Pushing the envelope: challenges in a frame-based representation of human anatomy

One of the main threads in the history of knowledge-representation formalisms is the trade-off between the expressiveness of first-order logic on the one hand and the tractability and ease-of-use of frame-based systems on the other hand. Frame-based systems provide intuitive, cognitively easy-to-understand, and scalable means for modeling a domain. However, when a domain model is particularly complex, frame-based representation may lead to complicated and sometimes awkward solutions. We have encountered such problems when developing the Digital Anatomist Foundational Model, an ontology aimed at representing comprehensively the physical organization of the human body. We show that traditional frame-based techniques such as is-a hierarchies, slots (roles) and role restrictions are not sufficient for a comprehensive model of this domain. The diverse modeling challenges and problems in this project required us to use such knowledge-representation techniques as reified relations, metaclasses and a metaclass hierarchy, different propagation patterns for template and own slots, and so on. We posit that even though the modeling structure imposed by frame-based systems may sometimes lead to complicated solutions, it is still worthwhile to use frame-based representation for very large-scale projects such as this one.

[1]  Henrik Eriksson,et al.  The evolution of Protégé: an environment for knowledge-based systems development , 2003, Int. J. Hum. Comput. Stud..

[2]  James J. Odell,et al.  Advanced object-oriented analysis and design using UML , 1997 .

[3]  Eyal Amir,et al.  Object-Oriented First-Order Logic , 1999, Electron. Trans. Artif. Intell..

[4]  Cornelius Rosse,et al.  A Reference Ontology for Bioinformatics: The Foundational Model of Anatomy , 2003 .

[5]  Cornelius Rosse,et al.  Hollinshead's Textbook of Anatomy , 1997 .

[6]  Ian Horrocks,et al.  DAML+OIL is not Enough , 2001, SWWS.

[7]  Natalya F. Noy,et al.  Component-Based Support for Building Knowledge-Acquisition Systems , 2000 .

[8]  Henrik Eriksson,et al.  Knowledge modeling at the millennium : The design and evolution of Protégé-2000 , 1999 .

[9]  Peter D. Karp,et al.  OKBC: A Programmatic Foundation for Knowledge Base Interoperability , 1998, AAAI/IAAI.

[10]  P. Karp.  The design space of frame knowledge representation systems , 1992 .

[11]  E. B Schulz,et al.  Application of Technology: Symbolic Anatomic Knowledge Representation in the Read Codes Version 3: Structure and Application , 1997, J. Am. Medical Informatics Assoc..

[12]  Linda G. Shapiro,et al.  The digital anatomist foundational model: principles for defining and structuring its concept domain , 1998, AMIA.

[13]  Mark A. Musen,et al.  The Knowledge Model of Protégé-2000: Combining Interoperability and Flexibility , 2000, EKAW.

[14]  Peter Szolovits,et al.  Representing Medical Knowledge in a Terminological Language is Difficult , 1988 .

[15]  C. Rosse.  Terminologia Anatomica: Considered from the perspective of next‐generation knowledge sources , 2001, Clinical anatomy (New York, N.Y. Print).

[16]  Alan L. Rector,et al.  GALEN's model of parts and wholes: experience and comparisons , 2000, AMIA.

[17]  José L. V. Mejino,et al.  A reference ontology for biomedical informatics: the Foundational Model of Anatomy , 2003, J. Biomed. Informatics.

[18]  D. Lindberg,et al.  The Unified Medical Language System , 1993, Methods of Information in Medicine.

[19]  José L. V. Mejino,et al.  The role of definitions in biomedical concept representation , 2001, AMIA.

[20]  José L. V. Mejino,et al.  Research Paper: Motivation and Organizational Principles for Anatomical Knowledge Representation: The Digital Anatomist Symbolic Knowledge Base , 1998, J. Am. Medical Informatics Assoc..

[21]  Douglas Herrmann,et al.  A Taxonomy of Part-Whole Relations , 1987, Cogn. Sci..