Library Linked Data Models: Library Data in the Semantic Web

Hyoungjoo Park & Margaret Kipp

This exploratory study examined Linked Data (LD) schemas/ontologies and data models proposed or in use by libraries around the world using MAchine Readable Cataloging (MARC) as a basis for comparison of the scope and extensibility of these potential new standards. The researchers selected 14 libraries from national libraries, academic libraries, government libraries, public libraries, multi-national libraries, and cultural heritage centers currently developing Library Linked Data (LLD) schemas. The choices of models, schemas, and elements used in each library's LD can create interoperability issues for LD services because of substantial differences between schemas and data models evolving via local decisions. The researchers observed that a wide variety of vocabularies and ontologies were used for LLD including common web schemas such as Dublin Core (DC)/DCTerms, and Resource Description Framework (RDF), as well as deprecated schemas such as MarcOnt and rdagroup1elements. A sharp divide existed as well between LLD schemas using variations of the Functional Requirements for Bibliographic Records (FRBR) data model and those with different data models or even with no listed data model. Libraries worldwide are not using the same elements or even the same ontologies, schemas and data models to describe the same materials using the same general concepts.

Cataloging & Classification Quarterly
Library linked data, Semantic Web, linked data, data model, metadata, cataloging
發布日期:2019年09月26日 最後更新:2019年10月09日