Introduction to FAIR Neuroscience

Introduction to FAIR Neuroscience
Purpose of the study track
This study track is intended for those with a neuroscience background looking to gain a basic understanding of how to implement the FAIR Guiding Principles in their research.
2 lecture/s in this Study track

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Lectures

1
Guiding Principles for FAIR and Open Science

This is the first of two workshops on reproducibility in science, during which participants are introduced to concepts of FAIR and open science.…

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2
Fairness and Health Equity in Machine Learning

This lesson describes a definitional framework for fairness and health equity in the age of the algorithm. While acknowledging the impressive…

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5 course/s in this Study track

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Courses

1
General Perspectives on FAIR

Since their introduction in 2016, the FAIR data principles have gained increasing recognition and adoption in global neuroscience. FAIR defines a…

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2
INCF TrainingSpace
Standards and Best Practices

Standards and best practices make neuroscience a data-centric discipline and are key for integrating diverse data and for developing a robust,…

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3
FAIR Approaches for Computational Neuroscience

As models in neuroscience have become increasingly complex, it has become more difficult to share all aspects of models and model analysis,…

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4
FAIR Approaches for Neuroimaging Research

Over the last three decades, neuroimaging research has seen large strides in the scale, diversity, and complexity of studies, the open…

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5
FAIR Approaches for Electrophysiology

The course provides an introduction to the growing field of electrophysiology standards, infrastructure, and initiatives. From data curation on…

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