Large, open datasets for human connectomics research: Considerations for reproducible and responsible data use
1Department of Physics, Florida International University, Miami, FL, USA.
Neuroimage
|September 18, 2021
Summary
Large, open datasets are revolutionizing human connectomics research. This review highlights progress in data sharing, reproducible analysis, and ethical considerations for brain imaging data.
Area of Science:
- Neuroscience
- Data Science
- Medical Imaging
Background:
- The field of human connectomics increasingly relies on large, open datasets.
- Magnetic resonance imaging (MRI) data sharing has evolved significantly.
- Reproducible data analyses are crucial for scientific validity.
Purpose of the Study:
- To review the evolution of data sharing in human connectomics.
- To summarize challenges and progress in reproducible data analysis.
- To discuss ethical considerations and future directions in connectomics research.
Main Methods:
- Literature review of data sharing practices in human connectomics.
- Analysis of progress in community guidelines, software, and training initiatives.
- Discussion of ethical conduct and social determinants of health in data analysis.
Main Results:
- Significant advancements in developing community guidelines and recommendations.
- Development of improved software and data management tools for connectomics.
- Initiatives to enhance training and education in data analysis and ethics.
Conclusions:
- Future connectomics research requires an emphasis on social determinants of health for diverse samples.
- Interdisciplinary collaboration is key to an innovative and inclusive future for connectomics.
- Ethical conduct is paramount to prevent stigmatization when analyzing large, open datasets.
