Andreas Abecker Knowledge Management Research Group From Hypermedia Information Retrieval to Knowledge Management in Enterprises Andreas Abecker, Michael Sintek, and Holger Wirtz German Research Center for Artificial Intelligence (DFKI) GmbH First International Symposium on Multimedia & Image Processing (IFMIP’98) May 1998, Anchorage, Alaska, USA

Andreas Abecker Knowledge Management Research Group IT Support for Knowledge Management Our Approach: Context-Sensitive Information Supply Information Modeling Issues Summary and Further Work IT Support for Knowledge Management Our Approach: Context-Sensitive Information Supply Information Modeling Issues Summary and Further Work Outline

Andreas Abecker Knowledge Management Research Group Knowledge Management and Organizational Learning are emerging paradigms in industry – shorter product life cycles, lean organizational structures, concurrent engineering efforts, globally dispersed virtual enterprises, enterprise reengineering, make knowledge management an urgent need for enterprises – managers are biased towards non-technological issues, like human resource management, cultural aspects, organizational changes etc. – several IT communities recently „discovered“ the area: workflow systems, CSCW, expert systems, case-based reasoning, intranets, data mining, document management systems, are considered to be useful for KM CURRENT SITUATION However, a commonly agreed-upon approach and methodology is still lacking.

Andreas Abecker Knowledge Management Research Group Basically, research on Organizational Memory can concentrate on knowledge explication, or on knowledge capitalization – explication of tacit knowledge: –the typical expert system approach –[KühnAbecker97]: cost-benefit problems –[Rittel72],[Buckingham Shum 97]: feasibility for “wicked problems”? –[DavenportJarvenpaa+96]: construction and maintenance problems TWO COMPLEMENTARY APPROACHES We concentrate on the second goal. – capitalization on implicit and existing explicit knowledge: –existing documents and knowledge sources often severely underutilized –ease finding, access, and exploitation –increase utilization potential

Andreas Abecker Knowledge Management Research Group Practical solutions require different degrees of formalization – Ensure the utilization of “formal” organizational knowledge: business rules, design guidelines, standard procedures, can be formalized to allow automatic processing – Enable sharing and reuse of experiences: lessons learned, best practice reports, case bases, can be stored as semi-structured electronic documents – Ease the exploitation of implicit knowledge, personal knowledge, and knowledge contained in documents and databases technical documentation, hypertexts, personal notes, minutes of meetings, graphics, images, product data sheets, business letters, must be effectively accessible OBJECTIVES OF AN ORGANIZATIONAL MEMORY How can several kinds of knowledge synergetically interact?

Andreas Abecker Knowledge Management Research Group We propose a three-layered model for context-sensitive, active knowledge supply Intelligent multimedia information retrieval enables powerful support. domain ontology enterprise ontology information ontology support information processing and retrieval process application level knowledge description level object level

Andreas Abecker Knowledge Management Research Group IR maps information need descriptions to knowledge item descriptions – [vanRijsbergen89] identified the three basic constituents of intelligent information retrieval: –a semantic representation of documents –a semantic representation of queries –an inference procedure mapping the latter one onto the former ones – logic-based formalisms have a clear semantics and powerful processing mechanisms which can incorporate background knowledge LOGIC-BASED INFORMATION RETRIEVAL In this talk, we focus on information modeling issues.

Andreas Abecker Knowledge Management Research Group Ontologies organize information models and background knowledge – information ontology: –kinds of information sources –logical structure -> relevance propagation –meta properties (reliability, message type, availability, creation context, intended usage context) –link to information content – enterprise ontology: –provides usage and creation context –basis for BPMs –enterprise organizational structure – domain ontology / thesaurus: –description of information content –natural language expressions linked to formal concepts –usually incomplete Information Ontology Domain Ontology Enterprise Ontology content context DIMENSIONS OF INFORMATION MODELING We extended standard modeling approaches by the context dimension.

Andreas Abecker Knowledge Management Research Group A First Version of the Required Ontologies has Already Been Prepared information group expertise personal expertise document section title book article information ontology company department employee enterprise ontology keyword s-p-o content thing domain ontology / thesaurus isa uses part of instance of object link rule message type Our scenario still provides a number of interesting research questions. Our scenario still provides a number of interesting research questions.

Andreas Abecker Knowledge Management Research Group We specified just the frames, not yet the content – stable and practically useful versions of reusable ontologies (information ontology) – conceptually clear content modeling – (semi-) automatic acquisition of knowledge descriptions – special knowledge representation formalisms for knowledge descriptions – semantically sound, yet efficient inference procedures OPEN RESEARCH TOPICS Nevertheless, applications already yield promising results.

Andreas Abecker Knowledge Management Research Group – IT support for Knowledge Management and Organizational Learning is an emerging, still open research topic. – We propose intelligent assistance for knowledge-intensive tasks which is based on context-sensitive, acitve information supply. – Information supply essentially amounts to a demanding multimedia and hypermedia retrieval task. – We propose ontolog-based information modeling with special focus on the context dimension and information meta properties. – Though the framework still provides many fundamental questions, pragmatically designed prototypes already yield promising results. SUMMARY