TY - JOUR PY - 2019// TI - FAIR SCI Ahead: the evolution of the Open Data Commons for preclinical spinal cord injury research (ODC-SCI.org) JO - Journal of neurotrauma A1 - Fouad, Karim A1 - Bixby, John L. A1 - Callahan, Alison A1 - Grethe, Jeffrey S. A1 - Jakeman, Lyn B. A1 - Lemmon, Vance P. A1 - Magnuson, David Sk A1 - Martone, Maryann E. A1 - Nielson, Jessica L. A1 - Schwab, Jan M. A1 - Taylor-Burds, Carol A1 - Tetzlaff, Wolfram A1 - Torres-EspĂn, Abel A1 - Ferguson, Adam R. SP - ePub EP - ePub VL - ePub IS - ePub N2 - Over the last 5 years multiple stakeholders in the field of spinal cord injury (SCI) research have initiated efforts to promote publications standards and to enable sharing of experimental data. In 2016 NIH/NINDS hosted representatives from the SCI community to streamline these efforts and to discuss the future of data sharing in the field according to the FAIR (Findable, Accessible, Interoperable and Reusable) data stewardship principles1. As a next step, a multi-stakeholder group hosted a 2017 symposium in Washington D.C. entitled "FAIR SCI Ahead: the Evolution of the Open Data Commons for Spinal Cord Injury research". The goal of this meeting was to receive feedback from the community regarding infrastructure, policies and organization of a community-governed Open Data Commons (ODC) for preclinical SCI research. Here we summarize the policy outcomes of this meeting and report on progress implementing these policies in the form of a digital ecosystem: the Open Data Commons for Spinal Cord Injury (ODC-SCI.org). ODC-SCI enables data management, harmonization and controlled sharing of data in a manner consistent with the well-established norms of scholarly publication. Specifically, ODC-SCI is organized around virtual 'laboratories' with the ability to share data within each of 3 distinct data sharing spaces: within the laboratory, across verified laboratories, or publicly under a creative commons license (CC-BY 4.0) with digital object identifier (DOI) that enables data citation. The ODC-SCI implements FAIR data sharing and enables pooled data-driven discovery while crediting the generators of valuable SCI data.
Language: en
LA - en SN - 0897-7151 UR - http://dx.doi.org/10.1089/neu.2019.6674 ID - ref1 ER -