Implementing a Registry Federation for Materials Science Data Discovery
Raymond L. Plante, Chandler Becker, Andrea M. Medina-Smith, Kevin G. Brady, Alden A. Dima, Benjamin J. Long, Laura M. Bartolo, Robert Hanisch
As a result of a number of national initiatives, we are seeing rapid growth in the data important to materials science that are available over the web. Consequently, it is becoming increasingly difficult for researchers to learn what data are available and how to access them. To address this problem, the Research Data Alliance (RDA) Working Group for International Materials Science Registries (IMRR) was established to bring together materials science and information technology experts to develop an international federation of registries that can be used for global discovery of data resources for materials science. A resource registry collects high-level metadata descriptions of resources such as data repositories, archives, websites, and services that are useful for data-driven research. By making the collection searchable, it aids scientists in industry, universities, and government labs to discover data relevant to their research and work interests. We present the results of our successful piloting of a registry federation for materials science data discovery. In particular, we out a blueprint for creating such a federation that is capable of amassing a global view of all available materials science data, and we enumerate the requirements for the standards that make the registries interoperable within the federation. These standards include a protocol for exchanging resource descriptions and a standard metadata schema for encoding those descriptions. We summarize how we leveraged an existing standard (OAI-PMH) for metadata exchange. Finally, we review the registry software developed to realize the federation and describe the user experience.
, Becker, C.
, Medina-Smith, A.
, Brady, K.
, Dima, A.
, Long, B.
, Bartolo, L.
and Hanisch, R.
Implementing a Registry Federation for Materials Science Data Discovery, CODATA Data Science Journal, [online], https://dx.doi.org/10.1002/http://doi.org/10.5334/dsj-2021-015, http://doi.org/10.5334/dsj-2021-015,https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=929883
(Accessed January 18, 2022)