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Revision with unchanged content. Information visualization is applied in many fields to gain faster insights with lighter user cognitive loads in analyzing large sets of data. To select the right visualization tool, there are a number of visualization evaluation methods currently available. However, these evaluation methods are often limited by the appropriateness of tools for a given domain since they are not evaluating according to tools´ intended use. Current methods conduct evaluations in a laboratory environment with "benchmark" tasks, often not aligned with the intended use. Intended use evaluation approach captures the key activities that will use the visual technology to calibrate the evaluation criteria toward these first-order needs. This book presents the results from an investigation into an intended use evaluation approach and its effectiveness of measuring domain specific information visualization tools. While the observations from this research are compelling for the intelligence community, the principles of the evaluation approach should apply to a wider range of visualization technologies. All the design rationales and processes were captured in this book.

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MS: Computer Science and Applications at Virginia Tech. Researcher at Information Security Research and Development Center, Seoul, S. Korea.

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