We describe a mapping language for converting data contained in spreadsheets into the Web Ontology Language (OWL). The developed language, called M 2 , overcomes shortcomings with existing mapping techniques, including their restriction to well-formed spreadsheets reminiscent of a single relational database table and verbose syntax for expressing mapping rules when transforming spreadsheet contents into OWL. The M 2 language provides expressive, yet concise mechanisms to create both individual and class axioms when generating OWL ontologies. We additionally present an implementation of the mapping approach, Mapping Master, which is available as a plug-in for the Protégé ontology editor.

Abstract. As the volume of digital images available on the Web continues to increase, there is a clear need for more advanced techniques for their effective retrieval and management. In this paper, we present a domain independent framework for both annotating and managing images on the Semantic Web. We introduce a tool that facilitates creating and publishing OWL annotations of image content to the Semantic Web. This is loosely coupled with a Semantic Web portal with provenance tracking. We illustrate the effectiveness of this system with an implementation of the approach and describe a hypothetical use case that resulted in a proof-of-concept designed in collaboration with NASA.

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Syndication systems on the Web have attracted vast amounts of attention in recent years. As technologies have emerged and matured, there has been a transition to more expressive syndication approaches; that is, subscribers and publishers are provided with more expressive means of describing their interests and published content, enabling more accurate information filtering. In this paper, we formalize a syndication architecture that utilizes expressive Web ontologies and logic-based reasoning for selective content dissemination. This provides finer grained control for filtering and automated reasoning for discovering implicit subscription matches, both of which are not achievable in less expressive approaches. We then address one of the main limitations with such a syndication approach, namely matching newly published information with subscription requests in an efficient and practical manner. To this end, we investigate continuous query answering for a large subset of the Web Ontology Language (OWL); specifically, we formally define continuous queries for OWL knowledge bases and present a novel algorithm for continuous query answering in a large subset of this language. Lastly, an evaluation of the query approach is shown, demonstrating its effectiveness for syndication purposes.

Interest in web-based syndication systems has been growing as information streams onto the web at an increasing rate. Technologies, like the standard Semantic Web languages RDF and OWL, make it possible to create expressive representations of the content of publications and subscriptions in a syndication framework. Because these languages are based in description logics, this representation allows the application to reasoning to make more precise matching of user interests with published information. A challenge to this approach is that the consistency of the underlying knowledge base must be maintained for these techniques to work. With the frequent addition of information from new publications, it is likely that inconsistencies will arise. There are many potential mechanisms for choosing which inconsistent information to discard from the KB to regain consistency; in the case of news syndication, we argue keeping the most trusted information is important for generating the most valuable matches. Thus, in this article, we present algorithms for belief-base revision, and specifically look at the user's trust in the information sources as a metric for deciding what to keep in the KB and what to remove. 1 RSS 1.0 Specification: http://web.resource.org/rss/1.0/spec 1 L.