Repositories for Environmental Health Sciences Data
The landscape of biomedical data repositories is vast and evolving. NIH supports many repositories for sharing biomedical data and encourages researchers to use domain-specific, open-access data sharing repositories – whether funded by NIH or other choices – whenever possible. When a domain-specific option is not available, researchers are encouraged to use a generalist repository that accepts data regardless of data type or discipline. To learn more about methods for data sharing and selecting data repositories visit NIH Sharing Scientific Data webpage.
Data and Metadata Standards Resources for Environmental Health Sciences
The Environmental Health Language Collaborative provides resources for getting started with ontologies, terminologies, and tools useful to harmonize EH research. The EHS Ontology Resources Catalog provides a compilation of organizations, ontologies/terminologies, and tools useful to harmonize environmental health research.
Data Management and Sharing Plan Development Resources
For information on NIEHS-specific recommendations on what to include in a Data Management and Sharing (DMS) Plan, please visit the NIEHS Data Management and Sharing Plan Development webpage.
The NIEHS Superfund Research Program Data Sharing Resources webpage provides information and resources on data sharing, data repositories, citing data, data integration, and data science training.
Additionally, several community resources and tools are available to help researchers create, review, and share Data Management and Sharing Plans that meet institutional and funder requirements. Check out the resources below.
- DMPTool: Build a data management plan using this open-access data management plan tool that meets institutional and funder requirements.
- DMPonline: DMPonline helps to create, review, and share data management plans that meet institutional and funder requirements.
- UK Data Service: UK Data Service provides various resources to manage data and includes a checklist for identifying data management and sharing best practices.