The FAIR principles, developed by the neuroscience community with the objective of promoting open science, are outlined by the International Neuroinformatics Coordinating Facility as ensuring data is findable, accessible, interoperable, and reusable.
These principles aim to enhance the ability of machines to find and use data, allowing individual researchers to cite data sets to inform more advanced studies — in short, how machines can solve the problem of having too much data to sort, in no single format.
Representing tool development initiatives, publishing, and data science, speakers from academia and industry across the globe come together in this workshop to present solutions for sharing, publishing, and collaborating in neuroscience.
They’ll cover the principles in detail, data standards and repositories, ethical and legal issues such as General Data Protection Regulation in the European Union, and Brain Imaging Data Structure, a way of organizing neuroimaging and behavioral data. From the publishing perspective, they’ll also propose questions to consider when publishing a paper, such as how to share your data and what information to make available.
To learn more about the best practices for data sharing, watch workshops on FAIR in neurotrauma and improving reproducibility in neuroscience.