Methods Inf Med 1998; 37(04/05): 501-509
DOI: 10.1055/s-0038-1634547
Original Article
Schattauer GmbH

Thesauri and Formal Classifications: Terminologies for People and Machines

A. L. Rector
1   Medical Informatics Group, Department of Computer Science University of Manchester, Manchester, UK
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Publikationsdatum:
15. Februar 2018 (online)

Abstract

Terminologies are now software. They are key components of the integration of electronic patient records, decision support systems and information retrieval systems. To be used as software, the different types of content in traditional terminologies must be separated, which we term here: conceptual, linguistic, inferential and pragmatic. The conceptual knowledge at the heart of the terminology needs to be expressed formally in order to provide a dependable framework for the other types of knowledge. Information left implicit in most existing coding and classification systems must be made explicit. The test of the resulting terminologies is how well they support software for key functions: including data entry, information retrieval, mediation, indexing, and authoring.

 
  • REFERENCES

  • 1 Baader F. Augmenting concept languages by transitive closure of roles: An alternative to terminological cycles. International Joint Conference on Artificial Intelligence (IJ-CAI-91) Morgan Kaufmann, 1991; 446-51.
  • 2 Baader F, Hollunder B. A terminological knowledge representation system with complete inference algorithm. Proceedings of the Workshop on Processing Declarative Knowledge, PDK0-91 (Lecture Notes in Artificial Intelligence #567) Berlin, Heidelberg: Springer-Verlag, 1991; 67-86.
  • 3 Brachman R, Levesque H. The tractability of subsumption in frame-based description languages. AAAI-84 Morgan Kaufman; 1984: 34-7.
  • 4 Brachman R, Schmolze J. An overview of the KL-ONE knowledge representation system. Cognitive Science 1985; 9: 171-216.
  • 5 Campbell K. Scalable methodologies for distributed development of logic-based convergent medical terminology. Meth Inform Med. (1998).
  • 6 Campbell K, Cohn S, Chute C, Rennels G, Shortliffe E. Galapagos: Computer-based support for evolution of a convergent medical terminology. Cimino J. eds. AMIA Fall Symposium. Washington, DC: Hanley and Belfus, Inc.; 1996: 269-73.
  • 7 Ceusters W. The distinction between linguistic and conceptual semantics in medical terminology and its implications for NLP-based knowledge acquisition. Meth Inform Med; (1998).
  • 8 Cimino J. Desiderata for controlled medical vocabularies in the twenty-first century. Meth Inform Med. (1998) (in press).
  • 9 Cimino J. Formal descriptions and adaptive mechanisms for changes in controlled medical vocabularies. Meth Inform Medicine 1996; 35: 202-10.
  • 10 Doyle J, Patil R. Two theses of knowledge representation: Language restrictions, taxonomic classification and the utility of representation services. Artificial Intelligence 1991; 48: 261-97.
  • 11 Fikes R, Farquhar A, Pratt W. Information brokers: Gathering information from heterogeneous information sources. Stewman HJ. eds. Ninth Florida Artificial Intelligence Research Symposium (FLAIRS-96). Key West, Florida: 1996: 192-7.
  • 12 Horrocks I, Rector A. Using a description logic with concept inclusions. Padgham L, Franconi E, Gehrke M, McGuinness D, Patel-Schneider P. eds. International Description Logics Workshop (DL 96). Menlo Park, CA, Cambridge, MA: AAAI Press; 1996: 132-5.
  • 13 Horrocks I, Rector A, Goble C. A description logic based schema for the classification of medical data. Baader F, Buchheit M, Jeusfeld M, Nutt W. eds. Knowledge Representation Meets Data bases (KRDB 96). Budapest, Hungary; 1996: 24-8.
  • 14 Johnson P. Personal Communication. 1996
