We will develop a world-class science platform relevant to political decision-makers responsible for housing, transport, employment and urban development in the world's biggest mega-city region, the Pearl River Delta Greater Bay Area. This platform integrates work on inequality indicators and predicting future land use and transport developed in western Europe in London and the Randstad with related work in Shenzhen and Guangzhou, producing a system that will use state-of-the-art simulation models, big data from routine transport, and new ways of using information technology for participatory governance. We argue that such a platform is essential for the very largest cities which are qualitatively different from smaller cities. The platform developed here would be a world first. The 21st century will be dominated by very large urban agglomerations, qualitatively different from those big cities that our contemporary analytical understanding and models of governance are able to handle. The growth of these mega-city regions is heavily influenced by the fusion of existing cities as well as by rapid continental scale migration. This growth is generating severe problems of social segregation, connectivity, mobility, and income inequalities that require new and powerful methods of analytical understanding such as those being developed using real-time 'big' data sources and new information technologies. We propose to develop the platform for prediction and urban governance using the Pearl River Delta 'Greater Bay Area' mega-city region as a demonstrator, bringing sustainability indicators and simulation models from the Greater London and urban Holland (the Randstad) regions to inform the development of an urban data and simulation platform relevant to designing and testing scenarios for new modes of transport and the alleviation of socio-economic inequalities in the Bay Area. These problems, we believe, will be key to mega-city regions during the rest of this century. The project will: (1) integrate already developed Land Use Transportation Interaction (LUTI) models for London and the Randstad with ongoing cellular development and transport models for the Greater Bay Area, (2) develop new indicators for measuring spatial efficiency and equity, (3) develop analytics to inform innovative policy analysis and governance, and (4) demonstrate these tools in association with planning agencies and government across the region. CASA (The Centre for Advanced Spatial Analysis) in University College London (UCL) will coordinate and lead the project and the consortium of seven partners will be based on the GIS group at Birkbeck University of London (BBK), the Geocomputation group at King's College London (KCL), the School of Business and Economics, Vrije Universiteit Amsterdam (VUA), the Geomatics Department and Smart Cities Institute at Shenzhen University (SZU), the Shenzhen Institute of Research and Innovation in the The University of Hong Kong (HKU-SIRI) at Shenzhen, and the Department of Geography at Sun Yat-sen University (SYSU).

Our 21st century lives will be increasingly connected to our digital identities, representations of ourselves that are defined from trails of personal data and that connect us to commercial and public services, employers, schools, families and friends. The future health of our Digital Economy rests on training a new generation of leaders who can harness the emerging technologies of digital identity for both economic and societal value, but in a fair and transparent manner that accommodates growing public concern over the use of personal data. We will therefore train a community of 80 PhD students with the interdisciplinary skills needed to address the profound challenges of digital identity in the 21st century. Our training programme will equip students with a unique blend of interdisciplinary skills and knowledge across three thematic aspects of digital identity - enabling technologies, global impacts and people and society - while also providing them with the wider research and professional skills to deliver a research project across the intersection of at least two of these. Our students will be situated within Horizon, a leading centre for Digital Economy research and a vibrant environment that draws together a national research Hub, CDT and a network of over 100 industry, academic and international partners. Horizon currently provides access to a large network of over 75 potential supervisors, ranging from from leading Professors to talented early career researchers. Each student will work with an industry, public, third sector or international partner to ensure that their research is grounded in real user needs, to maximise its impact, and also to enhance their employability. These external partners will be involved in co-sponsorship, supervision, providing resources and hosting internships. Our external partners have already committed to co-sponsor 30 students so far, and we expect this number to grow. Our centre also has a strong international perspective, working with international partners to explore the global marketplace for digital identity services as well as the cross-cultural issues that this raises. This will build on our success in exporting the CDT model to China where we have recently established a £17M International Doctoral Innovation Centre to train 50 international students in digital economy research with funding from Chinese partners. We run an integrated four-year training programme that features a bespoke core covering key topics in digital identity, optional advanced specialist modules, practice-led team and individual projects, training in research methods and professional skills, public and external engagement, and cohort building activities including an annual writing retreat and summer school. The first year features a nine month structured process of PhD co-creation in which students, supervisors and external partners iteratively refine an initial PhD topic into a focused research proposal. Building on our experience of running the current Horizon CDT over the past five years, our management structure responds to external, university and student input and manages students through seven key stages of an extended PhD process: recruitment, induction, taught programme, PhD co-creation, PhD research, thesis, and alumni. Students will be recruited onto and managed through three distinct pathways - industry, international and institutional - that reflect the funding, supervision and visiting constraints of working with varied external partners.