For scientists and data managers to create high quality EML metadata for dataset publication. EAL is optimized for automating recurring publications (time series or data derived from time series sources) but works well for "one-off" publications, especially through the MetaShARK interface. EAL prioritizes automated metadata extraction from data objects to minimize required human effort and encourages EML best practices to make publications Findable, Accessible, Interoperable, and Reusable.
- Optimized for automating recurring data publications
- Works well for one-off data publications
- Prioritizes automated metadata extraction from data objects
- Aligns with EML best practices of the U.S. Long Term Ecological Research Network (LTER)
- Requires no familiarity with EML
- Requires little familiarity with the R language
- Accepts all data types
- Is data repository agnostic
# Install from GitHub remotes::install_github("EDIorg/EMLassemblyline")
- Creating a Shiny interface for editing metadata template files thereby eliminating requirements for text and spreadsheet editors while facilitating use of dictionaries, vocabularies, and ontologies. This is under development in the MetaShARK application, developped by the PNDB (French Biodiversity National Data Hub).
- Aligning EAL with a profile of the most commonly used EML elements to provide an exchange interface with other information systems (e.g. LTER-core-metabase).
- See project issues for more.
This project uses semantic versioning.
Several people have contributed to this project. List of contributors.