Current state of Linked Data in digital libraries. (April 2016)

• Record Type: Journal Article
• Authors: Hallo, María; Luján-Mora, Sergio; Maté, Alejandro; Trujillo, Juan
• Is Part Of: Journal of information science. Volume 42:Number 2(2016)
• Page Start: 117
• Page End: 127
• Publication Date: 2016-04
• Subjects: Digital libraries -- Linked Data -- Semantic Web; Information science -- Periodicals; Information science; Periodicals; 020.5
• DOI: 10.1177/0165551515594729
• Languages: English
• ISSNs: 0165-5515

Abstract

The Semantic Web encourages institutions, including libraries, to collect, link and share their data across the Web in order to ease its processing by machines to get better queries and results. Linked Data technologies enable us to connect related data on the Web using the principles outlined by Tim Berners-Lee in 2006. Digital libraries have great potential to exchange and disseminate data linked to external resources using Linked Data. In this paper, a study about the current uses of Linked Data in digital libraries, including the most important implementations around the world, is presented. The study focuses on selected vocabularies and ontologies, benefits and problems encountered in implementing Linked Data in digital libraries. In addition, it also identifies and discusses specific challenges that digital libraries face, offering suggestions for ways in which libraries can contribute to the Semantic Web. The study uses an adapted methodology for literature review, to find data available to answer research questions. It is based on the information found in the library websites recommended by W3C Library Linked Data Incubator Group in 2011, and scientific publications from Google Scholar, Scopus, ACM and Springer from the last 5 years. The selected libraries for the study are the National Library of France, the Europeana Library, the Library of Congress of the USA, the British Library and the National Library of Spain. In this paper, we outline the best practices found in each experience and identify gaps and future trends.