What is YAMZ?
YAMZ (Yet Another Metadata Zoo) is a collective and collaborative metadata dictionary designed to support FAIR use of metadata. YAMZ enables individuals and communities of practice to contribute, comment on, and vote on terms.
YAMZ is a dictionary of terms meant to be selectively referenced by future standards. Some are fixed, and some are still evolving. Essentially, YAMZ constitutes a series of nano-specifications with unique, persistent identifiers that track a term from evolving to mature to deprecated.
Current development is focusing on enhancing application features that integrate community member expertise to: 1) determine a canonical set of metadata terms and 2) analyze and improve the quality of related metadata. This notion builds on the ranking/feedback loop that underlies community-driven systems in computer-supported cooperative work. YAMZ is integrating with ORCiD to find new ways for authors to automatically receive recognition for their work and provide opt-in rich profile information to help inform search result rankings.
Getting Involved
The current version of YAMZ is hosted by the Drexel College of Computing and Informatics at https://yamz.net. YAMZ is on Github (https://github.com/metadata-research/yamz). Discussion of YAMZ development and deployment issues takes place at the yamz-forum. The beta site is accessible at yamz.link.
LEADING
Current YAMZ support is via the NSF-U.S. Research Data Alliance/Ronin Institute as part of the IMLS LEADING fellowship program.
Publications
Rauch, C. B., Kelly, M., Kunze, J. A., & Greenberg, J. (2022). FAIR Metadata: A Community-Driven Vocabulary Application. In E. Garoufallou, M.-A. Ovalle-Perandones, & A. Vlachidis (Eds.), Metadata and Semantic Research (pp. 187–198). Springer International Publishing. https://doi.org/10.1007/978-3-030-98876-0_16
Greenberg, J., Murillo, A., Kunze, J., Callaghan, S., Guralnick, R., Nassar, N., … & Patton, C. (2014, January). Metadictionary: advocating for a community-driven metadata vocabulary application. In DC-2013, Lisbon, Portugal. [Google Scholar]
Patton, C. (2014). Community-based scoring of metadictionary terms [PDF]. https://github.com/cjpatton/seaice/blob/master/doc/Scoring.pdf