Context-sensitive framework for visual analytics in energy production from biomass
Wartiainen, P., Heimbürger, A., & Kärkkäinen, T. (2014). Context-sensitive framework for visual analytics in energy production from biomass. In B. Thalheim, H. Jaakkola, & Y. Kiyoki (Eds.), Proceedings of the 24th International Conference on Information Modelling and Knowledge Bases - EJC 2014 (pp. 508-515). Kiel Computer Science Series (4/2014). Kiel: Kiel University. Retrieved from https://www.numerik.uni-kiel.de/~discopt/kcss/kcss_2014_04_v1.0_print....
Published in
Kiel Computer Science SeriesDate
2014Discipline
TietotekniikkaCopyright
© the Authors, the Editors & Kiel University, 2014.
Data masses require a lot of data processing. Data mining is the traditional
way to convert data into knowledge. In visual analytics, humans are integrated into
the process as there is continuous interaction between the analyst and the analysis
software. Data mining methods can be utilized also in visual analytics where the
priority is given to the visualization of the information and to dimension reduction.
However, the provided data is not always enough. There is a large amount of background
contextual information, which should be included into the automated process.
This paper describes a context-sensitive approach, in which we utilize visual
analytics by studying all phases in the process according to our ”sensing, processing
and actuation” framework. Experimental studies show that our framework can
be very useful in the process of analyzing causes for and relations between variable
changes with laboratory-scale power plant data.
Publisher
Kiel UniversityIs part of publication
Proceedings of the 24th International Conference on Information Modelling and Knowledge Bases - EJC 2014ISSN Search the Publication Forum
2193-6781Keywords
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https://www.numerik.uni-kiel.de/~discopt/kcss/kcss_2014_04_v1.0_print.pdfMetadata
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