Summary:
Intelligence agencies often retrieve information from
multiple sources to anticipate and counter terrorist attacks. Often
difficulties of organizing this information arise when dealing with large
quantities of dynamically changing information. Interactive visuals tools allow
for effectively analyzing data and providing faster insight. Post Cold War
centralized terrorist organizations have been replaced by decentralized
terrorist cells that continually reinvent threats. In this case, visual
analytics in intelligence is extremely useful for identifying behaviors of
terrorist groups. For example, some of the advantages of using visual tools to
study behaviors of a network of individuals include identifying key players of
the complex network, identify emerging themes, indicate geo-spatial
relationships, and show correlations across multiple parameters.
During intelligence analysis, raw information processed
through multiple stages is transformed into actionable intelligence. According
to the authors, processing a large amount of raw material requires the use of visual
tools to track the transformation. Both evolving and complete analysis should
involve a review of the analytic process including tracking the sources of data
and their reliability, reviewing background knowledge of the scenario in
question, and analysts assumptions. Also known as provenance information,
information that is traceable is valuable when assessing the plausibility of
conclusions. Also a framework of permission management can be applied to visual
tools in an effort to manage transparency among analysis with differing
security clearances. The authors’ approach to traceability includes three
categories; data level, analysis products, and reasoning products. The
framework is based on products present in any analytic workflow. However, a
number of challenges exist in tracing provenance during intelligence analysis.
The authors suggest another framework called provenance reasoning workspace that
comprise of three spaces to reduce these challenges. The spaces include a data
space, a computation space, and a reasoning space.
Critique:
Although this article was short, it was not an easy read.
The article had a few sentence fragments and run on sentences. I had to read
some sentences a number of times to understand the content. The authors focus
was on using visual tools to keep track of the process of collecting
information to analyzing intelligence as oppose to using it as a tool that
enhances the presentation of the final product to the decision makers. Most of
the article focused on providing advantages of using visual tools to trace the
transformation of information to intelligence followed by frameworks. The
information on the article needed to be explained in more than two pages. The
authors’ framework for tracing the transformation of information into
intelligence is not very descriptive. An example or a methodology section testing
the frameworks may have shown the applicability of the frameworks.
This reminds me of the article that I summarized about
decision trees. Decision tress may not trace the process of gathering and
analyzing intelligence, but it is a tool that can visually organize data for
the analyst’s use rather than the decision maker’s. The authors’ frameworks are
prone to similar challenges of incorporating decision trees to intelligence
process. Similar to decision trees and contrary to the authors’ view, the
provenance frameworks may not be able to handle complex scenarios. It seems quite
tedious and requires the use of two different frameworks. Organizing data at
each phase will require the use of multiple tools. It also requires the
analysts to update each step when incorporating new evidence. I’m unsure of the
benefit of tracing the process of creating intelligence from the beginning to
the end in a visual manner.
Source:
Wong, W., Xu, K., & Attfield, S. (n.d.). Provenance for intelligence analysis using visual analytics.
Retrieved from http://eprints.mdx.ac.uk/8415/1/intelligence-analysis-provenance1.pdf
Posts
I disagree with the statement made by the authors claiming processing a large amount of raw material requires the use of visual tools to track the transformation. While visual tools may help not only the analyst but the decision maker see the transformation more clearly, it can still be done using traditional methods. Furthermore, I think an ideal situation would incorporate both visual tools as well as more traditional methods.
ReplyDeleteAdditionally, I think the suggestions made in the article are valid. Considering its short length an extension of the article may be useful in validating the findings of the authors.
Our topics are fairly similar with both authors wanting to show how visual analytics applies to the intelligence field. I agree that this article could have been longer in order to explain things more effectively. Additionally, where my article kind of helps your article is the fact that having traceable evidence means that someone else can pick up your project where you left off and have a good grasp of how to proceed. What I think they were trying to get at as well is that the products produced should be able to change into different forms.
ReplyDelete