Projects

Jigsaw
    Many people and organizations routinely perform analysis that involves large collections of documents, and in particular, textual documents. Jigsaw is a visual analytics system that helps investigators with reasoning and sense-making in such scenarios, when the investigator must consider and explore collections of unstructured and semi-structured text documents such as case reports, news articles, and suspicious activity reports. Analysts may seek to investigate an individual or incident, or they may simply be exploring with hopes to discover the unexpected. Jigsaw pairs computational analysis of the documents with a collection of visualizations that each portray different aspects of the documents, including connections between different entities. Thus, the system acts like a visual index onto a document collection, highlighting connections between entities and allowing the investigator to understand the context of events in a more timely and accurate manner. Jigsaw helps analysts "put the pieces together" and link initially unconnected activities into a more coherent story across a document collection.
Design for Intelligence Analysis
    This research seeks to inform design of visual analytics systems for intelligence analysis by understanding users, user tasks, and their tool usage. Current visual analytics research focuses on systems and techniques rather than identifying how analysts work and how systems could benefit them. For better use and appropriation of visual analytics tools, the community needs research studies that yield design implications from empirical findings. As the first step, this research aims to understand work processes and practices of intelligence analysts from a broader point of view and to identify where and how visual analytics tools can assist their tasks.
Information Visualization and Visual Analytics
    Our research focuses broadly on the areas of Information Visualization (InfoVis) and Visual Analytics (VA) that provide interactive visualizations of data to help people explore, analyze, and understand the data better and solve problems. Information visualization typically focuses on abstract data, that is, data without any agreed-upon depiction, such as financial data, text, statistics, databases, and software. Visual analytics emphasizes analytical reasoning about data and combines computational analysis techniques with interactive visualizations.