New and innovative approaches to difficult problems in biomedical research are emerging because researchers have unprecedented access to large databases, advanced computational and analysis capabilities, and sophisticated high-throughput experimental apparatus. An example of such an emerging research approach is called MS3D, and uses intra-molecular chemical cross-linking followed by mass spectrometric analysis to develop data that enables the determination of the structure of macro-molecules. We propose to construct a data-centric collaboration infrastructure, and to develop and evolve it working directly with the leaders of the emerging MS3D research community. The infrastructure will contain an extensible portal for sharing data, tools, and coordinating collaboration. Emerging middleware standards for data/metadata management will enable information interoperability, and similar standards for security, application integration, and collaboration wilt be adopted. We will modify existing tools that generate and analyze data to enable the creation and storage of new MS3D metadata in a format that allows interoperability with other tools and collaboratory functions, and we will create new tools as the portal and data schemas mature. We will also research and develop methods for automating the capture of data provenance and workflow, working towards the development of a comprehensive knowledge management system. The long-range vision will target a standards-based knowledge synthesis and management capability. These developments will be focused and validated by piloting them with leading scientists in the MS3D community. MS3D knowledge bases will be made publicly available through the MS3D web portal. The tools will be made available as open source and their adoption by the broader biomedical research community will be facilitated. ? ?
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