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Information 2018, 9(6), 144; https://doi.org/10.3390/info9060144

A Semantic Model for Selective Knowledge Discovery over OAI-PMH Structured Resources

Dissemination of Science Research Group, School of Political and Social Sciences, Autonomous University of the State of Mexico, 50100 Toluca de Lerdo, Mexico
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Received: 9 May 2018 / Revised: 31 May 2018 / Accepted: 7 June 2018 / Published: 12 June 2018
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Abstract

This work presents OntoOAI, a semantic model for the selective discovery of knowledge about resources structured with the OAI-PMH protocol, to verify the feasibility and account for limitations in the application of technologies of the Semantic Web to data sets for selective knowledge discovery, understood as the process of finding resources that were not explicitly requested by a user but are potentially useful based on their context. OntoOAI is tested with a combination of three sources of information: Redalyc.org, the portal of the Network of Journals of Latin America and the Caribbean, Spain, and Portugal; the institutional repository of Roskilde University (called RUDAR); and DBPedia. Its application allows the verification that it is feasible to use semantic technologies to achieve selective knowledge discovery and gives a sample of the limitations of the use of OAI-PMH data for this purpose. View Full-Text
Keywords: ontologies; Semantic Web; OAI-PMH; knowledge discovery; awareness to context ontologies; Semantic Web; OAI-PMH; knowledge discovery; awareness to context
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Becerril-García, A.; Aguado-López, E. A Semantic Model for Selective Knowledge Discovery over OAI-PMH Structured Resources. Information 2018, 9, 144.

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