This demo introduces WorkItemExplorer, an interactive environment to visually explore data from software development tasks. WorkItemExplorer enables developers and managers to investigate activity and correlations in their task management system by making data exploration flexible and interactive, and by utilizing multiple coordinated views. Our preliminary evaluation shows that WorkItemExplorer is able to answer questions that developers ask, while also enabling them to gain new insights through the free exploration of data.

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. We derived abstract models from our observations 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.

We explore how to support the creation of customized visualizations of ontology instance data through the specification of ontology mappings. We combine technologies from the disciplines of software modeling and ontology engineering. The feasibility of our approach is demonstrated by extending an existing ontology mapping tool, CogZ, to translate ontology mappings into software model transformation rules. The tool uses these transformations to automatically convert domain instance data into data that conforms to a model describing a visualization. After this transformation, a visualization of the domain instance data is generated.

The analysis of data from multiple sources promises rich insights into complex phenomena. However, such an analysis requires data integration, which remains difficult for users without programming skills. In order to enable those users to perform ad-hoc data analysis of multiple data sources, we are researching their cognitive support needs and developing tools that provide appropriate cognitive support for this task. As part of this, we are exploring a widget-centric data integration and analysis approach.