Ontological and Practical Issues in Using a Description Logic to Represent Medical Concept Systems: Experience from GALEN

  • Alan Rector
  • Jeremy Rogers
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4126)


GALEN seeks to provide re-usable terminology resources for clinical systems. The heart of GALEN is the Common Reference Model (CRM) formulated in a specialised description logic. The CRM is based on a set of principles that have evolved over the period of the project and illustrate key issues to be addressed by any large medical ontology. The principles on which the CRM is based are discussed followed by a more detailed look at the actual mechanisms employed. Finally the structure is compared with other biomedical ontologies in use or proposed.


Natural Kind Practical Issue Description Logic Biomedical Ontology Transitive Attribute 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Artale, A., Franconi, E., Guarino, N.: Open problems for part-whole relations. In: International Workshop on Descripition Logics, Boston, MA (1996)Google Scholar
  2. 2.
    Artale, A., Franconi, E., Pazzi, L.: Part-whole relations in object-centered systems: An overview. Data and Knowledge Engineering 20, 347–383 (1996)CrossRefMATHGoogle Scholar
  3. 3.
    Bateman, J.A.: Upper modelling: A general organization of knowledge for natural language processing. USC/Information Sciences Institute (1989)Google Scholar
  4. 4.
    Bittner, T., Donnelly, M., Smith, B.: Individuals, Universals, collections: On the foundational relations of ontology. In: International Conference on Formal Ontology and Information Systems (FOIS 2004), Turin, Italy (2004)Google Scholar
  5. 5.
    Borgida, A.: Description logics in data management. IEEE Transactions on Knowledge and Data Engineering 7(5), 671–682 (1995)CrossRefGoogle Scholar
  6. 6.
    Brachman, R., Levesque, H.: The tractability of subsumption in frame-based description languages. In: AAAI 1984. Morgan Kaufmann, San Francisco (1984)Google Scholar
  7. 7.
    Brachman, R.J., et al.: Living with Classic: When and how to use a KL-ONE-like language. In: Sowa, J. (ed.) Principles of Semantic Networks: Explorations in the representation of knowledge, pp. 401–456. Morgan Kaufmann, San Francisco (1991)Google Scholar
  8. 8.
    Brown, P., O’Neil, M., Price, C.: Semantic definition of disorders in Version 3 of the Read Codes. Methods of Information in Medicine 37, 415–419 (1998)Google Scholar
  9. 9.
    Casati, R., Varzi, A.C.: Parts and Places. In: Parts and Places: The Structurres of Spatial Representation. Clarendon Press, Oxford (1999)Google Scholar
  10. 10.
    Chute, C.: Clinical classification and terminology: Some history and current observations. Journal of the American Medical Informatics Association 7(3), 293–303 (2000)Google Scholar
  11. 11.
    Cimino, J.: Controlled Medical Vocabulary Construction: Methods from the Canon Group. Journal of the American Medical Informatics Association 1(3), 197–296 (1994)Google Scholar
  12. 12.
    Cimino, J.: Desiderata for controlled medical vocabularies in the twenty-first century. Methods of Information in Medicine 37(4-5), 394–403 (1998)Google Scholar
  13. 13.
    Degen, W., et al.: Formal Ontology in Information Systems (FOIS 2001) (2001)Google Scholar
  14. 14.
    Doyle, J., Patil, R.: Two theses of knowledge representation: Language restrictions, taxonomic classification and the utility of representation services. Artificial Intelligence 48, 261–297 (1991)CrossRefGoogle Scholar
  15. 15.
    Etherington, D.: Formalising nonmonotonic reasoning systems. Artificial Intelligence 31, 41–85 (1987)CrossRefMathSciNetMATHGoogle Scholar
  16. 16.
    Evans, D.A., et al.: Position statement: Towards a medical concept representation language. Journal of the American Medical Informatics Association 1(3), 207–217 (1994)Google Scholar
  17. 17.
    Gangemi, A., Guarino, N., Masolo, C., Oltramari, A., Schneider, L.: Sweetening ontologies with DOLCE. In: Gómez-Pérez, A., Benjamins, V.R. (eds.) EKAW 2002. LNCS, vol. 2473, p. 166. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  18. 18.
