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Scientific collaboration is largely focused on the sharing and joint analysis of scientific data and results. Today, a movement is afoot within the scientific computing community to shift "collaboratory" development from traditional tool-centric approaches to more data-centric ones. Yet, to effectively support data sharing means more than providing a common repository for storing and retrieving shared data sets. In order to reasonably comprehend and apply another researcher's data set, the scientist must grasp the various contexts of the data as it relates to the overall data space, applications, experiments, projects, and the scientific community. Under development at the Pacific Northwest National Laboratory, the Biological Sciences Collaboratory (BSC) enables the sharing of biological data and analyses through diverse capabilities such as metadata capture, electronic laboratory notebooks, data organization views, data provenance tracking, analysis notes, task management, and scientific workflow management. Overall, BSC strives to identify and capture the various social and scientific contexts in which data sharing collaborations in biology take place and to provide collaboration tools and capabilities that can effectively support and facilitate these important data sharing contexts.
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Chin et al. (2004) studied this question.
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