dc.contributor.author |
Das, Samir |
|
dc.contributor.author |
Birdsall Abrams, Mathew |
|
dc.contributor.author |
F. Egan, Gary |
|
dc.contributor.author |
S. Ghosh, Satrajit |
|
dc.contributor.author |
J. Goscinski, Wojtek |
|
dc.contributor.author |
S. Grethe, Jeffrey |
|
dc.contributor.author |
Hellgren Kotaleski, Jeanette |
|
dc.contributor.author |
Tatt Wei Ho, Eric |
|
dc.contributor.author |
N. Kennedy, David |
|
dc.contributor.author |
J. Lanyon, Linda |
|
dc.contributor.author |
B. Leergaard, Trygve |
|
dc.contributor.author |
S. Mayberg, Helen |
|
dc.contributor.author |
Milanesi, Luciano |
|
dc.contributor.author |
Mouček, Roman |
|
dc.contributor.author |
Poline, J. B. |
|
dc.contributor.author |
K. Roy, Prasun |
|
dc.contributor.author |
C. Strother, Stephen |
|
dc.contributor.author |
Tang, Tong Boon |
|
dc.contributor.author |
Tiesinga, Paul |
|
dc.contributor.author |
Wachtler, Thomas |
|
dc.contributor.author |
K. Wójcik, Daniel |
|
dc.contributor.author |
E. Martone, Maryann |
|
dc.contributor.author |
Bjaalie, Jan G. |
|
dc.date.accessioned |
2023-04-17T07:18:36Z |
|
dc.date.available |
2023-04-17T07:18:36Z |
|
dc.date.issued |
2022-01 |
|
dc.identifier.issn |
15392791 |
|
dc.identifier.uri |
http://localhost:8080/xmlui/handle/123456789/2033 |
|
dc.description |
This paper is submitted by the author of IIT (BHU), Varanasi |
en_US |
dc.description.abstract |
There is great need for coordination around standards and best practices in neuroscience to support efforts to make neuroscience a data-centric discipline. Major brain initiatives launched around the world are poised to generate huge stores of neuroscience data.At the same time, neuroscience, like many domains in biomedicine, is confronting the issues of transparency, rigor, and reproducibility. Widely used, validated standards and best practices are key to addressing the challenges in both big and small data science, as they are essential for integrating diverse data and for developing a robust, effective, and sustainable infrastructure to support open and reproducible neuroscience. However, developing community standards and gaining their adoption is difficult. The current landscape is characterized both by a lack of robust, validated standards and a plethora of overlapping,underdeveloped, untested and underutilized standards and best practices. The International Neuroinformatics Coordinating Facility (INCF), an independent organization dedicated to promoting data sharing through the coordination of infrastructure and standards, has recently implemented a formal procedure for evaluating and endorsing community standards and best practices in support of the FAIR principles. By formally serving as a standards organization dedicated to open and FAIR neuroscience, INCF helps evaluate, promulgate, and coordinate standards and best practices across neuroscience. Here, we provide an overview of the process and discuss how neuroscience can benefit from having a dedicated standards body. |
en_US |
dc.description.sponsorship |
Computational Neuroscience & Neuroimaging Laboratory, School of Bio-Medical Engineering, Indian Institute of Technology (BHU), UP, Varanasi, India |
en_US |
dc.language.iso |
en_US |
en_US |
dc.publisher |
Springer |
en_US |
dc.relation.ispartofseries |
Neuroinformatics;Volume 20, Issue 1, Pages 37 - 38 |
|
dc.subject |
Neuroscience |
en_US |
dc.subject |
Neuroinformatics |
en_US |
dc.subject |
Standards Organization for Open and FAIR Neuroscience |
en_US |
dc.subject |
International Neuroinformatics |
en_US |
dc.subject |
Neuroinformatics Coordinating Facility |
en_US |
dc.title |
A Standards Organization for Open and FAIR Neuroscience the International Neuroinformatics Coordinating Facility |
en_US |
dc.type |
Article |
en_US |