ESIP Recommendations for FAIR Metadata

From Earth Science Information Partners (ESIP)
The printable version is no longer supported and may have rendering errors. Please update your browser bookmarks and please use the default browser print function instead.

Since Wilkenson et al., 2016 introduced the FAIR Principles, discussions and implementation guidelines have been published in almost every possible context. Most of these guidelines are focused on making data and/or repositories FAIR and, because of the nature of the principles, they are generally related to policies and generally high-level guidance.

Many of the FAIR Principles are applicable to metadata as well as data. The original authors point out that “throughout the Principles, we use the phrase ‘(meta)data’ in cases where the Principle should be applied to both metadata and data.” Principles F2 (data are described with rich metadata) and R1 (meta(data) have a plurality of accurate and relevant attributes) mention metadata specifically, but responsibility for identifying specific metadata elements that support FAIR data is left to community standards (Principle R1.3).

The Beyond Data Discovery: Shared Services for Community Metadata Improvement Project (METADIG for short) funded by the U.S. National Science Foundation, recently convened experienced metadata practitioners from several communities (Data One, Long-Term Ecological Research, NOAA, NASA, California Digital Library) to initiate development of community guidelines for FAIR metadata in several dialects (Ecology Metadata Language, ISO 191*, and DataCite). This group introduced initial proposals during the summer meeting of the Earth Science Information Partners (ESIP) along with a repository for community discussion and input.

During the next phase of this project, the ESIP Documentation Cluster will develop the input in the repository into a recommendation document that includes FAIR metadata recommendations in at least three dialects (EML, ISO, and DataCite). The next three cluster meetings (4th Monday at noon Mountain Time) will focus on specific FAIR use cases: