FAIR Metadata: A Community-driven Vocabulary Application
Christopher B. Rauch (1), Mat Kelly (1), John A. Kunze (2), Jane, Greenberg (1) ((1) Drexel University College of Computing, Informatics,, Philadelphia, PA, USA, (2) California Digital Library, University of, California, Oakland, CA, USA)
TL;DR
This paper introduces YAMZ, a community-driven vocabulary tool designed to enhance FAIR metadata by promoting transparency, engagement, and flexibility, with recent innovations supporting FAIR principles.
Contribution
It presents the development and recent innovations of YAMZ, a community-driven vocabulary application that advances FAIR metadata practices.
Findings
YAMZ supports FAIR principles effectively.
Recent innovations improve community engagement.
YAMZ enhances metadata transparency and flexibility.
Abstract
FAIR metadata is critical to supporting FAIR data overall. Transparency, community engagement, and flexibility are key aspects of FAIR that apply to metadata. This paper presents YAMZ (Yet Another Metadata Zoo), a community-driven vocabulary application that supports FAIR. The history ofYAMZ and its original features are reviewed, followed by a presentation of recent innovations and a discussion of how YAMZ supports FAIR principles. The conclusion identifies next steps and key outputs.
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Taxonomy
TopicsResearch Data Management Practices · Semantic Web and Ontologies