Data science and its future in large neuroscience collaborations

Area of Science:

• Neuroscience
• Data Science
• Scientific Collaboration

Background:

• Large-scale neuroscience research, particularly within initiatives like the NIH's BRAIN Initiative, necessitates robust and scalable data management strategies.
• The optimal practical implementation of data management for extensive scientific collaborations remains an unresolved challenge.

Approach:

• A comprehensive data science survey was administered to active U19 grants funded by the NIH's BRAIN Initiative.
• The survey targeted data science liaisons and Principal Investigators, representing approximately 500 researchers across 21 national collaborations.
• The study documented current tools, technologies, and methodologies employed in neuroscience data science.

Key Points:

• Current data science practices in neuroscience collaborations exhibit several identified shortcomings.
• The survey provides insights into the existing landscape of data management tools and techniques.
• Analysis highlights areas for improvement in data handling within large research networks.

Conclusions:

• The findings inform the development of strategic plans and policy recommendations.
• Proposed policies aim to enhance data collection, utilization, publication, and reuse in neuroscience.
• Recommendations include a focus on improving data science training for the neuroscience community.