The rapid evolution of computing, networking, and data capturing technologies, along with advances in data mining and analysis, are fundatmentally changing the way scholarly research is conducted. Web resource aggregations are increasingly essential to scholarship as it embraces these new techniques. In this paper, researchers present a methodology for identifying and describing Web resource aggregations stemming from the Open Archives Initiative-Object Reuse and Exchange (OAI-ORE) project.
The precepts of the architecture of the World Wide Web, the Semantic Web, and the Linked Data initiative serve as the platform of the OAI-ORE specifications, and thus their incorporation into the eScholarship cyberinfrastructure guarantees the integration of scholarly research projects into the Data Web. The OAI-ORE solution tackles the resource aggregation challenge by expressing the data model in terms of the primitives of Web Architecture and the Semantic Web — namely, as Resources, Representations, uniform resource identifiers (URIs), and Resource Description Framework triples.
The aggregation that comprises the central entity in the data model represents a set of other resources, and this approach dovetails with the way in which real-world entities or concepts are included in the Web through the mechanisms proposed by the Linked Data effort. The resource map has a representation that describes the aggregation, and the map can be accessed through the aggregation's URI using the mechanisms defined for Cool URIs for the Semantic Web.
Finally, the resource map's representation consists of a serialization of the triples describing the aggregation. "While OAI-ORE was motivated by scholarly communication, we believe that the proposed solution has broader applicability," write the researchers. "Aggregations, sets, and collections are as common on the Web as they are in the everyday physical world. In many situations it would benefit agents and services if aggregations were unambiguously enumerated and described, essentially layering an additional level of resource granularity upon the Web."
From Linked Data on the Web (LDOW)
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Abstracts Copyright © 2009 Information Inc., Bethesda, Maryland, USA
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