A Semantics-Based, End-User-Centered Information Visualization Process for Semantic Web Data

  • Martin VoigtEmail author
  • Stefan Pietschmann
  • Klaus Meißner
Part of the Human–Computer Interaction Series book series (HCIS)


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.


Association Rule Mining Recommendation Algorithm Information Visualization SPARQL Query Link Open Data 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag London 2013

Authors and Affiliations

  • Martin Voigt
    • 1
    Email author
  • Stefan Pietschmann
    • 1
  • Klaus Meißner
    • 1
  1. 1.TU DresdenDresdenGermany

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