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Semantic Models for Adaptive Interactive SystemsA Semantics-Based, End-User-Centered Information Visualization Process for Semantic Web Data

Semantic Models for Adaptive Interactive Systems: A Semantics-Based, End-User-Centered... [Understanding and interpreting Semantic Web data is almost impossible for novices as skills in Semantic Web technologies are required. Thus, Information Visualization (InfoVis) of this data has become a key enabler to address this problem. However, convenient solutions are missing as existing tools either do not support Semantic Web data or require users to have programming and visualization skills. In this chapter, we propose a novel approach towards a generic InfoVis workbench called VizBoard, which enables users to visualize arbitrary Semantic Web data without expert skills in Semantic Web technologies, programming, and visualization. More precisely, we define a semantics-based, user-centered InfoVis workflow and present a corresponding workbench architecture based on the mashup paradigm, which actively supports novices in gaining insights from Semantic Web data, thus proving the practicability and validity of our approach.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

Semantic Models for Adaptive Interactive SystemsA Semantics-Based, End-User-Centered Information Visualization Process for Semantic Web Data

Part of the Human–Computer Interaction Series Book Series
Editors: Hussein, Tim; Paulheim, Heiko; Lukosch, Stephan; Ziegler, Jürgen; Calvary, Gaëlle
Voigt, Martin; Pietschmann, Stefan; Meißner, Klaus
Semantic Models for Adaptive Interactive Systems — May 14, 2013
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References (30)

Publisher
Springer London
Copyright
© Springer-Verlag London 2013
ISBN
978-1-4471-5300-9
Pages
83 –107
DOI
10.1007/978-1-4471-5301-6_5
Publisher site
See Chapter on Publisher Site

Abstract

[Understanding and interpreting Semantic Web data is almost impossible for novices as skills in Semantic Web technologies are required. Thus, Information Visualization (InfoVis) of this data has become a key enabler to address this problem. However, convenient solutions are missing as existing tools either do not support Semantic Web data or require users to have programming and visualization skills. In this chapter, we propose a novel approach towards a generic InfoVis workbench called VizBoard, which enables users to visualize arbitrary Semantic Web data without expert skills in Semantic Web technologies, programming, and visualization. More precisely, we define a semantics-based, user-centered InfoVis workflow and present a corresponding workbench architecture based on the mashup paradigm, which actively supports novices in gaining insights from Semantic Web data, thus proving the practicability and validity of our approach.]

Published: May 14, 2013

Keywords: Association Rule Mining; Recommendation Algorithm; Information Visualization; SPARQL Query; Link Open Data

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