Abstract
We present a modular, high performance, open-source database system that incorporates popular neuroimaging database features with novel peer-to-peer sharing, and a simple installation. An increasing number of imaging centers have created a massive amount of neuroimaging data since fMRI became popular more than 20 years ago, with much of that data unshared. The Neuroinformatics Database (NiDB) provides a stable platform to store and manipulate neuroimaging data and addresses several of the impediments to data sharing presented by the INCF Task Force on Neuroimaging Datasharing, including 1) motivation to share data, 2) technical issues, and 3) standards development. NiDB solves these problems by 1) minimizing PHI use, providing a cost effective simple locally stored platform, 2) storing and associating all data (including genome) with a subject and creating a peer-to-peer sharing model, and 3) defining a sample, normalized definition of a data storage structure that is used in NiDB. NiDB not only simplifies the local storage and analysis of neuroimaging data, but also enables simple sharing of raw data and analysis methods, which may encourage further sharing.
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Acknowledgments
Features and ideas for the Neuroinformatics Database were conceived by many individuals over the course of its development. In this way, the entire staff of the Olin Neuropsychiatry Research Center contributed to its development. Development of NiDB was supported by the National Institutes of Health (NIH) from the following grants: R37-MH43775 (NIMH), R01-AA016599 (NIAAA), RC1-AA019036-01 (NIAAA), P50-AA12870-11 (NIAAA), R01-MH077945 (NIMH), R01-MH080956-01 (NIMH), R01-MH081969 (NIMH), R01-MH082022 (NIMH), R03-DA027893 (NHLBI), R01-EB006841 (NIH/NIBIB), R44-MH075481-03A2 (NIMH), R01-AA015615-01 (NIAAA), R01-DA020709 (NIDA), RC1-MH089257 (NIH/NIMH), R01-MH074797-01 (NIMH).
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Book, G.A., Anderson, B.M., Stevens, M.C. et al. Neuroinformatics Database (NiDB) – A Modular, Portable Database for the Storage, Analysis, and Sharing of Neuroimaging Data. Neuroinform 11, 495–505 (2013). https://doi.org/10.1007/s12021-013-9194-1
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DOI: https://doi.org/10.1007/s12021-013-9194-1