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Visual trend analysis with digital libraries

: Nazemi, Kawa; Retz, Reimond; Burkhardt, Dirk; Kuijper, Arjan; Kohlhammer, Jörn; Fellner, Dieter W.


Lindstaedt, Stefanie (Ed.) ; Association for Computing Machinery -ACM-:
15th International Conference on Knowledge Technologies and Data-Driven Business, I-KNOW 2015. Proceedings : 21-23 October 2015, Graz
New York: ACM, 2015
ISBN: 978-1-4503-3721-2
Art. 14, 8 pp.
International Conference on Knowledge Technologies and Data-Driven Business (I-KNOW) <15, 2015, Graz>
Conference Paper
Fraunhofer IGD ()
Visual analytics; information visualization; data integration; data mining; trend analysis; information extraction; Forschungsgruppe Semantic Models, Immersive Systems (SMIS)

The early awareness of new technologies and upcoming trends is essential for making strategic decisions in enterprises and research. Trends may signal that technologies or related topics might be of great interest in the future or obsolete for future directions. The identification of such trends premises analytical skills that can be supported through trend mining and visual analytics. Thus the earliest trends or signals commonly appear in science, the investigation of digital libraries in this context is inevitable. However, digital libraries do not provide sufficient information for analyzing trends. It is necessary to integrate data, extract information from the integrated data and provide effective interactive visual analysis tools.
We introduce in this paper a model that investigates all stages from data integration to interactive visualization for identifying trends and analyzing the market situation through our visual trend analysis environment. Our approach improves the visual analysis of trends by investigating the entire transformation steps from raw and structured data to visual representations.