In safety-critical IT projects, the success of which is crucial to public safety, the failure of an IT system can have far-reaching consequences. In practice, however, the reuse of valuable experience-based knowledge, which is often available in natural language and on different IT systems or in physical documents, poses a considerable challenge. If this experience-based knowledge is not taken into account, the consequences can be serious and lead to high additional costs and considerable project delays. One possible approach to solving these problems lies at the interface of business administration, business informatics and computer science. This approach combines the previously separate disciplines of project management, knowledge management and artificial intelligence (AI). It shows how proven “traditional” AI techniques, especially ontologies and case-based reasoning, can be used effectively in safety-critical IT projects. By combining ontology-supported case-based reasoning with artificial neural networks for the “modern” Word2Vec technique, a cloud-based software is designed that can be used to significantly improve the reuse of experience-based knowledge in safety-critical IT projects.
The article presented here shows how the combination of traditional and modern AI techniques can provide a key to the systematic reuse of mission-critical experience-based knowledge in IT projects.
Mr. Jan Peter Schagen, M.Sc., was a research assistant at the Institute for Production and Industrial Information Management and is doctoral student at the Faculty of Economics of the University of Duisburg-Essen. He studied Business Administration (B.Sc.) at the University of Duisburg-Essen, Campus Essen, followed by a Master’s degree in Markets and Companies (M.Sc.). As part of his work as a research assistant, he was involved in the joint project KI-LiveS, which aimed to transfer techniques from artificial intelligence research into business practice. His dissertation project focuses on the "intelligent" reuse of empirical knowledge in project management using ontology-supported case-based reasoning with a particular focus on the design, implementation and evaluation of adaptation rules for an ontologysupported case-based reasoning system.
Mr. Stephan Zelewski, PhD., was Professor of Business Administration and Director of the Institute for Production and Industrial Information Management at the Faculty of Economics at the University of Duisburg-Essen (until November 2024). He studied business administration and economics (Dipl.-Kfm., Dipl.-Volksw.) at the Universities of Münster and Cologne. In 1985, he received his doctorate from the University of Cologne with a thesis on the business application potential of artificial intelligence. After his habilitation on structuralist production theory, he was Professor of Business Administration and Director of the Institute for Production Management and Industrial Information Management at the University of Leipzig from 1993 to 1998. Mr. Zelewski’s main areas of work are, on the one hand, issues of computer-aided production management at the interface between business administration and business informatics with a focus on project management, logistics, supply chain management and production planning and control. On the other hand, he is intensively involved in the transfer of findings from research into artificial intelligence to economic problems, particularly with regard to knowledge-based systems, ontologies and case-based reasoning.
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