Web Science

The growth and use of the Web across a number of disciplines is increasing at a remarkable rate, offering new possibilities to study and solve problems on the Web. Researchers in various domains of interest are structuring their agenda to create new and revolutionary capabilities or exploit the opportunities created by the ubiquitous, mobile and media-rich Web. However, without a fundamental understanding of the current and evolving Web trends, these opportunities may be missed or delayed.

This course unveils the foundations of the World Wide Web, including key semantic Web technologies used in processing machine-readable data across emerging Web intelligence based applications. The course provides a practical roadmap to represent a particular knowledge on the Web and advocates ad-hoc semantic search, that go beyond traditional information retrieval approaches. Hence, semantically enriched data on the Web is a prime focus of this course.

Major topics cover the suite of technologies used for designing and developing semantic Web content repositories for domain-related knowledge and practices. The purpose is to integrate prevailing unstructured data into a domain-specific knowledge inference process that harnesses content heterogeneity and ambiguity. These latter barriers are overcome by combining standard technologies, including a distributed addressing and naming mechanism (Uniform Resource Identifiers or URIs), a formal knowledge representation (RDF and OWL), and a common query language (SPARQL). The autonomous capability of managing knowledge on the Web is extended to the physical, real-time world using a myriad of embedded devices, leading to the evolution of Web of Things. This future trend and its promising applications are also discussed in this course.

 

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