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Linked Data in Neuroscience: Applications, Benefits, and Challenges

By B Nolan Nichols, Satrajit S Ghosh, Tibor Auer, Thomas Grabowski, Camille Maumet, David Keator, Maryann E. Martone, Kilian M. Pohl, Jean-Baptiste Poline

Posted 24 May 2016
bioRxiv DOI: 10.1101/053934

The fundamental goal of neuroscience is to understand the nervous system at all levels of description, from molecular components to behavior. The complexity of achieving this goal in neuroscience, and biomedicine in general, poses many technical and sociological challenges. Among these are the need to organize neuroscientific data, information, and knowledge to facilitate new scientific endeavors, provide credibility and visibility of research findings, and increase the efficiency of data reuse. Linked Data is a set of principles based on Web technology that can aid this process as it organizes data as an interconnected network of information. This review examines the history, practical impact, potential, and challenges of applying Linked Data principles to neuroscience.

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