The aggregation of imaging, clinical, and behavioral data from multiple independent institutions and researchers presents both a great opportunity for biomedical research as well as a formidable challenge. Many research groups have well-established data collection and analysis procedures, as well as data and metadata format requirements that are particular to that group. Moreover, the types of data and metadata collected are quite diverse, including image, physiological, and behavioral data, as well as descriptions of experimental design, and preprocessing and analysis methods. Each of these types of data utilizes a variety of software tools for collection, storage, and processing. Furthermore sites are reluctant to release control over the distribution and access to the data and the tools. To address these needs, the Biomedical Informatics Research Network (BIRN) has developed a federated and distributed infrastructure for the storage, retrieval, analysis, and documentation of biomedical imaging data. The infrastructure consists of distributed data collections hosted on dedicated storage and computational resources located at each participating site, a federated data management system and data integration environment, an Extensible Markup Language (XML) schema for data exchange, and analysis pipelines, designed to leverage both the distributed data management environment and the available grid computing resources.

Abstract We have developed a simple algebraic approach to music description and composition called Haskore . In this framework, musical objects consist of primitive notions such as notes and rests, operations to transform musical objects such as transpose and tempo-scaling, and operations to combine musical objects to form more complex ones, such as concurrent and sequential composition. When these simple notions are embedded into a functional language such as Haskell, rather complex musical relationships can be expressed clearly and succinctly. Exploiting the algebraic properties of Haskore, we have further defined a notion of literal performance (devoid of articulation) through which observationally equivalent musical objects can be determined. With this basis many useful properties can be proved, such as commutative, associative, and distributive properties of various operators. An algebra of music thus surfaces.