    Gruber, T.R.: Toward Principles for the Design of Ontologies Used for Knowledge Sharing. Knowledge Systems Laboratory, Stanford University (1993)Google Scholar
  19. 19.
    Guarino, N., Welty, C.: An overview of OntoClean. In: Staab, S., Studer, R. (eds.) Handbook of Ontologies, pp. 151–159. Springer, Heidelberg (2004)Google Scholar
  20. 20.
    Guarino, N., Welty, C.: Towards a methodology for ontology-based model engineering. In: ECOOP 2000 Workshop on Model Engineering, Cannes, France (2000)Google Scholar
  21. 21.
    Guha, R., Lenat, D.: Enabling agents to work together. Communications of the ACM 37, 127–142 (1994)CrossRefGoogle Scholar
  22. 22.
    Haarslev, V., Moeller, R.: Expresive ABox reasoning with number restrictions, role hierarchies, and transitively closed roes. In: Proceedings of the Seventh International Conference on Knowledge Representation and Reasoning (KR 2000). Morgan Kaufmann, San Francisco (2000)Google Scholar
  23. 23.
    Hahn, U., Romacker, M., Schulz, S.: How knowledge drives understanding - matching medical ontologies with the needs of medical language processing. Artificial Intelligence in Medicine 15(1), 25–52 (1999)CrossRefGoogle Scholar
  24. 24.
    Hahn, U., Schulz, S., Romacker, M.: Part-whole reasoning: a case study in medical ontology engineering. IEEE Intelligent Systems and their Applications 14(5), 59–67 (1999)CrossRefGoogle Scholar
  25. 25.
    Hahn, U., Schulz, S., Romacker, M.: Partonomic reasoning as taxonomic reasoning in medicine. In: Proc. of the 16th National Conf. on Artificial Intelligence & 11th Innovative Applications of Artificial Intelligence (AAAI 1999/IAAI 1999). AAAI Press/MIT Press, Orlando FL (1999)Google Scholar
  26. 26.
    Hardiker, N.R., Rector, A.L.: Modeling nursing terminology using the GRAIL representation language. Journal of the American Medical Informatics Association 5, 120–128 (1998)Google Scholar
  27. 27.
    Horrocks, I.: Optimising Tableaux Decision Procedures for Description Logics, in Computer Science, p. 176. University of Manchester, Manchester (1997)Google Scholar
  28. 28.
    Horrocks, I.: Using an expressive description logic: FaCT or Fiction in Principles of Knowledge Representation and Reasoning. In: Proceedings of the Sixth International Conference on Knowledge Representation (KR 1998). Morgan Kaufmann, San Francisco (1998)Google Scholar
  29. 29.
    Horrocks, I., Sattler, U.: The decidability of SHIQ with complex role inclusion axioms. Artificial Intelligence 160(102), 79–104 (2004)CrossRefMathSciNetMATHGoogle Scholar
  30. 30.
    Kirby, J., Rector, A.L.: The PEN&PAD Data Entry System: From prototype to practical system. In: AMIA Fall Symposium. Hanley and Belfus, Inc., Washington DC (1996)Google Scholar
  31. 31.
    Lenat, D.B., Guha, R.V.: Building Large Knowledge-Based Systems: Representation and inference in the Cyc Project, p. 372. Addison-Wesley, Reading (1989)Google Scholar
  32. 32.
    Martin, R.F., et al.: Foundational Model of Neuroanatomy:Implications for the Human Brain Project. In: AMIA Fall Symposium, Washington DC (2001)Google Scholar
  33. 33.
    Masolo, C., et al.: WonderWeb Deliveable 18. WonderWeb consortium (2003)Google Scholar
  34. 34.
    Mejino, J.L.V., Rosse, C.: Conceptualization of anatomical spatial entities in the Digital Anatomist Foundational Model. Journal of the American Medical Informatics Association (1999 Annual Symposium Special Issue), 112–116 (1999)Google Scholar
  35. 35.
