KEMM: A Knowledge Engineering Methodology in the Medical Domain

  • Authors:

  • Pinar Wennerberg;Sonja Zillner;Manuel Möller;Paul Buitelaar;Michael Sintek

  • Affiliations:

  • Siemens AG, Corporate Technology, Munich, Germany;Siemens AG, Corporate Technology, Munich, Germany;DFKI GmbH, Knowledge Management Dept., Kaiserslautern, Germany;DFKI GmbH, Language Technology Lab, Saarbrücken, Germany;DFKI GmbH, Knowledge Management Dept., Kaiserslautern, Germany

  • Venue:
  • Proceedings of the 2008 conference on Formal Ontology in Information Systems: Proceedings of the Fifth International Conference (FOIS 2008)
  • Year:
  • 2008

Quantified Score

Hi-index 0.00

Visualization

Abstract

Medical research and clinical practice deal with complex and heterogeneous data. This requires a systematic approach for semantic integration of information to support clinicians in their daily tasks. As the clinicians speak and think in a very different language than that of the computer scientists, existing knowledge engineering approaches based on classical expert interviews fall short. Moreover, as human health is a very sensitive subject, the reuse of standardized hence reliable ontologies as medical knowledge resources becomes a key requirement. In this paper, we first discuss the specific medical knowledge engineering requirements, we identified along a semantic medical image and text retrieval use case. Then we report on ongoing work towards establishing a corresponding methodology based on ontology reuse that is derived from the requirements. The methodology, which will be discussed in detail, relies on a novel technique for semi-automatically generating a set of potential user queries to support the knowledge elicitation process.