Registry Interfaces Version 1.1

Dower, Theresa; Demleitner, Markus; Benson, Kevin; Plante, Ray; Auden, Elizabeth; Graham, Matthew; Greene, Gretchen; Hill, Martin; Linde, Tony; Morris, Dave; O`Mullane, Wil; Rixon, G.; Stebe, A.; Andrews, Kona

doi:10.5479/ads/bib/2018ivoa.spec.0723d

Cited by 1 publication

(3 citation statements)

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“…OAI-PMH is quite flexible in how it can be used; however, additional care must be taken to ensure that metadata records get replicated in a timely and efficient manner. We recommend a profile like that defined and used by the registry standard of the International Virtual Observatory Alliance (IVOA) ( Dower 2018 ) which has the following features:…”

Section: Oai-pmh As a Standard Exchange Protocolmentioning

confidence: 99%

“…We note that while our registry contains only coarse-grained view of the materials science data that is out there, this does not prevent us from using it to discover and download individual datasets. As an example, from the astronomical community, the virtual observatory framework features a registry as the first step in an automated data discovery process: the registry is used to find the repositories and portals where data is served ( Dower, 2018 ). Users can be directed to those portals; however, if the sites have also registered search services, those sites can be queried automatically to find individual datasets or measurements.…”

Section: Introduction: Targeted Problem Space and Goalsmentioning

confidence: 99%

“…This paper focuses on the registry framework that was adopted for the Working Group’s working demonstration of a registry federation for discovering data resources for MSE research. It is based on the architecture and experience built by the International Virtual Observatory Alliance (IVOA; Dower, 2018 ) and attempts to generalize their approach for application to any discipline. In particular, extract the key requirements that makes a registry federation work.…”

Section: Introduction: Targeted Problem Space and Goalsmentioning

confidence: 99%

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Implementing a Registry Federation for Materials Science Data Discovery

Plante

Becker

Medina-Smith

et al. 2021

Data Science Journal

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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 laboratories 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.

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Section: Oai-pmh As a Standard Exchange Protocolmentioning

confidence: 99%

Section: Introduction: Targeted Problem Space and Goalsmentioning

confidence: 99%

Section: Introduction: Targeted Problem Space and Goalsmentioning

confidence: 99%

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