    Mork, P., Bernstein, P.: Adapting a generic match algorithm to align ontologies of human anatomy. In: 20th International Conference on Data Engineering, Boston. IEEE, Los Alamitos (2004)Google Scholar
  36. 36.
    Mork, P., Pottinger, R., Bernstein, P.: Challenges in precisely aligning models of human anatomy. In: Proceedings of Medinfo 2004. IMIA, San Francisco (2004)Google Scholar
  37. 37.
    Neal, P.J., Shapiro, L.G., Rosse, C.: The Digital Anatomist structural abstraction: a scheme for the spatial description lf anatomical entities. Journal of the American Medical Informatics Association (Fall Symposium Special Issue), 423–427 (1998)Google Scholar
  38. 38.
    Nowlan, W.A.: Clinical workstation: Identifying clinical requirements and understanding clinical information. International Journal of Bio-Medical Computing 34, 85–94 (1994)CrossRefGoogle Scholar
  39. 39.
    O’Neil, M., Payne, C., Read, J.: Read Codes Version 3: A user led terminology. Methods of Information in Medicine 34, 187–192 (1995)Google Scholar
  40. 40.
    Odell, J.J.: Six different kinds of composition. Journal of Object Oriented Programming 5(8), 10–15 (1994)Google Scholar
  41. 41.
    Padgham, L., Lambrix, P.: A framework for part-of hierarchies in terminological logics. In: KR 1994 (1994)Google Scholar
  42. 42.
    Rector, A.: Analysis of propagation along transitive roles: Formalisation of the GALEN experience with medical ontologies. In: CEUR-Proceedings 53, 2002 International Workshop on Description Logics (DL 2002), Toulouse France, p. 53 (2002)Google Scholar
  43. 43.
    Rector, A.: Coordinating taxonomies: Key to re-usable concept representations. In: Wyatt, J.C., Stefanelli, M., Barahona, P. (eds.) AIME 1995. LNCS, vol. 934. Springer, Heidelberg (1995)Google Scholar
  44. 44.
    Rector, A.: Modularisation of domain ontologies Implemented in description logics and related formalisms including OWL. In: Knowledge Capture 2003, Sanibel Island, FL. ACM, New York (2003)Google Scholar
  45. 45.
    Rector, A.: Thesauri and formal classifications: Terminologies for people and machines. Methods of Information in Medicine 37(4-5), 501–509 (1998)Google Scholar
  46. 46.
    Rector, A., et al.: The GRAIL concept modelling language for medical terminology. Artificial Intelligence in Medicine 9, 139–171 (1997)CrossRefGoogle Scholar
  47. 47.
    Rector, A., et al.: Scale and Context: Issues in ontologies to link health- and bio-Informatics. In: AMIA Fall Symposium. Austin Texas, Hanley and Belfus, Philadelphia (2002)Google Scholar
  48. 48.
    Rector, A., et al.: Making sound re-usable terminology practical: The GALEN approach. In: Towards and Electronic Health Care Record, Europe 1998. Medical Records Institute, Newton Mass, London (1998)Google Scholar
  49. 49.
    Rector, A., et al.: A Terminology Server for Medical Language and Medical Information Systems. Methods of Information in Medicine 34, 147–157 (1995)Google Scholar
  50. 50.
    Rector, A., Taweel, A., Rogers, J.: Models and inference methods for clinical systems: A principled approach. In: Medinfo 2004. North Holland, San Francisco (2004)Google Scholar
  51. 51.
    Rector, A., et al.: GALEN: Terminology Services for Clinical Information Systems. In: Laires, M., Ladeira, M., Christensen, J. (eds.) Health in the New Communications Age, pp. 90–100. IOS Press, Amsterdam (1995)Google Scholar
  52. 52.
    Rector, A.L.: Clinical Terminology: Why is it so hard? Methods of Information in Medicine 38, 239–252 (1999)Google Scholar
  53. 53.
    Rector, A.L.: Defaults, context and knowledge: Alternatives for OWL-Indexed Knowledge bases. In: Pacific Symposium on Biocomputing (PSB-2004), Kona, Hawaii. World Scientific, Singapore (2004)Google Scholar
  54. 54.
