Ontobroker: Ontology Based Access to Distributed and Semi-Structured Information

Abstract

The World Wide Web (WWW) can be viewed as the largest multimedia database that has ever existed. However, its support for query answering and automated inference is very limited. Metadata and domain specific ontologies were proposed by several authors to solve this problem. We developed Ontobroker which uses formal ontologies to extract, reason, and generate metadata in the WWW. The paper describes the formalisms and tools for formulating queries, defining ontologies, extracting metadata, and generating metadata in the format of the Resource Description Framework (RDF), as recently proposed by the World Wide Web Consortium (W3C). These methods provide a means for semantic based query handling even if the information is spread over several sources. Furthermore, the generation of RDF descriptions enables the exploitation of the ontological information in RDF-based applications. INTRODUCTIONIn more and more application areas large collections of digitized multimedia information are gathered and have to be maintained (e.g. in medicine, chemical applications or product catalogs). Therefore, there is an increasing demand for tools and techniques supporting the management and usage of digital multimedia data. Especially the World Wide Web (WWW) can be regarded as the largest multimedia database that ever existed and every day more and more data is available through it. Its support for retrieval and usage is very limited because its main retrieval services are keyword-based search facilities carried out by different search engines, web crawlers, web indices, man-made web catalogs etc. Given a keyword, such services deliver a set of pages from the 351 352 SEMANTIC ISSUES IN MULTIMEDIA SYSTEMS web that use this keyword. Ontologies and metadata (based on ontologies) are proposed as a means for retrieving and using multimedia data [4] [32]. They provide "an explicit specification of a conceptualization" [16] and are discussed in the literature as means to support knowledge sharing and reuse [9] [14]. This approach to reuse is based on the assumption that if a modeling scheme -i.e. an ontology-is explicitly specified and agreed upon by a number of agents, it is then possible for them to share and reuse knowledge. Clearly, it is unlikely that there will be a common ontology for the whole population of the WWW and every subject. This leads to the metaphor of a newsgroup or domain specific ontology [19] [26] to define the terminology for a group of people which share a common view on a specific domain. Using ontologies for information retrieval has certain advantages over simple keyword based access methods: An ontology provides a shared vocabulary for expressing information about the contents of·(multimedia) documents. In addition, it includes axioms for specifying relationships between concepts. Such an ontology may then in turn be used to formulate semantic queries and to deliver exactly the information we are interested in. Furthermore, the axioms provide a means for deriving information which has been specified o...

Temporalizing Ontology-Based Data Access

“…Ontology-based data access [11,17] addresses these requirements. The fact base is viewed to be a Description Logic ABox (which is not interpreted with the CWA), and an ontology, also formulated in an appropriate DL, constrains the interpretations of unary and binary predicates, called concepts and roles in the DL community.…”

Leveraging Semantic Technologies towards Social Ambient Intelligence

“…The CoOL integration is an extension of the core to inter-operate with web services. OntoBroker (Decker, Erdmann, Fensel, & Studer, 1999) was chosen for semantic inference and reasoning, supporting F-Logic as knowledge representation and query language.…”

Methodologies, tools and languages for building ontologies. Where is their meeting point?

“…It is similar to the previous tools: it is an extensible and flexible environment, based on a plugin architecture, which provides functionality to browse and edit ontologies. It includes plugins that are in charge of inferring using Ontobroker [14], of exporting and importing ontologies in different formats (FLogic, XML, RDF(S), DAML þ OIL), etc. Two versions of OntoEdit are available: OntoEdit Free and OntoEdit Professional.…”

“…We can say that the Ontolingua Server and Prote ege e 2000 do not have an inference engine. OILEd performs inferences using FACT inference engine [39], OntoEdit uses Ontobroker [14], Ontosaurus uses the Loom classifier [54], WebODE uses Ciao Prolog [37] and WebOnto uses OCML [56]. Besides, Ontosaurus and WebODE provide evaluation facilities.…”

“…FLogic is the only of the previous languages that do not have Lisp-like syntax. Its inference engine, Ontobroker [14], can be used for constraint checking and deducting new information.…”