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  4. From raw data to rich visualization: Combining visual search with data analysis
 
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2014
Book Article
Title

From raw data to rich visualization: Combining visual search with data analysis

Abstract
Visual analytics is an interdisciplinary field of research at the boundary between data mining, statistics and visualization. Patterns and relations in the data complement a semantic representation of knowledge on a lower level of abstraction. One important goal of visual analytics is to find relations hidden in vast amounts of data, which can be turned into useful knowledge. Analysis needs to be "visual", because human's visual cognitive abilities are important for the identification and refinement of the analytical process. Further the results of the analysis have to be presented in a way to match the user's perspective on the proposed task. However, typical users are not experts in statistics or data mining. The challenge of visual analytics is to keep domain experts in charge of the analytical process while reducing the workload due to the complexity of the techniques. While search and analysis usually are mentioned in different contexts, they are highly interdependent processes. In fact, every exploratory analysis is a search for new knowledge. In turn, this knowledge can be used to refine future searches by introducing new concepts or relations to draw from. This article will show how automated and visual methods can be combined to connect knowledge artifacts on multiple levels of abstraction.
Author(s)
May, Thorsten  
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Nazemi, Kawa
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Kohlhammer, Jörn  orcid-logo
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Mainwork
Towards the Internet of Services. The THESEUS Research Program  
DOI
10.1007/978-3-319-06755-1_16
Language
English
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Keyword(s)
  • Visual analytics

  • information visualization

  • data mining

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