Objects and Domains for Managing Medical Data and Knowledge

Abstract:

This paper assesses the object-oriented data paradigm, and describes an algebraic approach which permits the generation of data objects from relational data, based on the knowledge captured in a formal Entity-Relationship model, the Structural Model. The advantage is that now objects can be created that satisfy a variety of particular views, as long as the hierarchies represented by the views are subsumed in the network represented by the overall structural model.

The disadvantage of creating view-objects dynamically is that the additional layering has performance implications, so that the speedup expected from object-oriented databases versus relational databases, due to their hierarchical object storage, cannot be realized. However, scalability of systems is increased since large systems tend to have multiple objectives, and hence often multiple valid hierarchical views over the data. This approach has been implemented in the Penguin project, and recently some commercial successors are emerging.

In truly large systems new problems arise, namely that now not only multiple views will exist, but also that the domains to be covered by the data will be autonomous and hence heterogeneous. One result is that ontologies associated with the multiple domains will differ as well. This paper proposes a knowledge-based algebra over the ontologies, so that the domain knowledge can be partitioned for maintenance. Only the articulation points, where the domains intersect, have to be agreed upon as defined by matching rules which define the shared ontologies.

Keywords:

Object-oriented Paradigm - Entity-Relationship Model - Domain-Knowledge Base

• References

• 1 Liskov BH, Zilles SN. Specification techniques for data abstractions. IEEE Trans Softw Engin 1975; SE-1: 7-19.
• 2 Manola F. The third-generation/OODBMS manifesto, commercial version. ACM SIGMOD Record 1991; 20: 91-7.
• 3 OMG. The Cornman Object Request Broker. Framingham MA: Object Management Group; 1991
• 4 Liskov B, Day M, Shira L. Distributed Object Management in THOR. In: Öszu et al. Distributed Object Management. Morgan-Kaufman; 1993
• 5 Barsalou T, Sujansky W, Herzenberg L, Wiederhold G. Management of complex immunogenetics information using an enhanced relational model. Comp Biomed Res 1991; 24: 476-98.
• 6 Wiederhold G. Database Design (2nd ed). New York: McGraw-Hill; 1983
• 7 Wiederhold G, El-Masri R. The structural model for database design. In: Chen, ed. Entity-Relationships Approach to Systems Analysis and Design. Amsterdam: North-Holland; 1980: 237-57.
• 8 Barsalou T, Siambela N, Keller A, Wiederhold G. Updating relational databases through object-based views. In: Proceedings ACM SIGMOD Conference on the Management of Data 91. Boulder CO: 1991: 248-57.
• 9 Davidson J. A natural language interface for performing database updates. Proceedings IEEE CS Intl Conf on Data Engineering. Los Angeles: 1984: 69-76.
• 10 Gruber TR. A translation approach to portable ontology specifications. Knowledge Acquisition 1993; 5: 199-220.
• 11 Haddock G, Harbison K. From scenarios to domain models: processes and representations. In: Proceedings of the Conference on Knowledge-based Artificial Intelligence Systems in Aerospace and Industry. SPIE; 1994
• 12 Wiederhold G. The roles of artificial intelligence in information systems. J Intell Inform Systems 1992; 1: 35-56.
• 13 Humphreys BL, Lindberg DAB. The Unified Medical Language project: A distributed experiment in improving access to biomedical information. In: MEDINFO 92. Amsterdam: North-Holland; 1992: 1496-1500.
• 14 Lenat D, Guha RV. et al. Cyc: towards programs with common sense. Comm ACM 1990; 33: 30-49.
• 15 Kahn RE. Networks for advanced computing. Scientific American 1987; 257: 136-43.
• 16 Gruber TR, Olsen G. An ontology for engineering mathematics. In: Doyle J, Torasso P, Sandewall E. eds. Fourth International Conference on Principles of Knowledge Representation and Reasoning. Morgan Kaufmann Publ; 1994
• 17 Collet C, Huhns M, Shen W-M. Resource integrating using a large knowledge base in carnot. IEEE Computer 1991; 24: 45-64.