Knowledge Generation through Human-Centered Information Visualization

Author:

Einsfeld Katja1,Ebert Achim1,Kerren Andreas2,Deller Matthias3

Affiliation:

1. Computer Science Department, Visualization Lab, University of Kaiserslautern, PO BOX 3049, D-67653, Kaiserslautern, Germany

2. School of Mathematics and Systems Engineering (MSI), Växjö University, Vejdes Plats 7, Växjö, SE-351 95, Sweden.

3. Competence Center Human-Centered Visualization (HCV), German Research Center for Artificial Intelligence, DFKI GmbH, Trippstadter Strasse 122, D-67663, Kaiserslautern, Germany

Abstract

One important intention of human-centered information visualization is to represent huge amounts of abstract data in a visual representation that allows even users from foreign application domains to interact with the visualization, to understand the underlying data, and finally, to gain new, application-related knowledge. The visualization will help experts as well as non-experts to link previously or isolated knowledge-items in their mental map with new insights. Our approach explicitly supports the process of linking knowledge-items with three concepts. At first, the representation of data items in an ontology categorizes and relates them. Secondly, the use of various visualization techniques visually correlates isolated items by graph-structures, layout, attachment, integration or hyperlink techniques. Thirdly, the intensive use of visual metaphors relates a known source domain to a less known target domain. In order to realize a scenario of these concepts, we developed a visual interface for non-experts to maintain complex wastewater treatment plants. This domain-specific application is used to give our concepts a meaningful background.

Publisher

SAGE Publications

Subject

Computer Vision and Pattern Recognition

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