RESUMEN
The joint Open PHACTS/GEN2PHEN workshop on "Solving Bottlenecks in Data Sharing in the Life Sciences" was held in Volendam, the Netherlands, on September 19 and 20, 2011, and was attended by representatives from academia, industry, publishing, and funding agencies. The aim of the workshop was to explore the issues that influence the extent to which data in the life sciences are shared, and to explore sustainability scenarios that would enable and promote "open" data sharing. Several key challenges were identified and solutions to each of these were proposed.
Asunto(s)
Disciplinas de las Ciencias Biológicas/organización & administración , Difusión de la Información , Disciplinas de las Ciencias Biológicas/legislación & jurisprudencia , HumanosRESUMEN
There is an urgent need to improve the infrastructure supporting the reuse of scholarly data. A diverse set of stakeholders-representing academia, industry, funding agencies, and scholarly publishers-have come together to design and jointly endorse a concise and measureable set of principles that we refer to as the FAIR Data Principles. The intent is that these may act as a guideline for those wishing to enhance the reusability of their data holdings. Distinct from peer initiatives that focus on the human scholar, the FAIR Principles put specific emphasis on enhancing the ability of machines to automatically find and use the data, in addition to supporting its reuse by individuals. This Comment is the first formal publication of the FAIR Principles, and includes the rationale behind them, and some exemplar implementations in the community.
Asunto(s)
Recolección de Datos , Curaduría de Datos , Proyectos de Investigación , Sistemas de Administración de Bases de Datos , Guías como Asunto , Reproducibilidad de los ResultadosRESUMEN
WikiProteins enables community annotation in a Wiki-based system. Extracts of major data sources have been fused into an editable environment that links out to the original sources. Data from community edits create automatic copies of the original data. Semantic technology captures concepts co-occurring in one sentence and thus potential factual statements. In addition, indirect associations between concepts have been calculated. We call on a 'million minds' to annotate a 'million concepts' and to collect facts from the literature with the reward of collaborative knowledge discovery. The system is available for beta testing at http://www.wikiprofessional.org.