After talking about basic charts and high-information graphics I introduce dynamic visualization as visual representations that can change through user interaction.
Here are the lecture slides: Beyond Charts: Dynamic Visualization.
That’s the magic of computer graphics! The visual representation can respond and change according to our actions. Isn’t that great? Yes it is, but what is it for? This is what I asked to my students at the beginning of this class. I ask because I have the impression interaction in many visualizations comes as an afterthought: let’s put a little bit of hovering there and a nice animated zoom there. But interaction is an integral part of the well-reasoned choices a designers has to make in order to make a visualization effective, it’s not just an additional layer one can add there to add a couple of cool functions.
Interaction is the element of a visualization design that allows people to reason about data and that’s the way I presented it in class. It’s only through interaction that you can smoothly go through a long series of loops of: (1) detect something interesting in the data; (2) trigger a question; (3) change the representation in order to answer that question. Here is the (almost embarrassingly simplified) diagram I have used:
Interaction is basically about reasoning with data though many of these intricate loops, not making it cool. Even though admittedly interaction does make visualization cool. But I guess you want to go past beyond the coolness factor, right? That’s almost too easy to achieve.
Next, I introduce Donald Norman’s 7 stages of action. The model describes the stages humans go through when they interact with the world to achieve a specific goal. Here is a sketch of the model:
The model has been designed to describe things as simple as opening a door or turning on the volume of you speakers but it works equally well with complex user interfaces. The pedagogical value of the model in my opinion is that it make explicit the fact that interactive visualization is a lot about translation: (1) translating the goals we have in our head into actions and visual search tasks we perform with our hand and eyes and (2) translating (actually decoding and giving a meaning) to the changed visual representation we have in front of us after changing it through our actions. Our role as visualizations designers is to make these translations as smooth and natural as possible. Norman calls these critical points “gulf of execution” and “gulf of interpretation”. Easy and effective.
The comments I received after the lecture in our internal forum confirmed that the model does help students wrapping their head around the role of interaction in visualization so I am glad I included it. One student commented: “It is really interesting to see a process, which we all manage, unconsciously broken down to separate steps, where we can surprisingly easily relate those steps to our own experiences. ” Another one wrote: “I was really intrigued with Norman’s 7 Stages of Action. It seems like a really logical way to think holistically about interaction design.”
During the rest of my lecture I described this paper: Yi, Ji Soo, et al. “Toward a deeper understanding of the role of interaction in information visualization.” Visualization and Computer Graphics, IEEE Transactions on 13.6 (2007): 1224-1231. This is a super useful paper if you want to learn more about the role of interaction in visualization. The thing I like the most about it is that it describes interaction techniques in terms if “intent” rather than how they are implemented. I like this approach because it abstract away from the technicalities of the technique and creates a more direct connection between interaction and reasoning. These are the categories:
Mark something as interesting (Select)
Show me something else (Explore)
Show me a different arrangement (Reconfigure)
Show me a different representation (Encode)
Show me more or less detail (Abstract/Elaborate)
Show me something conditionally (Filter)
Show me related items (Connect)
If you have never read this paper I suggest you to give it a look, it’s a very good read. Another very good read on the same topic is the more recent: Heer, Jeffrey, and Ben Shneiderman. “Interactive dynamics for visual analysis.” Queue 10.2 (2012): 30. That’s a very good one too.
One of my students in the forum raised a question about complexity: by introducing all this interaction don’t we risk to make visualization too hard to use and understand? Yes, I think there is a very high risk to make things too complex and more interaction does increase the need of users to learn how to use the system. It’s wise to adopt a parsimony principe when we talk about interaction in visualization. Cramming twenty different techniques in one system for the sake of it it’s not going to work. Interaction is a dangerous tool and it must be used with great care. The best is when it blends smoothly into the visual representation and makes important questions easy to answer.
Overall I think we still have to learn a lot about interaction. Most visualizations on the web are static, and most of the interactive ones are either not very well designed or very limited. While little interaction may be necessary for visual data presentations, more rich and well-integrated interaction is crucial for analytical reasoning. If we want to help people reason about data and derive useful insights we have to better understand how to support this complex process.
That’s all for now. Thanks for reading.