Workshop: Registering and Using Compact Identifiers Biomedical Data Citation

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Instructors: Sarala Wimalaratne, European Bioinformatics Institute (EMBL-EBI); John Kunze, California Digital Library (CDL)

Level: Beginner to Intermediate

Time: 1 hour

Abstract:

Compact Identifiers – sometimes called CURIEs - have been widely and informally used in biomedical informatics. They have recently been formalized in a cross-system implementation with formal support agreements now in place between major institutions.  Compact Identifier resolvers now in place support Web resolution for names of biomedical digital entities based on a registry of namespaces and a set of redirection rules. Rules are also being added for names beyond the biomedical domain (ORCID, ISSN, ARK, GRID, etc). The system is supported as production-grade software by two major research institutions in North America and in Europe.

Compact Identifiers consist of two parts: 1) a unique prefix or namespace indicating the assigning authority and 2) a locally assigned identifier sometimes called a database accession number. The first (prefix) part is useful to avoid global identifier collisions when integrating datasets run by different communities and consortia under a variety of autonomous data management systems and practices. Compact Identifiers will resolve correctly when the prefix is properly registered, and the PREFIX:ACCESSION string is appended to a proper resolver address. Currently resolvers supported by the California Digital Library and the European Bioinformatics Institute (EMBL-EBI) support this model and share a common namespace prefix registry.

This micro-course will introduce Compact Identifiers, and discuss their role as globally resolvable identifiers for data, especially where DOIs are not readily available. It will show how to request and register a namespace prefix for your data; discuss resolver and resolution options where there are multiple provider choices; and show how Compact Identifiers work in the evolving data citation ecosystem.

 

Learning this simple and straightforward technique allows any data to be made citable.