Lifting the Lid on Linked Data
High quality research and teaching relies partly on access to a broad range of resources. Archive and library materials inform and enhance knowledge, and their value could be increased if the data can be made to "work harder", by using it in different ways and repurposing it for different contexts. Providing bibliographic and archive data as Linked Data allows for the development of new channels into the data and new connections with other data sources. Researchers are more likely to discover sources that may materially affect their research outcomes, and the 'hidden' collections of archives and special collections are more likely to be exposed and used.
This session will explore the progress of the JISC-funded LOCAH Project: Linked Open Copac and Archives Hub. The project aims to make records from the Archives Hub service and Copac service available as Linked Data. The Archives Hub is an aggregation of archival metadata from repositories across the UK; Copac provides access to the merged library catalogues of libraries throughout the UK, including all national libraries. In each case the aim is to provide Linked Data according to the principles set out by Tim Berners-Lee, so that we make our data interconnected with other data and contribute to the growth of the Semantic Web.
The presentation will cover aspects of data modelling, the selection of vocabularies and the design of URI patterns. It will examine options for enriching the data, to provide links to other datasets. A prototype visualisation will be shown, demonstrating how Linked Data can enable researchers to interrogate data in different ways. The different approaches taken for the archival data and bibliographic data will be contrasted to demonstrate how the goal of Linked Data can be interpreted in different ways. The presentation will conclude with a look at some of the main opportunities and barriers to the creation and use of Linked Data.
This presentation will move beyond the theoretical of Linked Data to concentrate on the practical: is it easy to do? What sorts of approaches are there? What are the challenges?