OBJECTIVE: The aim of the project ARIANE is to model and implement seamless, natural, and easy-to-use interfaces with various kinds of heterogeneous biomedical information databases. DESIGN: A conceptual model of some of the Unified Medical Language System (UMLS) knowledge sources has been developed to help end users to query information databases. A query is represented by a conceptual graph that translates the deep structure of an end-user's interest in a topic. A computational model exploits this conceptual model to build a query interactively represented as query graph. A query graph is then matched to the data graph built with data issued from each record of a database by means of a pattern-matching (projection) rule that applies to conceptual graphs. RESULTS: Prototypes have been implemented to test the feasibility of the model with different kinds of information databases. Three cases are studied: 1) information in records is structured according to the UMLS knowledge sources; 2) information is able to be structured without error in the frame of the UMLS knowledge; 3) information cannot be structured. In each case the pattern-matching is processed by the projection rule according to the structure of information that has been implemented in the databases. CONCLUSION: The conceptual graphs theory provides with a homogeneous and powerful formalism able to represent both concepts, instances of concepts in medical contexts, and associations by means of relationships, and to represent data at different levels of details. The conceptual-graphs formalism allows powerful capabilities to operate a semantic integration of information databases using the UMLS knowledge sources.
OBJECTIVE: The aim of the project ARIANE is to model and implement seamless, natural, and easy-to-use interfaces with various kinds of heterogeneous biomedical information databases. DESIGN: A conceptual model of some of the Unified Medical Language System (UMLS) knowledge sources has been developed to help end users to query information databases. A query is represented by a conceptual graph that translates the deep structure of an end-user's interest in a topic. A computational model exploits this conceptual model to build a query interactively represented as query graph. A query graph is then matched to the data graph built with data issued from each record of a database by means of a pattern-matching (projection) rule that applies to conceptual graphs. RESULTS: Prototypes have been implemented to test the feasibility of the model with different kinds of information databases. Three cases are studied: 1) information in records is structured according to the UMLS knowledge sources; 2) information is able to be structured without error in the frame of the UMLS knowledge; 3) information cannot be structured. In each case the pattern-matching is processed by the projection rule according to the structure of information that has been implemented in the databases. CONCLUSION: The conceptual graphs theory provides with a homogeneous and powerful formalism able to represent both concepts, instances of concepts in medical contexts, and associations by means of relationships, and to represent data at different levels of details. The conceptual-graphs formalism allows powerful capabilities to operate a semantic integration of information databases using the UMLS knowledge sources.
Authors: Qing T Zeng; Jonathan Crowell; Robert M Plovnick; Eunjung Kim; Long Ngo; Emily Dibble Journal: J Am Med Inform Assoc Date: 2005-10-12 Impact factor: 4.497