Abstract
Scientific research becomes increasingly reliant on multi-disciplinary, multi-institutional collaboration through sharing experimental data. Indeed, data sharing is mandatory by government research agencies such as NIH. The major hurdles for data sharing come from: i) the lack of data sharing infrastructure to make data sharing convenient for users; ii) users’ fear of losing control of their data; iii) difficulty on sharing schemas and incompatible data from sharing partners; and iv) inconsistent data under schema evolution. In this paper, we develop a collaborative data sharing system SciPort, to support consistency preserved data sharing among multiple distributed organizations. The system first provides Central Server based lightweight data integration architecture, so data and schemas can be conveniently shared across multiple organizations. Through distributed schema management, schema sharing and evolution is made possible, while data consistency is maintained and data compatibility is enforced. With this data sharing system, distributed sites can now consistently share their research data and their associated schemas with much convenience and flexibility. SciPort has been successfully used for data sharing in biomedical research, clinical trials and large scale research collaboration.
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© 2009 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering
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Wang, F., Vergara-Niedermayr, C. (2009). Collaboratively Sharing Scientific Data. In: Bertino, E., Joshi, J.B.D. (eds) Collaborative Computing: Networking, Applications and Worksharing. CollaborateCom 2008. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 10. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03354-4_58
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DOI: https://doi.org/10.1007/978-3-642-03354-4_58
Publisher Name: Springer, Berlin, Heidelberg
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