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A Distributed Infrastructure for Metadata about Metadata: The HDMM Architectural Style and PORTAL-DOORS System
Future Internet 2010, 2(3), 238-258; doi:10.3390/fi2030238

Ontology Alignment—A Survey with Focus on Visually Supported Semi-Automatic Techniques

1,* , 2
1 Know-Center GmbH, Inffeldgasse 21a, 8010 Graz, Austria 2 MIMOS Berhad Technology Park Malaysia, 57000 Kuala Lumpur, Malaysia 3 Graz University of Technology, Inffeldgasse 21a, 8010 Graz, Austria 4 ZBW, Leibniz-Information Centre for Economy, University Kiel, Düsternbrooker Weg 120, 24105 Kiel, Germany
* Author to whom correspondence should be addressed.
Received: 1 July 2010 / Revised: 27 July 2010 / Accepted: 29 July 2010 / Published: 4 August 2010
(This article belongs to the Special Issue Metadata and Markup)
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Semantic technologies are of paramount importance to the future Internet. The reuse and integration of semantically described resources, such as data or services, necessitates the bringing of ontologies into mutual agreement. Ontology alignment deals with the discovery of correspondences between concepts and relations from different ontologies. Alignment provides the key ingredient to semantic interoperability. This paper gives an overview on the state of the art in the field of visually supported semi-automatic alignment techniques and presents recent trends and developments. Particular attention is given to user interfaces and visualization techniques supporting involvement of humans in the alignment process. We derive and summarize requirements for visual semi-automatic alignment systems, provide an overview of existing approaches, and discuss the possibilities for further improvements and future research.
Keywords: ontology alignment; semantic technologies; information visualization; visual analytics ontology alignment; semantic technologies; information visualization; visual analytics
This is an open access article distributed under the Creative Commons Attribution License (CC BY) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Granitzer, M.; Sabol, V.; Onn, K.W.; Lukose, D.; Tochtermann, K. Ontology Alignment—A Survey with Focus on Visually Supported Semi-Automatic Techniques. Future Internet 2010, 2, 238-258.

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