Since information visualization has become increasingly vital to experts, it is now important to enable information visualization novices to consume, construct, and coordinate visualizations as well. Choosel is a web-based environment that aims at facilitating flexible visual data exploration for information visualization novices. It supports the iterative construction of multiple coordinated views during the visual data analysis process. A preliminary user study with 8 participants indicated that multiple windows, enhanced drag and drop interaction, and highlighting of items and sets, in particular, support novices in the visual data exploration process in a useful and intuitive way.
Download Poster Abstract (2 pages)08 September 2010
Choosel Poster at InfoVis 2010
22 July 2010
How Information Visualization Novices Construct Visualizations
Together with Melanie Tory and Margaret-Anne Storey, I investigated how information visualization novices construct visualizations in a laboratory setting. Our research paper "How Information Visualization Novices Construct Visualizations" was accepted for presentation at IEEE InfoVis 2010.
Here is the abstract of our paper:
It remains challenging for information visualization novices to rapidly construct visualizations during exploratory data analysis. We conducted an exploratory laboratory study in which information visualization novices explored fictitious sales data by communicating visualization specifications to a human mediator, who rapidly constructed the visualizations using commercial visualization software.
We found that three activities were central to the iterative visualization construction process: data attribute selection, visual template selection, and visual mapping specification. The major barriers faced by the participants were translating questions into data attributes, designing visual mappings, and interpreting the visualizations. Partial specification was common, and the participants used simple heuristics and preferred visualizations they were already familiar with, such as bar, line and pie charts.
From our observations, we derived abstract models that describe barriers in the data exploration process and uncovered how information visualization novices think about visualization specifications. Our findings support the need for tools that suggest potential visualizations and support iterative refinement, that provide explanations and help with learning, and that are tightly integrated into tool support for the overall visual analytics process.
14 April 2010
Supporting End Users in Coordinating Multiple Visualizations
I presented the tool and the results (see poster and presentation below) at the IBM University Days 2010. A version of the visual analytics environment that is tailored to exploring biomedical ontologies is available at: bio-mixer.appspot.com