This paper gives an overview about the development of the field of Knowledge Engineering over the last 15 years. We discuss the paradigm shift from a transfer view to a modeling view and describe two approaches which considerably shaped research in Knowledge Engineering: Role-limiting Methods and Generic Tasks. To illustrate various concepts and methods which evolved in the last years we describe three modeling frameworks: CommonKADS, MIKE, and PROTÉGÉ-II. This description is supplemented by discussing some important methodological developments in more detail: specification languages for knowledge-based systems, problem-solving methods, and ontologies. We conclude with outlining the relationship of Knowledge Engineering to Software Engineering, Information Integration and Knowledge Management. Key WordsKnowledge Engineering, Knowledge Acquisition, Problem-Solving Method, Ontology, Information Integration IntroductionIn earlier days research in Artificial Intelligence (AI) was focused on the development of 2 formalisms, inference mechanisms and tools to operationalize Knowledge-based Systems (KBS). Typically, the development efforts were restricted to the realization of small KBSs in order to study the feasibility of the different approaches.Though these studies offered rather promising results, the transfer of this technology into commercial use in order to build large KBSs failed in many cases. The situation was directly comparable to a similar situation in the construction of traditional software systems, called "software crisis" in the late sixties: the means to develop small academic prototypes did not scale up to the design and maintenance of large, long living commercial systems. In the same way as the software crisis resulted in the establishment of the discipline Software Engineering the unsatisfactory situation in constructing KBSs made clear the need for more methodological approaches.So the goal of the new discipline Knowledge Engineering (KE) is similar to that of Software Engineering: turning the process of constructing KBSs from an art into an engineering discipline. This requires the analysis of the building and maintenance process itself and the development of appropriate methods, languages, and tools specialized for developing KBSs.Subsequently, we will first give an overview of some important historical developments in KE: special emphasis will be put on the paradigm shift from the so-called transfer approach to the so-called modeling approach. This paradigm shift is sometimes also considered as the transfer from first generation expert systems to second generation expert systems [43]. Based on this discussion Section 2 will be concluded by describing two prominent developments in the late eighties: Role-limiting Methods [99] and Generic Tasks [36]. In Section 3 we will present some modeling frameworks which have been developed in recent years:, and PROTÈGÈ-II [123]. Section 4 gives a short overview of specification languages for KBSs. Problem-solving methods have been a major research ...
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...
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