In the context of the needs of the Semantic Web and Knowledge Management, we consider what the requirements are of ontologies. The ontology as an artifact of knowledge representation is in danger of becoming a Chimera. We present a series of facts concerning the foundations on which automated ontology construction must build. We discuss a number of different functions that an ontology seeks to fulfill, and also a wish list of ideal functions. Our objective is to stimulate discussion as to the real requirements of ontology engineering and take the view that only a selective and restricted set of requirements will enable the beast to fly. 1.

Abstract. We discuss our DLDB knowledge base system and evaluate its capability in processing a very large set of real-world Semantic Web data. Using DLDB, we have constructed the Hawkeye knowledge base, in which we have loaded more than 166 million facts from a diverse set of real-world data sources. We use this knowledge base to demonstrate realistic integration queries in egovernment and academic scenarios. In order to support Hawkeye, we extended DLDB with additional reasoning capabilities. At present, the Semantic Web consists of numerous independent ontologies. We demonstrate that OWL can be used to integrate these ontologies and thereby integrate the data sources that commit to them. In terms of performance, we show that the load time of our system is linear on the number of triples loaded. Furthermore, we show that many complex queries have response times under one minute, and that simple queries can be answered in seconds. 1

Abstract not found

Abstract. Web 2.0, not the Semantic Web, has become the face of “the next generation Web ” among the tech-literate set, and even among many in the various research communities involved in the Web. Perceptions in these communities of what the Semantic Web is (and who is involved in it) are often misinformed if not misguided. In this paper we identify opportunities for Semantic Web activities to connect with the Web 2.0 community; we explore why this connection is of significant benefit to both groups, and identify how these connections open valuable research opportunities “in the real ” for the Semantic Web effort.

Abstract. Research into tools to support both quantitative and qualitative analysis of specialist knowledge domains has been undertaken within the two broadly independent traditions of Bibliometrics and Knowledge Management. The ‘knowledge domain analysis ’ (KDA) tools within the first tradition follow a citation-based approach to representing knowledge domains and use citation links as the basis for identifying patterns in the relationships among authors and publications. KDA tools within the second, more recent tradition extend the representational scope to include more features of knowledge domains such as the various types of agents in the domain, their intellectual affiliations, and their research activities, all with the aim of enabling more precise queries about the domains. This second approach depends on the development of software artefacts called ontologies, which are used to explicitly define schemes for representing knowledge domains as well as inference rules to facilitate querying. However, current research into ontologies of scholarly domains has not as yet emphasised the key role of ontologies as vehicles for reuse. This report investigates the design

For guidance on citations see FAQs. c ○ [not recorded] Version: [not recorded] Link(s) to article on publisher’s website: