The HEAL studies represent a tremendous diversity of scientific enquiry across many disciplines. This cross-disciplinary nature is reflected within the HEAL federated data ecosystem, which leverages existing data repositories and other data resources in a manner that enables the Data Platform to make HEAL data and resources findable. The HEAL Data Stewardship Group (HEAL Stewards) is committed to providing a variety of documents to assist HEAL Investigators in navigating and contributing to the HEAL data ecosystem.
These documents will be updated regularly in the coming months with materials supporting work at all stages of the data lifecycle. If you have questions or would like to discuss specific study needs, please contact us at http://bit.ly/HEALStewardsConnect.
The Data Stewards are here to help you with data management and making your data FAIR. We understand that each study has unique needs and is at different stages of conducting investigation. The documents below are general recommendations and intended to provide support to HEAL studies as they move through their own data lifecycle.
|HEAL Repository Recommendations||Data repositories can ensure HEAL data lives on beyond the horizon of a given research project. This document will provide criteria and recommendations to help studies evaluate and select a repository based on research and community needs.||Fall 2021|
|HEAL Minimal Metadata Standards||Metadata is important for ensuring your data is findable, even if the data cannot be shared. This document will provide recommendations we believe will maximize the value of HEAL data and the HEAL Data Platform. Metadata provides additional information about study data resources, even in cases where the data cannot be publicly available.||Fall 2021|
|HEAL Data Standards for semantic linking, search, and translational use cases||Data standards enable advanced searching to make data finable. This document describes machine readable formats and data modeling standards you can use to make your data easy to find for researchers. It outlines controlled vocabularies, ontologies, and other tools for FAIR curation as they apply to your data.||Fall 2021|