Linked Data Application Wins the UK Discovery Developer Competition

DiscoBro, an application developed by Mathieu d’Aquin from KMi, is one of the three winners of a developer competition organized by the Resource Discovery Task Force and also won the award for the best use of the MusicNet linked dataset.

The aim of the competition was to demonstrate the benefits of open data and metadata to improve the utility of libraries, archives and museums for their users. Entries were required to make use of one or more of ten listed data sources, and were evaluated based on their usability and utility, especially in tasks related to the discovery of useful resources within the considered datasets.

DiscoBro, which is short for “Discovery Browser” is a simple Web application that makes it possible to discover data resources while browsing the Web.

It takes the form of a bookmarklet that can be dragged in the bookmark bar of the browser. While reading a page, the bookmarklet can be clicked to make appear on the side of it terms that correspond to resources mentioned in the text of the page. Each term links to the description of the corresponding resource in DBPedia (the Linked Data version of Wikipedia). Also, if the same term is described in one another data source, (e.g., MusicNet or ArchiveHub), links will appear in the list, to connect to the discovered resources.

What is remarkable here is how well such a simple addition to our usual interaction with Web content directly demonstrates the potential of linked data in terms of opening up to the discovery and reuse of online resources. Indeed, as expressed by Joy Palmer, Project Manager for UK Discovery, in her summary of the competition “instantly (it seems to me) we’re forced beyond the finding aid and document-centric mindset, and thinking about our descriptions as data that needs to be interlinkable to be found and used. It is remarkable how well Discobro works. My own search for the Stanley Kubrick archives in the Archives Hub using the bookmarklet immediately provided multiple links out to DBpedia entries on Kubrick’s life, cinematography, and films. All this is not achieved through a manual mashing of data, but an automatic ‘meshing’ that can scale (which is perhaps one of the most heady promises of Linked Data).”

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