Making Linked-Data Accessible: A Review

Linked Data (LD) is a paradigm that utilises the Resource Description Framework (RDF) triplestore to describe numerous pieces of knowledge linked together. When an entity is retrieved in LD, the associated data becomes immediately accessible. SPARQL, the query language facilitating access to LD, contains a complex syntax that requires prior knowledge due to the complexity of the underlying concepts. End-users may experience a sense of intimidation when faced with using LD and adopting the technology into their respective domains. Therefore, to promote LD adoption among end-users, it is crucial to address these challenges by developing more accessible, efficient, and intuitive tools and techniques that cater to users with varying levels of expertise. Users can employ query formulation tools and interfaces to search and extract relevant information rather than manually constructing SPARQL queries. This paper investigates and reviews existing methods for searching and accessing LD using query-building tools, identifies alternatives to these tools, and highlights their applications. Based on the reviewed works, we establish 22 criteria for comparing query builders to identify the weaknesses and strengths of each tool. Subsequently, we identify common usage themes for current solutions employed in accessing and searching LD. Moreover, we explore current techniques utilised for validating these approaches, emphasising potential limitations. Finally, we identify gaps within the literature and highlight future research directions to further advance LD accessibility and usability for end-users.