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

• Main Authors: Arianna Becerril-García, Eduardo Aguado-López
• Format: Article
• Language: English
• Published: MDPI AG 2018-06-01
• Series: Information
• Subjects: ontologies; Semantic Web; OAI-PMH; knowledge discovery; awareness to context
• Online Access: http://www.mdpi.com/2078-2489/9/6/144

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.