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KEMM: A Knowledge Engineering Methodology in the Medical Domain

by: Pinar Wennerberg, Sonja Zillner, Manuel Möller, Paul Buitelaar, and Michael Sintek

In: Proc. of the 5th International Conference on Formal Ontology in Information Systems FOIS (2008) .

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.

BibTeX record

@inproceedings{Wennerberg2008,
  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.},
  added-at = {2010-03-12T13:21:51.000+0100},
  author = {Wennerberg, Pinar and Zillner, Sonja and M\"oller, Manuel and Buitelaar, Paul and Sintek, Michael},
  biburl = {http://www.bibsonomy.org/bibtex/222814e4a867fab412b0023c34a21d057/manuelm},
  booktitle = {Proc. of the 5th International Conference on Formal Ontology in Information 	Systems (FOIS)},
  interhash = {ab52cb2be4cd4e175bce14e1538ec6ec},
  intrahash = {22814e4a867fab412b0023c34a21d057},
  keywords = {medico},
  timestamp = {2010-03-12T13:21:51.000+0100},
  title = {KEMM: A Knowledge Engineering Methodology in the Medical Domain},
  year = 2008
}

Endnote record

%0 Conference Paper
%1 Wennerberg2008
%A Wennerberg, Pinar
%A Zillner, Sonja
%A M\"oller, Manuel
%A Buitelaar, Paul
%A Sintek, Michael
%B Proc. of the 5th International Conference on Formal Ontology in Information 	Systems (FOIS)
%D 2008
%K 
%T KEMM: A Knowledge Engineering Methodology in the Medical Domain
%X 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.