The biological exploration of the earth has resulted in enormous museum collections. Museum specimens and their associated data document biodiversity and provide vital infrastructure supporting the missions of systematics. Access to collections data is crucial for the rapid progress of systematics and ultimately for the assessment, analysis, and management of biotic resources. U.S. collections are held by more than 150 museums and botanical gardens, and the highly partitioned distribution of collections data among autonomously managed databases impedes their effective use. The unmet need is for technology that enables users to assemble data from distributed sources, while hiding the complexity of data distribution, and the heterogeneity among local systems and schemas. The federated databases model architecture has repeatedly been identified as appropriate for developing information interoperability within the biological sciences. Establishing a federation of collections databases imposes a minimal set of requirements for cooperation within a community. While technical solutions for enabling database interoperability will be developed in the computer science community, the required semantic data standards can only result from efforts arising within and carried out by the collections community. This project is being conducted under the auspices of the Association of Systematics Collections (ASC) Committee on Computerization and Networking, and represents a continuation of an effort on behalf of the systematics community (museums and similar institutions) to develop an information model for biological collections. The model will encompass all disciplines, not just plants or single animal groups, and all taxa, not just endangered or threatened species. The goal is to develop a unifying, consensus-based, implementation-independent (conceptual) schema for collections information, down to the level of the atomic data concept. This project does not propose to build a collections database management system, but rather, to establish a semantic data standard that will enable specimen data to be combined across systematics disciplines to address pressing resource management needs and to test complex research questions.