    Rector, A.L.: The Interface between Information, Terminology, and Inference Models. In: Tenth World Conference on Medical and Health Informatics: Medinfo 2001, London, England (2001)Google Scholar
  55. 55.
    Rector, A.L., et al.: Interface of inference models with concept and medical record models. In: Artificial Intelligence in Medicine Europe (AIME), Cascais, Portugal. Springer, Heidelberg (2001)CrossRefGoogle Scholar
  56. 56.
    Rector, A.L., et al.: Reconciling users’ needs and formal requirements: Issues in developing a re-usable ontology for medicine. IEEE Transactions on Information Technology in BioMedicine 2(4), 229–242 (1999)CrossRefGoogle Scholar
  57. 57.
    Rodrigues, J.M., et al.: Galen-In-Use: An EU Project applied to the development of a new national coding system for surgical procedures: NCAM. In: Medical Informatics Europe 1997, Porto Carras, Greece. IOS Press, Amsterdam (1997)Google Scholar
  58. 58.
    Rogers, J., Rector, A.: The GALEN ontology. In: Medical Informatics Europe (MIE 1996), Copenhagen. IOS Press, Amsterdam (1996)Google Scholar
  59. 59.
    Rogers, J., Rector, A.: GALEN’s model of parts and wholes: Experience and comparisons. Journal of the American Medical Informatics Association (Fall symposium special issue), 819–823 (2000)Google Scholar
  60. 60.
    Rogers, J., et al.: From rubrics to dissections to GRAIL to classifications. In: Medical Informatics Europe (MIE 1997), Thesalonika, Greece. IOS Press, Amsterdam (1997)Google Scholar
  61. 61.
    Rogers, J.E.: Development of a methodology and an ontological schema for medical terminology. In: School of Medicine, Dentistry, Nursing and Pharmacy, p. 185. University of Manchester (2004)Google Scholar
  62. 62.
    Rogers, J.E., et al.: Validating clinical terminology structures: Integration and cross-validation of Read Thesaurus and GALEN. Journal of the American Medical Informatics Association (Fall Symposium Special Issue), 845–849 (1998)Google Scholar
  63. 63.
    Rosse, C., Shapiro, I.G., Brinkley, J.F.: The Digital Anatomist foundational model: Principles for defining and structuring its concept domain. Journal of the American Medical Informatics Association(1998 Fall Symposium Special issue), 820–824 (1998)Google Scholar
  64. 64.
    Schank, R.C., Abelson, R., Scripts, P.: Plans, Goals, and Understanding. Lawrence Erlbaum Associates, Hilsdale (1977)MATHGoogle Scholar
  65. 65.
    Schulz, S., Hahn, U.: Mereotopological reasoning about parts and (w)holes in bio-ontologies. In: Formal Ontology in Information Systems (FOIS 2001). ACM, Ogunquit (2001)Google Scholar
  66. 66.
    Schulz, S., Hahn, U.: Parts, locations, and holes - Formal reasoning about anatomical structures. In: Quaglini, S., Barahona, P., Andreassen, S. (eds.) AIME 2001. LNCS, vol. 2101, p. 293. Springer, Heidelberg (2001)CrossRefGoogle Scholar
  67. 67.
    Schulz, S., Hahn, U., Romacker, M.: Modeling anatomical spatial relations with description logics. In: AMIA Fall Symposium (AMIA 2000), Los Angeles, CA, Hanly & Belfus (2000)Google Scholar
  68. 68.
    Shahar, Y., et al.: A problem-solving architecture for managing temporal data and their abstractions. In: Workshop on Implementing Temporal Reasoning, AAAI 1992, San Jose, CA (1992)Google Scholar
  69. 69.
    Smith, B.: The basic tools of formal ontology. In: Formal Ontology in Information Systems (FOIS) (Frontiers in Artificial Intelligence and Applications). IOS Press, Amsterdam (1998)Google Scholar
  70. 70.
    Smith, B.: The logic of biological classification and the foundations of biomedical ontology. In: 10th International Conference in Logic Methodology and Philosophy of Science, Oviedo Spain. Elsevier-North-Holland (2004)Google Scholar
  71. 71.
