Is Neuroscience FAIR? A Call for Collaborative Standardisation of Neuroscience Data.

Area of Science:

• Neuroscience
• Informatics
• Data Science

Background:

• Current neuroscience research faces challenges with data and research object standardization.
• Insufficient standards impede the interoperability and reusability of multi-modal and multiscale neuroscience data.

Purpose of the Study:

• To examine the role of international collaboration and organizations like the International Neuroinformatics Coordinating Facility (INCF) in promoting FAIR data principles for neuroscience.
• To advocate for enhanced standardization of neuroscience data to facilitate research integration and efficient reuse.

Main Methods:

• This perspective article analyzes the current landscape of neuroscience data sharing and standardization.
• It discusses the impact of inadequate standards on research object interoperability and reusability.

Main Results:

• The lack of standardized data formats and protocols is a significant barrier in neuroscience research.
• International collaborative efforts are essential for establishing and implementing effective data standards.

Conclusions:

• Increased international collaboration and standardization are vital for making neuroscience data Findable, Accessible, Interoperable, and Reusable (FAIR).
• Adoption of FAIR principles will foster greater integration and efficient reuse of neuroscience research objects.