Community Research and Development Information Service - CORDIS

Optimising the benefits of digital libraries

New software solutions make searching digital libraries easier and more productive.
Optimising the benefits of digital libraries
A digital library is any computerised system that distributes digital content to a community of users. Most digital libraries have twin functions of storing and preserving content, and delivering it to end users. These may be humans or other software applications.

Often, however, digital libraries incompletely utilise modern technology, imposing bottlenecks and inefficiencies on their potential use. Semantic web technologies offer solutions by improving searchability for humans, and assisting software to track connections and links. These relatively new technologies have yet to be fully adopted by the digital library market.

One EU-funded initiative aimed to support European small and medium-sized enterprises (SMEs) by helping them improve their services through semantic web technologies. The 'Semantic tools for digital libraries' (SEMLIB) project was a collaboration among one Irish and one Italian university, and four SMEs. It began in 2011, securing funding for 24 months. Its three main goals included developing software tools that facilitate export and republishing of metadata, exploit the republished metadata, and use it to improve searching and browsing.

The collaboration resulted in two new software tools. The Pundit web annotation system allows users to annotate web pages, and to link those notes to other web pages or web objects. This creates a network of linked web objects, a potentially valuable resource showing connections and structure in apparently unrelated objects. It may, for example, be used as an individual or collaborative research tool, drawing together snippets of related information from various web sources. Pundit is open-source software. SLDR is a linked data recommendation system. It is essentially a database of related objects, which uses semantic engines to recommend additional similar content. The system will intelligently extrapolate from input search terms to suggest other terms, similar to what the user intended.

The SEMLIB project achieved its aims, and has implemented its software tools as demonstrative applications for four European SMEs. The software brings clear advantages to these SME contexts, and helps improve their services.

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