The European GALEN project is developing terminology services based on a large, re-usable medical ontology. The ontology is being built using GRAIL, a description logic with transitivity and general concept inclusions.

Despite years of work, no re-usable clinical terminology has yet been demonstrated in widespread use. This paper puts forward ten reasons why developing such terminologies is hard. All stem from underestimating the change entailed in using terminology in software for ‘patient centred ’ systems rather than for its traditional functions of statistical and financial reporting. Firstly, the increase in scale and complexity are enormous. Secondly, the resulting scale exceeds what can be managed manually with the rigour required by software, but building appropriate rigorous representations on the necessary scale is, in itself, a hard problem. Thirdly, ‘clinical pragmatics ’ – practical data entry, presentation and retrieval for clinical tasks – must be taken into account, so that the intrinsic differences between the needs of users and the needs of software are addressed. This implies that validation of clinical terminologies must include validation in use as implemented in software. Why-is-terminology-hard-single-r2.doc 14/01/00 15:21 2 1.

This report describes and evaluates optimisation techniques for a tableaux based satisfiability testing algorithm used to compute subsumption in Grail, an expressive description logic. Five techniques are studied in detail: normalisation and encoding, indexing, semantic branching, dependency directed backtracking and caching. The effectiveness of these techniques is evaluated by empirical testing using a large knowledge base from the Galen project. The performance of the optimised classifier and subsumption test are also compared with that of the Kris classifier and KSAT satisfiability testing procedure using both the Galen knowledge base and randomly generated test data. 1 Introduction As part of the European Galen project the Medical Informatics Group at Manchester University have built a large concept model representing knowledge about medical terminology. The model is intended to promote sharing and re-use of medical data by acting as a flexible and extensible classification sche...