NIBIB is focusing on engineering the future of health by supporting technology development to advance and improve health. NIBIB continues to strongly encourage researchers to share their research findings (both positive and negative) through various forms of manuscript publications (e.g. journals, conference papers, preprints, etc.). Scientific data and its associated metadata supporting research findings should be managed, shared, and cited (through DOIs or other PIDs, if applicable) in the corresponding publications. The managing and sharing of scientific data should follow the NIH DMS policy. NIBIB applicants should follow the NIH DMS policy, as described below.
Planning and Budgeting for Data Management & Sharing
NIH expects applicants to submit a plan for how they will manage and share their data and allows applicants to include certain costs associated with data management and sharing in their budget. Prospectively planning for how scientific data will be managed and ultimately shared is a crucial first step in optimizing the reach of data generated from NIH-funded research. Investigators and institutions are encouraged to consider these crucial elements early in research planning.
Writing a Data Management & Sharing Plan
Budgeting for Data Management & Sharing
Data management is the process of validating, organizing, protecting, maintaining, and processing scientific data to ensure the accessibility, reliability, and quality of the data for its users. Proper data management is crucial for maintaining scientific rigor and research integrity.
Data Management Principles
Sharing Scientific Data
Sharing scientific data accelerates biomedical research discovery, enhances research rigor and reproducibility, provides accessibility to high-value datasets, and promotes data reuse for future research studies. Under the NIH Data Management & Sharing Policy, investigators are empowered to choose the most appropriate methods for sharing scientific data. Learn more about methods for data sharing and selecting data repositories.
Data Sharing Approaches
Selecting a Data Repository