  • 15 Kirby J, Cope N, Souza Ad, Fowler H, Gain R. The PEN&PAD Data Entry System. Brender J, Christensen J, Scherrer J-R, McNair P. eds. Medical Informatics Europe (MIE-96) Copenhagen. IOS Press; 1996: 430-4.
  • 16 Kirby J, Rector AL. The PEN&PAD Data Entry System: From prototype to practical system. Cimino J. eds. AMIA Fall Symposium. Washington DC: Hanley and Belfus, Inc.; 1996: 709-13.
  • 17 Lenat RGaDB. Re. CycLing paper reviews. Artificial Intelligence 1993; 61: 149-74.
  • 18 MacGregor R. The evolving technology of classification-based knowledge representation systems, in Principles of Semantic Networks: Explorations in the representation of knowledge. Sowa J. eds. San Mateo, CA: Morgan Kaufmann; 1991: 385-400.
  • 19 Musen M, Schreiber A. Architectures for intelligent systems based on reusable components. Artificial Intelligence in Medicine 1995; 189-99.
  • 20 Odell JJ. Six different kinds of composition, Journal of Object Oriented Programming. 1994 5. 10-5.
  • 21 Padgham L, Lambrix P. A Framework for Part-of Hierarchies in Terminological Logics. Sandewall E, Torasso P. eds. KR-94. 1994: 485-96.
  • 22 Rassinoux A-M. Modeling just the important and relevant concepts in medical language understanding. Meth Inform Medicine. 1997 (in press).
  • 23 Rector A, Bechhofer S, Goble C, Horrocks I, Nowlan W, Solomon W. The GRAIL concept modelling language for medical terminology. Artificial Intelligence in Medicine. 1996 (in press).
  • 24 Rector A, Gangemi A, Galeazzi E, Glowinski A, Rossi-Mori A. The GALEN CORE Model Schemata for Anatomy: Towards a re-usable application-independent model of medical concepts. Barahona P, Veloso M, Bryant J. eds. Twelfth International Congress of the European Federation for Medical Informatics, MIE-94. Lisbon, Portugal: 1994: 229-33.
  • 25 Rector A, Horrocks I. Experience building a large, re-usable medical ontology using a description logic with transitivity and concept inclusions, Workshop on Ontological Engineering, AAAI Spring Symposium, 1997. Menlo Park, CA, Standford, CA: AAAI Press; 1996. (in press).
  • 26 Rector A, Solomon W, Nowlan W, Rush T. A Terminology Server for Medical Language and Medical Information Systems. Meth Inform Med 1995; 34: 147-57.
  • 27 Rector A, Zanstra P, Solomon D. The GALEN Consortium, GALEN: Terminology Services for Clinical Information Systems, in Health in the New Communications Age. Laires M, Ladeira M, Christensen J. eds. Amsterdam: IOS Press; 1995: 90-100.
  • 28 Rocha RA, Huff SM, Haug PJ, Warner HR. Designing a controlled medical vocabulary server: the VOSER project. Computers and Biomedical Research 1994; 27: 472-507.
  • 29 Rogers J, Rector A. The GALEN ontology. Brender J, Christensen J, Scherrer J-R, McNair P. eds. Medical Informatics Europe (MIE 96). Copenhagen: IOS Press; 1996: 174-8.
  • 30 Rogers J, Solomon D, Rector A, Zanstra P. From rubrics to disections to GRAIL to classifications, Medical Informatics Europe (MIE-97). Thesalonika, Greece: IOS Press; 1997. (in press).
  • 31 Sattler U. A concept language for an engineering application with part-whole relations. International Workshop on Description Logics – DL-95, Rome 1995; 119-23.
  • 32 Shortliffe E, Barnett G, Cimino J, Greenes R, Huff S, Patel V. Collaborative medical informatics research using the Internet and the World Wide Web. Journal of the American Medical Informatics Association 1996 Symposium Supplement 1996; 125-9.
  • 33 Simon HA. The Sciences of the Artificial. MIT Press; 1969. 1981.
  • 34 Sowa J. Conceptual Structures: Knowledge Representation in Mind and Machine. New York: John Wiley & Sons; 1985
  • 35 Winston M, Chaffin R, Hermann D. A taxonomy of part-whole relations. Cognitive Science 1987; 11: 417-44.
  • 36 Wood W. The KL-ONE Family. Computers and Mathematics with Applications 1992; 23: 133-77.
  • 37 Zanstra P. Het GALEN Project, de Classification manager. CBV Niuews; 1993