In order to assess the mission and strategic direction in an academic department of biomedical informatics, we used social network analysis to identify patterns of common interest among the department's multidisciplinary faculty. Data representing faculty and their self-identified research methods and expertise were analyzed by applying a network modularity algorithm to detect community structure. Three distinct communities of practice emerged: empirical discovery and prediction; human and organizational factors; and information management. This analysis made intuitive sense and served the goal of stimulating discussion from new perspectives. The findings will guide future direction and faculty recruitment efforts. Communities of practice present a novel view of interdisciplinarity in biomedical informatics.
