Journal article Open Access
Martin, Paul;
Remy, Laurent;
Theodoridou, Maria;
Jeffery, Keith;
Zhao, Zhiming
Virtual Research Environments (VREs), also known as science gateways or virtual laboratories, assist researchers
in data science by integrating tools for data discovery, data retrieval, workflow management
and researcher collaboration, often coupled with a specific computing infrastructure. Recently, the push
for better open data science has led to the creation of a variety of dedicated research infrastructures
(RIs) that gather data and provide services to different research communities, all of which can be used
independently of any specific VRE. There is therefore a need for generic VREs that can be coupled
with the resources of many different RIs simultaneously, easily customised to the needs of specific
communities. The resource metadata produced by these RIs rarely all adhere to any one standard
or vocabulary however, making it difficult to search and discover resources independently of their
providers without some translation into a common framework. Cross-RI search can be expedited by
using mapping services that harvest RI-published metadata to build unified resource catalogues, but
the development and operation of such services pose a number of challenges.
In this paper, we discuss some of these challenges and look specifically at the VRE4EIC Metadata
Portal, which uses X3ML mappings to build a single catalogue for describing data products and other
resources provided by multiple RIs. The Metadata Portal was built in accordance to the e-VRE Reference
Architecture, a microservice-based architecture for generic modular VREs, and uses the CERIF standard
to structure its catalogued metadata. We consider the extent to which it addresses the challenges of
cross-RI search, particularly in the environmental and earth science domain, and how it can be further
augmented, for example to take advantage of linked vocabularies to provide more intelligent semantic
search across multiple domains of discourse.
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2019.journal.fgcs.semantic-mapping-camera.pdf
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