Abstract
The OpenAIRE infrastructure is the point of reference for Open Science in Europe. Its services populate and provide access to a graph of objects relative to publications, datasets, people, organizations, projects, and funders aggregated from a variety of data sources, such as institutional repositories, data archives, journals, and CRIS systems. Not only, objects in the graph are harmonized to achieve semantic homogeneity, de-duplicated and merged, and enriched by inference with missing properties and/or relationships. The OpenAIRE Literature Broker Service is designed to offer subscription and notification functionalities for institutional repositories to: (i) learn about publication objects in OpenAIRE that do not appear in their collection but may be pertinent to it, and (ii) learn about extra properties or relationships relative to publication objects in their collection. Due to the high variability of the information space the following problems may arise: (i) subscriptions may vary over time to adapt to information space evolution, (ii) repository managers need to be able to quickly test their configurations before activating them, (iii) notifications may be redundant, and (iv) notifications may be very large over time. This paper presents the data model and software architecture of the OLBS, specifically designed to address these issues.
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Notes
- 1.
Typologies and numbers of data sources currently included in OpenAIRE are available from https://www.openaire.eu/search/data-providers.
- 2.
- 3.
The Directory of Open Access Repositories, http://www.opendoar.org.
- 4.
OASIS Standard WS-Topics specification 1.3 (2006), http://docs.oasis-open.org/wsn/wsn-ws_topics-1.3-spec-os.pdf.
- 5.
Elasticsearch https://www.elastic.co.
- 6.
PostgreSql http://www.postgresql.org.
- 7.
OASIS Web Services Notification (WSN), https://www.oasis-open.org/committees/tc_home.php?wg_abbrev=wsn (26/01/2016).
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Acknowledgement
This work is partially funded by the EC H2020 project OpenAIRE2020 (Grant agreement: 643410, Call: H2020-EINFRA-2014-1).
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Manghi, P., Atzori, C., Bardi, A., La Bruzzo, S., Artini, M. (2017). Realizing a Scalable and History-Aware Literature Broker Service for OpenAIRE. In: Agosti, M., Bertini, M., Ferilli, S., Marinai, S., Orio, N. (eds) Digital Libraries and Multimedia Archives. IRCDL 2016. Communications in Computer and Information Science, vol 701. Springer, Cham. https://doi.org/10.1007/978-3-319-56300-8_9
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