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Ontology visualization methods and tools: a survey of the state of the art

Published online by Cambridge University Press:  20 July 2018

Marek Dudáš ,
Steffen Lohmann ,
Vojtěch Svátek Open the ORCID record for Vojtěch Svátek [Opens in a new window]  and
Dmitry Pavlov
Marek Dudáš
Affiliation:
University of Economics, Prague, W. Churchill Sq. 1938/4, 130 67 Prague 3 - Žižkov, Czech Republic; e-mail: marek.dudas@vse.czsvatek@vse.cz
Steffen Lohmann
Affiliation:
Fraunhofer Institute for Intelligent Analysis and Information Systems (IAIS), Schloss Birlinghoven, 53757, Sankt Augustin, Germany e-mail: steffen.lohmann@iais.fraunhofer.de
Vojtěch Svátek
Affiliation:
University of Economics, Prague, W. Churchill Sq. 1938/4, 130 67 Prague 3 - Žižkov, Czech Republic; e-mail: marek.dudas@vse.czsvatek@vse.cz
Dmitry Pavlov
Affiliation:
IITMO University, 49 Kronverksky Pr., St. Petersburg, 197101, Russia e-mail: dmitry.pavlov@vismart.biz
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Abstract

Various ontology visualization tools using different visualization methods exist and new ones are being developed every year. The goal of this paper is to follow up on previous surveys with an updated classification of ontology visualization methods and a comprehensive survey of available tools. The tools are analyzed for the used visualization methods, interaction techniques and supported ontology constructs. It shows that most of the tools apply two-dimensional node-link visualizations with a focus on class hierarchies. Color and shape are used with little variation, support for constructs introduced with version 2 of the OWL Web Ontology Language is limited, and it often remains vague what tasks and use cases are supported by the visualizations. Major challenges are the limited maturity and usability of many of the tools as well as providing an overview of large ontologies while also showing details on demand. We see a high demand for a universal ontology visualization framework implementing a core set of visual and interactive features that can be extended and customized to respective use cases.

Type
Survey Article
Information
The Knowledge Engineering Review , Volume 33 , 2018 , e10
Copyright
© Cambridge University Press, 2018 

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