Facilitating Casual Users in Interacting with Linked Data through Domain Expertise

Abstract

Linked Data use has expanded rapidly in recent years; however there is still a lack of support for casual users to create complex queries over this Web of Data. Until this occurs, the real benefits of having such rich metadata available will not be realised by the general public. This paper introduces an approach to supporting casual users discover relevant information across multiple Linked Data repositories, by enabling them to leverage and tailor semantic attributes. Semantic attributes are semantically meaningful terms that encapsulate expert rules encoded in multiple formats, including SPARQL. Semantic attributes are created in SABer (Semantic Attribute Builder), which is usable by non-technical domain experts. This opens the approach to almost any domain. A detailed evaluation of SABer is described within this paper, as is a case study that shows how casual users can use semantic attributes to explore multiple structured data sources in the music domain.