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Interactive Visual Analytics System for Criminal Intelligence Analysts with Multiple Coordinated Views
Seokweon Jung, Donghwa Shin, Jinwook Bok, Seokhyeon Park, Hyeon Jeon, Jinwook Seo, Insoo Lee, Sooyoung Park
http://doi.org/10.5626/JOK.2023.50.1.47
Data that criminal intelligence analysts have to analyze have become much larger and more complex in recent decades. However, the environment and methods of investigation have not yet kept up with those changes. In this study, we examined current investigation practices in Korean Government Agency. We focused on the sensemaking process of investigation and tried to adopt visual analytics approaches for sensemaking into the investigation. We derived tasks and design requirements and designed a multi-view visual analytics system that could satisfy them. We validated our design with a high-fidelity prototype through a case study to show realistic use cases.
Progressive Visual Analytics Using Scagnostics and an Automatic Partitioning Variables Selection Method
DongHwa Shin, Sehi L’Yi, Hyunjoo Song, Jinwook Seo
http://doi.org/10.5626/JOK.2018.45.8.801
In this paper, we propose a visual analytics system that combines progressive visualization with a partitioning variables selection method, one of the analytic techniques based on a scagnostics concept. In order to overcome the problems of scalability and performance associated with the existing method, all of the interface elements are designed so as to update the analysis progress in real time. The interface consists of two parts: an overview of the scatterplots to be analyzed and a detailed view for exploring interesting scatterplots in detail. We introduce the design rationale of our system and present a data analysis scenario to show how users can effectively use the system.
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