III: Small: Supporting Investigative Analysts and Researchers in Sense-making across Large Document Collections through Visual Analytics

Georgia Tech Research Corporation, Atlanta GA

Investigators

Abstract

People routinely encounter and seek to make sense of large collections of data that include both unstructured reports or stories and loosely-structured logs or spreadsheets. In many cases, information of relevance is scattered about a large number of documents and it is the task of an analyst to read the documents and "put the pieces together." For instance, police investigators when sifting through a multitude of observations, case reports, and witness testimonies must develop a coherent view of the events that really occurred. Academic researchers investigating a new domain pour over large numbers of paper abstracts, citations, and articles to develop a better understanding of the state of work in that area. The process of connecting individual pieces of information such as those discussed above into a more coherent narrative is a component of investigative analysis, the main focus of this project. One common element of analytic sense-making activities is that they are cognitively very challenging, frequently involving large collections of data that tax a person's memory, deduction, reasoning, and general analytic capabilities. Investigative analysis today is made even more challenging by the ever-increasing torrent of data available in a world where one can access vast databases and conduct internet searches that in seconds return a quantity of documents no human can read and assimilate in a reasonable amount of time. But technological means of augmenting human memory and analytic reasoning hold great potential as investigative aids. This project explores the development of computational systems to make investigative analysts more effective and more efficient. The PI's approach centers on providing multiple visual representations of the individual pieces of data gathered during the investigation, to help highlight connections or potential connections among them and to help analysts determine the next pieces of data to examine from a large collection of evidence. The PI will draw upon his experience in information visualization and visual analytics to design and create a system to help analysts, and upon his experience in human-computer interaction to evaluate whether the system is effective. The work will include fundamental research on challenges such as the representation of reliability and uncertainty in a visualization display, the development of collaborative system capabilities so that analysts can work together, and the integration of sophisticated automated textual analysis capabilities with the human-directed exploration approach that visual interfaces provide. Careful evaluation of all the new analytic capabilities will accompany their design as well. Broader Impacts: Investigative analysis is a fundamental activity in law enforcement and in intelligence activities that are important to our national security. This project will invent next-generation visual analytic techniques and technologies that can be used to develop investigative analysis systems in the future. Other domains such as news reporting, academic research, and business intelligence also require investigative analysis, so this project has the potential to impact those fields as well.