The realm of neuroscience has seen exponential growth in the quantity and complexity of data being generated across its various sub-disciplines. Despite the wealth of data, the capacity to effectively share, integrate, and reproduce findings remains a challenge. This is primarily due to a number of factors including the lack of standardization in data protocols and formats employed by neuroscientists as well as diverse data protection regulations and governance mechanisms. To address this, the FAIR (Findable, Accessible, Interoperable, and Reusable) principles have been introduced, focusing on ensuring data is efficiently structured and shared for optimal reuse. Several initiatives are also underway to address the lack of harmonized governance of brain data.

The ultimate goal of this Research Topic is to promote understanding and the application of Open and FAIR data principles in neuroscience research. These principles can revolutionize data-sharing protocols, making neuroscience data more accessible and reusable, hence leading to more comprehensive and integrative neuroscientific discoveries. Advances in metadata and ontologies are critical tools in achieving this goal, as they standardize and structure data for optimal sharing and integration across diverse neuroscience databases.

This Research Topic aims to explore the challenges, solutions, and innovative approaches related to Open and FAIR data in neuroscience, specifically focusing on the following themes:
-Open-source software and tools for achieving Open and FAIR data in neuroscience
-Infrastructure (cloud services, server capabilities, etc.) to manage and handle Open and FAIR neuroscience data.
-Implementation and development of metadata and ontologies in neuroscience research
-Cognitive, Behavioral and Computational aspects of using FAIR Data in Neuroscience
-Challenging and innovative uses of FAIR principles in neuroscience
-Case studies highlighting the outcomes of FAIR data application
-New policies and standards for data storage and usage in neuroscience
-Ethical considerations of Open and FAIR data in neuroscience.
-Data Governance Approaches for FAIR Data in Neuroscience

We welcome a variety of manuscript types, including original research papers, methodological papers, review articles, and short communication papers that contribute to these themes. We encourage interdisciplinary collaboration, bringing together neuroscientists, data scientists, policymakers, and professionals in ethics and law.

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Frontiers in Neuroinformatics

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