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Semantics visualization - definition, approaches and challenges

 
: Nazemi, Kawa; Burkhardt, Dirk; Ginters, Egils; Kohlhammer, Jörn

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Fulltext ()

Procedia computer science 75 (2015), pp.75-83
ISSN: 1877-0509
International Conference on Virtual and Augmented Reality in Education (VARE) <3, 2015, Monterrey/Mexico>
English
Journal Article, Conference Paper, Electronic Publication
Fraunhofer IGD ()
visualization; simulation; semantic visualization; Business Field: Visual decision support; Research Area: Human computer interaction (HCI)

Abstract
The visualization of the simulation results must be done in conformity with beneficiaries perception and professional domain understanding. It means that right data must be identified before. Semantic technologies provide new ways for accessing data and acquiring knowledge. The underlying structures allow finding information easier, gathering meanings and associations of the data entities and associating the data to users' knowledge. Even though the focus of the research in this area is more to provide ''machine readable'' data, human-centered systems benefit from the technologies too. Especially graphical representations of the semantically structured data play a key-role in today's research. The meaningful relations of data entities and the meaningful and labeled clustering of data in form of semantic concepts enable new ways to visualize data. With these new ways, various challenges are related with deploying semantics visualizations beyond analytical search and simulation. The goal is to give a common understanding of the term semantics as it is used in semantic web.
This paper dealt with the general idea of semantics visualization. First a short introduction to semantic formalisms is given followed by a general definition. Subsequently approaches and techniques of existing semantics visualizations are presented, where-as a new classification is introduced to describe the techniques. The article concludes with future challenges in semantics visualization focusing on users, data and tasks.

: http://publica.fraunhofer.de/documents/N-389176.html