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.