This week I attended a high energy ISP seminar on Human-Data Interaction by Saman Amirpour. Saman is an ISP graduate student who also works with the CREATE Lab. His work in progress project on the Explorable Visual Analytics tool serves as a good introduction to this post:
While this may have some resemblance with other projects such as the famous Gapminder Foundation led by Hans Rosling, Saman presented a bigger picture in his talk and provided motivation for the emergence of a new field: Human-Data Interaction.
Big data is a term that gets thrown around a lot these days and probably needs no introduction. There are three parts of the big data problem, involving data collection, knowledge discovery and communication. Although we are able to collect massive amounts of data easily, the real challenge lies in using it to our advantage. Unfortunately, we do not enough sophistication in our machine learning algorithms that can handle this as yet. You really can’t do without the human in the loop for making some sense of the data and asking intelligent questions. And as this Wired article points out, visualization is the key for allowing us humans to do this. But, our present-day tools are not well suited for this purpose and it is difficult to handle high dimensional data. We have a tough time to intuitively understand such data. For example, try visualizing a 4D analog of a cube in your head!
So now the relevant question that one could ask is that if Human-data interaction (or HDI) really any different from the long existing areas of visualization and visual analytics? Saman suggests that HDI addresses much more than visualization alone. It involves answering 4 big questions on:
- Steering To help in navigate the high dimensional space. This is the main area of interest for researchers in the visualization area.
But we also need to solve problems with:
- Sense-making i.e. how can we help the users to make discoveries from the data. Sometimes, the users may not even start with the right questions in mind!
- Communication The data experts need a medium to share their models that can in-turn allow others to ask new questions.
- And finally, all of this needs to be done after solving the Technical challenges in building the interactive systems that support all of this.
Tools that can sufficiently address these challenges are the way to go in future. They can truly help the humans in their sense-making processes by providing them with responsive and interactive methods to not only test and validate their hypotheses but also communicate them.
Saman devoted the rest of the talk to demo some of the tools that he contributed towards and gave some examples of beautiful data visualizations. Most of them were accompanied by a lot of gasping sounds from the audience. He also presented some initial guidelines for building HDI interfaces based on these experiences.
interesting to see other definitions of HDI arising — we’ve written a little about HDI as well 🙂 http://ssrn.com/abstract=2508051
see http://hdiresearch.org/ for more.
mort
Thanks for your links! I have browsed through them and it looked interesting. I have bookmarked them for studying later.