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Several principles have guided our discussions and influenced the projects selected by ontology team members. The group early on confirmed the intention stated in the proposal to reuse appropriate parts of currently available ontologies rather than building a new, self-contained ontology for LD4L. While there are advantages to working from a blank slate, we believe it makes eminent sense for a project focused on linked data to draw as much as possible on existing ontologies that have already have achieved significant adoption or show promise for doing so.
At the outset the ontology team recognized the existence of a great deal of prior art in the form of published ontologies and significant ongoing ontology initiatives addressing the representation of bibliographic information in RDF. Elements of the Bibliographic Ontology and FaBIO had already been incorporated into the VIVO-ISF ontology Ontology (GitHub) and were familiar to team members from previous work – and Paolo Ciccarese from Harvard was a principal FABIO FaBIO contributor. The BIBFRAME initiative at the Library of Congress addresses the representation of MARC metadata in RDF, while OCLC has worked to extend the Schema.org ontology as a bridge between the library community and the Web. The Collections ontology and ORE address collections of digital objects; the Open Annotation Data Model annotations, and PROV-O and PAV provenance. Ongoing work in the Hydra Community addresses repr
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SRSIS OntologyBecause no existing ontology supports the range of entities and relationship that SRSIS will encompass, we will use the Protégé ontology editor to develop a SRSIS ontology framework that reuses appropriate parts of currently available ontologies while introducing extensions and additions where necessary. The framework will be based on and remain compatible with the existing VIVO and emerging research dataset and research resource ontology work. It will be sufficiently expressive to encompass traditional catalog metadata from both Cornell and Harvard, the basic linked data elements described in the Stanford Linked Data Workshop Technology Plan, and the usage and other contextual elements from StackLife. The ontology will capture a series of basic concepts and be structured as modules that draw inspiration from and reuse existing ontology classes and properties where appropriate, such as the Semantic Publishing and Referencing ontologies, and that also support arbitrary system-wide refinement, including local extensions. |
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While our library catalogs are very likely the largest single sources of metadata, each partner university maintains a large number of digital collections representing a diversity of subject domains, size, and complexity. Several of our use cases involve connecting catalog data with these non-MARC sources, not only to provide a more unified search interface, but to be able to interconnect and cross-references sources that for now remain almost entirely separate. The benefits go both ways, and the addition of sources outside the traditional library domain brings in yet more possibilities for value-added services enhanced by entity recognition and external links. Prime examples of these non-library sources are Stanford's Profiles (CAP Network software), Harvard's Faculty Finder (Harvard Catalyst Profiles software), and Cornell's VIVO (VIVO software and VIVO-ISF Ontology ).
- Linked Data in VRA Core 4.0: Converting VRA XML Records into RDF/XML (Jeff Mixter)
- PBcore – Public Broadcasting Metadata Dictionary Project
Annotations and virtual collections
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