Abstract

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.

Details

Title
Linked Data in Neuroscience: Applications, Benefits, and Challenges
Author
B Nolan Nichols; Ghosh, Satrajit S; Auer, Tibor; Grabowskith, Thomas J; Maumet, Camille; Keator, David; Pohl, Kilian; Jean-Baptiste Poline
University/institution
Cold Spring Harbor Laboratory Press
Section
Confirmatory Results
Publication year
2016
Publication date
Nov 2, 2016
Publisher
Cold Spring Harbor Laboratory Press
ISSN
2692-8205
Source type
Working Paper
Language of publication
English
ProQuest document ID
2070366325
Copyright
�� 2016. This article is published under http://creativecommons.org/licenses/by/4.0/ (���the License���). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.