PT  - JOURNAL ARTICLE
AU  - B Nolan Nichols
AU  - Satrajit S. Ghosh
AU  - Tibor Auer
AU  - Thomas Grabowski
AU  - Camille Maumet
AU  - David Keator
AU  - Maryann E. Martone
AU  - Kilian M. Pohl
AU  - Jean-Baptiste Poline
TI  - Linked Data in Neuroscience: Applications, Benefits, and Challenges
AID  - 10.1101/053934
DP  - 2016 Jan 01
TA  - bioRxiv
PG  - 053934
4099  - http://biorxiv.org/content/early/2016/11/02/053934.short
4100  - http://biorxiv.org/content/early/2016/11/02/053934.full
AB  - 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.