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Details of Grant 

EPSRC Reference: EP/L016117/1
Title: EPSRC Centre for Doctoral Training in Web Science Innovation
Principal Investigator: Hall, Professor Dame W
Other Investigators:
Isaksen, Professor L Halford, Professor SJ Shadbolt, Professor N
Weal, Dr MJ Carr, Professor LA
Researcher Co-Investigators:
Project Partners:
BBC BT Business South
Defence Science & Tech Lab DSTL Digital Catapult Edelman
Free (VU) University of Amsterdam Inqb8r Limited KAIST
Nominet Limited Open Data Institute Ordnance Survey
Roke Manor Research Ltd Samsung Serious Organised Crime Agency SOCA
Switch Concepts Ltd
Department: Electronics and Computer Science
Organisation: University of Southampton
Scheme: Centre for Doctoral Training
Starts: 01 October 2014 Ends: 31 March 2023 Value (£): 3,618,520
EPSRC Research Topic Classifications:
Artificial Intelligence Human-Computer Interactions
Information & Knowledge Mgmt
EPSRC Industrial Sector Classifications:
Information Technologies
Related Grants:
Panel History:
Panel DatePanel NameOutcome
23 Oct 2013 EPSRC CDT 2013 Interviews Panel I Announced
Summary on Grant Application Form
Web Science is the science of the World Wide Web and its impact, both positive and negative, on society. The Web is a socio-technical mixture of the people, organizations, browsers, policies, applications, standards, data centres, shopping baskets and social network status updates that have come to shape our everyday lives and global futures. Web Science offers the insights necessary to understand the flow of data and knowledge around the globe, and the social and technical processes that can turn gigabytes and terabytes of raw data and into valuable new applications or evidence-based policy. Web Science helps us appreciate the threats to our online identities but also the opportunities of allowing our personal digital avatars to participate in new kinds of online businesses, online politics and online social engagements. Web Science offers a basis for innovating new personal practices and new social formations, and the ability to predict the consequences for the UK's digitally connected citizens. With an integrated understanding of these research areas, Web Science doctoral graduates will be able to innovate in the shaping of Web growth and Web policy, positioned to lead UK industry and government to reap the maximum economic and social value from its emerging digital economy.

The Centre will recruit 13 excellent candidates annually from a variety of science, engineering, social science and humanities backgrounds. It will provide a cohort-based, 4-year doctoral programme with an initial training year that combines foundational aspects of Web Science research with technical aspects of the Web's architecture, an intensive training in interdisciplinarity and a grounding in innovation. A student-centred process of PhD research selection will begin at the end of the first semester with students starting to negotiate a potential project topic and multidisciplinary supervisor team with members of the Supervisor Forum. The CDT will offer a thorough programme of postgraduate research and professional training in co-ordination with the University Research and Graduate School. Complementary cohort-specific training will be offered to support and enhance the opportunities offered by the CDT (e.g. more intensive team building courses or communication training to prepare for specific industry events). The cohort experience is maintained throughout the PhD with frequent team-based events including collaborations with industry partners and international research exchanges.

The Web Science CDT will use a multidisciplinary training approach that has successfully cut across traditional disciplinary silos in research practice, institutional structure and University administration. Its novel cohort-based training environment creates a socially cohesive and self-supporting group of students that successfully integrate their diverse disciplinary expertise in collaborative teams. Its programme of cross-cohort activities encourages mentorship, thus making the CDT self-sustaining and allowing it to amplify the research leadership of the supervisory staff. The net effect of these cohort benefits is to allow each student to undertake more challenges and to achieve more excellent training outcomes than possible in an individual training regime.
Key Findings
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Potential use in non-academic contexts
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Impacts
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Summary
Date Materialised
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Further Information:  
Organisation Website: http://www.soton.ac.uk