Slides of InfoVis 2010 presentation "How Information Visualization Novices Construct Visualizations"

I presented the paper "How Information Visualization Novices Construct Visualizations" at IEEE InfoVis 2010 in Salt Lake City. Here are my slides:

Choosel at VisWeek 2010 and at CASCON 2010

Interested in data visualization on the web? There are several Choosel-related events at VisWeek 2010, CSER and CASCON 2010. Choosel is an open-source framework for browser-based data visualization.

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Oct 24-28, I will present the InfoVis poster "Choosel – Web-based Visualization Construction and Coordination for Information Visualization Novices" at VisWeek 2010. Here is a preview:

Oct 31st, there will be a presentation on Choosel and the Work Item Explorer at CSER. The Work Item Explorer (developed by Patrick Gorman, Del Myers and Christoph Treude) is a research prototype built on Choosel that facilitates the flexible, iterative exploration of Jazz data, focusing primarily on work items.

Nov 1-4, there will be CASCON exhibits on Choosel and the Work Item Explorer. The Choosel exhibit (Bradley Blashko, Lars Grammel) will be at booth X2 near the Central Tower, and the Work Item Explorer exhibit (Patrick Gorman, Christoph Treude) will be at booth U5. The exhibits are open 5pm to 7pm on Monday (Nov 1), from 8.30am to 7pm on Tuesday and Wednesday (Nov 2 and 3), and from 8.30am to 1pm on Thursday (Nov 4).

Choosel Poster at InfoVis 2010

I will present a poster on the Choosel Framework at IEEE InfoVis 2010. The main goal of the Choosel project is to enable software developers and researchers to easily create web-based visual data exploration environments for novices. The poster paper briefly summarizes some of the related work, the features of Choosel, and the results of a prelimary usability evaluation:

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)

How Information Visualization Novices Construct Visualizations

Visualization for the masses is a topic that has gained a lot of attraction in the InfoVis community in recent years, e.g. in projects such as IBM ManyEyes. The goal is to enable a wide user population to leverage information visualization technology to understand large amounts of data. This could potentially help them make more informed decisions, and is especially promising as more and more data becomes available (see open data). However, there are still many challenges that need to be addressed so that visualization for the masses can become a reality, ranging from limited visual literacy to insufficient tool support.

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.

Download Technical Report