To a user, the web is an exciting world of interconnected links. Yet to a computer, large portions of the web remains a flat, boring world devoid of meaning, because there is not enough machine-readable information about the semantic relationship between the data. This is a pity, as documents online describe real objects objects and imaginary concepts, and give particular relationships between them.
The Linked Data project develops Tim Berners-Lee's vision of the 'Semantic Web' in which all documents contain semantic information in machine-readable form, and links can be created with relationship values between them. This extra level of semantics enables us to use computer power to exploit the information to a greater extent than through human reading. Today, the concept of linked data has evolved from Berners-Lee's original proposal and plays an increasingly important role on the web.
Our work on the Linked Data project explores various topics from ranking methods for entity-oriented semantic web search, through the exploration of linked open government data, to how machine and human driven computation can be combined to create, manage and use semantic information more effectively.