This paper, like the previous three, introduces a new system of visualization for investigative analysis called JigSaw. JigSaw provides analysts with several different views for a document collection. It primarily focuses on displaying connection between entities in the documents. The authors claim that each view provides different perspective to data and thus they become the main theme of this paper.
It was interesting to know that JigSaw is actually written in Java and is based on MVC pattern. The paper provides some technical background related to JigSaw in preceding section. The focus of the article then shifts to the different views provided by JigSaw viz. –
- List View: which shows connections between sets of entities and what needs to be done based on the situation (list being too long or too short)
- Graph View : represents reports and their entities in traditional node-link graph/network visualization. JigSaw is compared here with other graph viz like the GreenLand and I would consent with the author to this point about Jigsaw handling the situation of drawing incremental view rather than depicting it on large layout.
- Scatter plot View: highlights pairwise connections between entities and there was not much new in this view that I already didn’t know about and finally,
- Text View: which is based on actual text of the reports. The authors claim that multiple reports can be loaded into one Text View and I like the idea of showing the same using multiple tabs within the same window.
The paper then describes a scenario where JigSaw was applied and its result. The paper then concludes with the limitations of the system being introduced mainly being the lack of a way to represent estimated likelihood of probability which investigative analysis often takes in consideration. Overall a descriptive reading.
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