Biomedicine and the Semantic Web: A Knowledge Model for Visual Phenotype

Semantic Web tools provide new and significant opportunities for organizing and improving the utility of biomedical information. As librarians become more involved with biomedical information, it is important for them, particularly catalogers, to be part of research teams that are employing these techniques and developing a high level interoperable biomedical infrastructure. To illustrate these principles, we used Semantic Web tools to create a knowledge model for human visual phenotypes (observable characteristics). This is an important foundation for generating associations between genomics and clinical medicine. In turn this can allow customized medical therapies and provide insights into the molecular basis of disease. The knowledge model incorporates a wide variety of clinical and genomic data including examination findings, demographics, laboratory tests, imaging, and variations in DNA sequence. Information organization, storage and retrieval are facilitated through the use of metadata and the ability to make computable statements in the visual science domain. This paper presents our work, discusses the value of Semantic Web technologies in biomedicine, and identifies several important roles that library and information scientiscan play in developing a more powerful biomedical information infrastructure.