Advertisement

Visualizing and Navigating Ontologies with KC-Viz

  • Enrico Motta
  • Silvio Peroni
  • José Manuel Gómez-Pérez
  • Mathieu d’Aquin
  • Ning Li
Chapter

Abstract

There is empirical evidence that current user interfaces for ontology engineering are still inadequate in their ability to reduce task complexity for users, especially non-expert ones. Here we present a novel tool for visualizing and navigating ontologies, KC-Viz, which exploits an innovative ontology summarization method to support a “middle-out ontology browsing” approach, where it becomes possible to navigate ontologies starting from the most information-rich nodes (i.e., key concepts). This approach is similar to map-based visualization and navigation in geographical information systems, where, e.g., major cities are displayed more prominently than others, depending on the current level of granularity. Building on its powerful and empirically validated ontology summarization algorithm, KC-Viz provides a rich set of navigation and visualization mechanisms, including flexible zooming into and hiding of specific parts of an ontology, visualization of the most salient nodes, history browsing, saving and loading of customized ontology views, as well as essential interface support, such as graphical zooming, font manipulation, tree layout customization, and other functionalities.

Keywords

Class Abstract Ontology Engineering Spatial Entity Sensemaking Process Flexible Exploration 
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.

Notes

Acknowledgments

This work was partially supported by funding from the European Commission, in the context of the NeOn and SmartProducts projects. The paper has benefited greatly from many insightful comments from Pierluigi Miraglia, who kindly suggested both ways to improve the presentation of this work as well as interesting new directions for future research.

References

  1. d’Aquin M, Sabou M, Motta E (2008) Reusing knowledge from the semantic web with the Watson Plugin. Demo at the 2008 international semantic web conference, Karlsruhe, GermanyGoogle Scholar
  2. Dzbor M, Motta E, Buil Aranda C, Gómez-Pérez JM, Goerlitz O, Lewen H (2006) Developing ontologies in OWL: an observational study. Workshop on OWL: experiences and directions, Athens, GA, USA, Nov 2006Google Scholar
  3. Katifori A, Halatsis C, Lepouras G, Vassilakis C, Giannopoulou E (2007) Ontology visualization methods—a survey. ACM Comput Surv 39(4):Art.10CrossRefGoogle Scholar
  4. Peroni S, Motta E, d’Aquin M (2008) Identifying key concepts in an ontology through the integration of cognitive principles with statistical and topological measures. In: Third Asian Semantic Web Conference, Bangkok, ThailandGoogle Scholar
  5. Plaisant C, Grosjean J, Bederson BB (2002) Spacetree: supporting exploration in large node link tree, design evolution and empirical evaluation. In: Proceedings of the international symposium on information visualization, 2002Google Scholar
  6. Rosch E (1978) Principles of categorization. In: Cognition and categorization. Lawrence Erlbaum, HillsdaleGoogle Scholar
  7. Shneiderman B (1992) Tree visualization with tree-maps: a 2d space-filling approach. ACM Trans Graph 11(1):92–99, 15zbMATHCrossRefGoogle Scholar
  8. Shneiderman B (1996) The eyes have it: a task by data type taxonomy for information visualizations. In: Proceedings of the 1996 IEEE symposium on Visual Languages (VL 1996), Boulder, CO, USA. IEEE Computer Society, Washington, DC, USAGoogle Scholar
  9. Souza K, Dos Santos A, Evangelista SRM (2003) Visualization of ontologies through hypertrees. In: Proceedings of the Latin American conference on Human-computer interaction, 2003, p 251–255Google Scholar
  10. Tartir S, Arpinar IB, Moore M, Sheth AP, Aleman-ÙMeza B (2005) OntoQA: Metric-based ontology quality analysis. In Proceedings of the IEEE Workshop on Knowledge Acquisition from Distributed, Autonomous, Semantically Heterogeneous Data and Knowledge Sources, co-located with the 5th IEEE International Conference on Data Mining (ICDM 2005). November 27, 2005, Huston, Texas, USAGoogle Scholar
  11. Wang TD, Parsia B (2006) Cropcircles: topology sensitive visualization of owl class hierarchies. In: Proceedings of the 5th International Semantic Web Conference 2006, Athens, GA, USAGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Enrico Motta
    • 1
  • Silvio Peroni
    • 2
  • José Manuel Gómez-Pérez
    • 3
  • Mathieu d’Aquin
    • 1
  • Ning Li
    • 1
  1. 1.Knowledge Media Institute (KMi)The Open UniversityMilton KeynesUK
  2. 2.Department of Computer ScienceUniversity of BolognaBolognaItaly
  3. 3.Intelligent Software Components (iSOCO)MadridSpain

Personalised recommendations