IJCIRISSN 1996-1065 [Online]
ISSN 1818-1139 [PRINT]

Volume 2 (2) 2008

Title:	A Flexible Approach for User Evaluation of Biomedical Ontologies
Authors:	Gilbert Maiga* , Ddembe Williams
Published:	©IJCIR Vol2 (2) 2008, PP. 62-74
Language:	English

Abstract:
There has been an emergence of various ontologies describing data from either the clinical or biological domains. Associated with this are attempts to develop systems that integrate clinical and biological ontologies using various strategies to overcome issues of scope, differing levels of granularity and conflicting user needs. However, lack of knowledge about user needs for such integration systems, and absence of a general framework to assess their suitability for specific application remain obstacles to their reuse and wide adoption in distributed computing environments. This paper describes a study that aims to address this problem by proposing an evaluation framework for ontology integration to suit user needs. The framework draws on existing ontology evaluation approaches in relating user objectives to ontology characteristics. Systems theory is used to explain the dynamics of a biomedical environment. The framework therefore includes feedbacks from the evaluation process to the user characteristics of the integrated systems. This framework was validated by a study using structured interviews and questionnaires in a survey. The results indicate that it is sufficiently flexible for evaluating ontology based biomedical integrated systems, taking into account the conflicting needs of different users interested in accessing complex libraries of biomedical data.View full Article

Categories and Subject descriptors: H.1.1 [Models and Principles]: Systems and Information theory – General Systems Theory; J.3 [Life and Medical Sciences]: Medical Information Systems, Biology and Genetics General terms: Ontology Evaluation; Biomedical Ontology; Ontology Integration; User Evaluation; Evaluation Frameworks; Systems Approach. Additional key words and phrases: Biological data; Clinical data.