Scope

Ontologies defined using semantic technologies such as RDF/S or OWL can be used to precisely define the domain knowledge of a knowledge-based system. Naturally, as the number of ontologies developed increases, there comes a need for methods to integrate or align the separate ontologies. Ontology alignment algorithms can be used to establish semantic correspondences between related, but different, knowledge bases. Nonetheless, validating ontology alignment results is a challenge because it requires that the person undertaking the alignment has an in depth knowledge of both data sources.

Over the past decade a number of algorithms and techniques have been developed for aligning two or more ontologies using automated and semi-automated methods. However, it is recognised that human intervention is required to make judgments on the quality of the alignment pairs that result from such methods. Promising techniques from the information visualization community can, and have been applied, to help support such decision-making tasks in ontology alignment. Furthermore, initial studies have shown that visualization helps improve the accuracy of the alignment results.

Many challenges remain to be addressed within the broad area of ontology alignment such as: scalability, human-computer interaction, cognitive aspects, alignment accuracy, applicability of different approaches, ontology evolution, run-time requirements of semantic web services and applications, etc.

The OnAV Workshop aims to provide a forum for researchers discussing state of the art approaches to ontology management, and in particular, to investigate how information visualization techniques can be applied to support ontology alignment decision making tasks. However, we also encourage researchers and practitioners working in other areas such as ontologies for Semantic Web applications, Web2.0 and Web3.0, to submit interesting and challenging contributions.