    Solomon, W., Heathfield, H.: Conceptual modelling used to represent drug interactions. In: Twelfth International Congress of the European Federation for Medical Informatics, MIE 1994, Lisbon, Portugal (1994)Google Scholar
  72. 72.
    Solomon, W., et al.: A reference terminology for drugs. Journal of the American Medical Informatics Association (Fall Symposium Special Issue), 152–155 (1999)Google Scholar
  73. 73.
    Sowa, J.: Knowledge Representation. Morgan Kaufmann, San Francisco (1999)Google Scholar
  74. 74.
    Staab, S., Maedche, A.: Ontology engineering beyond the modeling of concepts and relations. In: ECAI 2000, 14th European Conference on Artificial Intelligence; Workshop on Applications of Ontologies and Problem Solving Methods (2000)Google Scholar
  75. 75.
    Stearns, M., et al.: SNOMED clinical terms: overview of the development process and project status. In: AMIA Fall Symposium (AMIA 2001), Henley & Belfus (2001)Google Scholar
  76. 76.
    The Gene Ontology Consortium, Creating the gene ontology resource: design and implementation. Genome Research 11, 1425–1433 (2001)Google Scholar
  77. 77.
    The Gene Ontology Consortium, Gene Ontology: tool for the unification of biology. Nature Genetics 25, 25–29 (2000)Google Scholar
  78. 78.
    Touretzky, D.: The Mathematics of Inheritance Systems. Morgan Kaufmann, Los Altos (1986)MATHGoogle Scholar
  79. 79.
    Tuttle, M.S.: The position of the canon group: A reality check. Journal of the American Medical Informatics Association 1(3), 298–299 (1994)Google Scholar
  80. 80.
    United States Center for Health Statistics, International Classification of Diseases. In: Ninth Revision with Clinical Modifications. The Center, Washington (1980)Google Scholar
  81. 81.
    Uschold, M., Gruninger, M.: Ontologies: principles, methods and applications. Knowledge Engineering Review 11(2) (1996)Google Scholar
  82. 82.
    Varzi, A.C.: Mereological commitments. Dialectica 54, 283–305 (2000)CrossRefGoogle Scholar
  83. 83.
    Welty, C., Guarino, N.: Supporting ontological analysis of taxonomic relationships. Data and Knowledge Engineering 39(1), 51–74 (2001)CrossRefMATHGoogle Scholar
  84. 84.
    Winston, M., Chaffin, R., Hermann, D.: A taxonomy of part-whole relations. Cognitive Science 11, 417–444 (1987)CrossRefGoogle Scholar
  85. 85.
    Woods, W.: What’s important about knowledge representation? IEEE Computer 16, 22–29 (1983)Google Scholar
  86. 86.
    Wroe, C., Cimino, J.: Using openGALEN techniques to develop the HL7 drug formulation vocabulary. In: American Medical Informatics Association Fall Symposium(AMIA 2001) (2001)Google Scholar
  87. 87.
    Wroe, C., et al.: Inheritance of drug information. Journal of the American Medical Informatics Association (Annual Symposium Special Issue), 1158 (2000)Google Scholar
  88. 88.
    Zhang, S., Bodenreider, O.: Comparing associative concepts among equivalent concepts across ontologies. In: Medinfo 2004. IOS Press, San Francisco (2004)Google Scholar
  89. 89.
    Zhang, S., Bodenreider, O.: Investigating implicit knowledge in ontologies with application to the anatomical domain. In: Pacific Symposium on Bioinformatics (2004)Google Scholar
  90. 90.
    Zhang, S., Mork, P., Bodenreider, O.: Lessons learnned from aligning two representations of Anatomy. In: First international workshop on formal biomedical knowledge representation. Whistler, Canada (2004)Google Scholar
  91. 91.
    Zweigenbaum, P., et al.: Issues in the structuring and acquisition of an ontology for medical language understanding. Methods of Information in Medicine 34(1/2), 15–24 (1995)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Alan Rector
    • 1
  • Jeremy Rogers
    • 1
  1. 1.School of Computer ScienceUniversity of ManchesterManchesterUK

Personalised recommendations