Towards FAIR neuroscience: An efficient workflow for sharing and integrating data
Signy Benediktsdottir, Archana Golla, Camilla H. Blixhavn, Eivind Hennestad, Heidi Kleven, Peyman Najafi, Eszter A. Papp, Sophia Pieschnik, Maja A. Puchades, Ingrid Reiten, Ulrike Schlegel, Oliver Schmid, Lyuba Zehl, Andrew P. Davison, Trygve B. Leergaard, Jan G. Bjaalie · FENS Forum 2024
The shift towards open science enables the exploration of an increasing variety of neuroscience datasets. The diversity of data formats, ways to organize and describe data, however, pose a significant challenge for reproducing and reusing scientific outputs. To address this, we developed an efficient data curation workflow for sharing FAIR and integrated neuroscience data. This workflow is well documented and continuously refined to meet researchers' needs.The aim of the data curation process is to build the best possible metadata representation of the data for discoverability and reuse. Accor
ePoster · Neuroscience