Mapping solid earth data and research infrastructures to CERIF

Bailo, Daniele; Ulbricht, Damian; Nayembil, Martin L.; Trani, Luca; Spinuso, Alessandro; Jeffery, Keith G.. 2017 Mapping solid earth data and research infrastructures to CERIF. Procedia Computer Science, 106. 112-121. 10.1016/j.procs.2017.03.043

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Official URL: https://doi.org/10.1016/j.procs.2017.03.043

Abstract/Summary

EPOS is a Research Infrastructure plan that is undertaking the challenge of integrating data from different solid Earth disciplines and of providing a common knowledge-base for the Solid-Earth community in Europe, by implementing and managing a logically centralised catalog based on the CERIF model. The EPOS catalogue will contain the information about all the participating actors, such as Research Infrastructures, Organisations and their assets, in relationship with the people, their roles and their affilitation within the specific scientific domain. The catalogue will guarantee the discoverability of domain specific data, data products, software and services (DDSS) and enable the EPOS Integrated Core Services system to perform - on behalf of a end user – advanced operations on data as for instance processing and visualization. It will also foster the homogenisation of vocabularies, as well as supporting heterogeneous metadata. Clearly, the effort of accomodating the diversities across all the players needs to take into account of existing initiatives concerning metadata standards and institutional recommendations, trying to satisfy the EPOS requirements by incorporating and profiling more generic concepts and semantics. The paper describes the approach of the EPOS metadata working group, providing the rationale behind the integration, extension and mapping strategy to converge the EPOS metadata baseline model towards the CERIF entities, relationships and vocabularies. Special attention will be given to the outcomes of the mapping process between two elements of the EPOS baseline - Research Infrastructure and Equipment - and CERIF, by providing detailed insights and description of the two data models, of encountered issues and of proposed solutions.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	10.1016/j.procs.2017.03.043
ISSN:	18770509
Date made live:	04 Aug 2017 13:54 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/517483

Item Type:

Publication - Article

Digital Object Identifier (DOI):

10.1016/j.procs.2017.03.043

ISSN:

18770509

Date made live:

04 Aug 2017 13:54 +0 (UTC)

URI:

https://nora.nerc.ac.uk/id/eprint/517483