摘要
Although significant progress has been made towards effective insight discovery in visual analytics systems, there are few effective approaches for managing the large number of insights generated in visual analytics processes. This paper presents Manylnsights, a multidimensional visual analytics prototype that integrates several novel insight management approaches proposed by the authors in their previous work. These approaches include insight annotation, browsing, retrieval, organization, and association. This paper also reports a long-term case study that evaluated Manylnsights with a domain expert, realistic analytic tasks, and real datasets.
Although significant progress has been made towards effective insight discovery in visual analytics systems, there are few effective approaches for managing the large number of insights generated in visual analytics processes. This paper presents Manylnsights, a multidimensional visual analytics prototype that integrates several novel insight management approaches proposed by the authors in their previous work. These approaches include insight annotation, browsing, retrieval, organization, and association. This paper also reports a long-term case study that evaluated Manylnsights with a domain expert, realistic analytic tasks, and real datasets.
基金
partially supported by the US National Science Foundation (Nos. 0946400 and 0915528)
the DHS Visual Analytics for Command, Control, and Interoperability (VACCINE) Center of Excellence, under the auspices of the SouthEast Regional Visual Analytics Center
