Monday, November 28, 2011

Jigsaw: Supporting Investigative Analysis through Interactive Visualization

This paper discusses the initial Jigsaw system for visualizing textual data in a variety of ways.  The system attempts to take a collection of reports and select entities (people, place, date, organization) from the text and determine connections between entities.  The system targets smaller reports to provide an interactive visualization that provides data about connections and allows analysts to browse and explore reports and information.  The system tries to provide multiple ways for analysts to see the data.  The first is a double column list with space in the middle for connecting links to be drawn.  Each columns can be sorted independently to provide different ways of clumping the data.  Also provides a graph view with entities as bubbles and lines drawn as connections that is effective for small to moderate size data sets.  The scatter plot appears busy and the data easily gets squished down to a hard to read state.  The text view provides an interesting view by allowing the raw report to be viewed with highlighted words that groups by colors.

This paper does a good job of exploring and examining the flaws in the system at its current state as well as the papers thoroughness.  First off, is that as the number of reports grows the ability to trace connections and relevant information becomes difficult.  Also, a collection must initially be static and at the current time of the paper could not adapt to adding in new reports.  The authors themselves propose ideas that I myself had while reading such as the ability for analysts to write and store notes and thoughts and to provide crowd source annotations about different data visualizations.  This system when written was a good first step into a difficult world of analytic text visualization.  I would be interested in how it has evolved over time.