The Horizon institute is a multidisciplinary centre of excellence for Digital Economy (DE) research. The core mission of Horizon has been to balance the opportunities arising from the capture, analysis and use of personal data with an awareness and understanding of human and social values. The focus on personal data in a wide range of contexts has required the development of a broad set of multidisciplinary competencies allowing us to build links from foundational algorithms and system to issues of society and policy. We follow a user-centred approach, undertaking research in the wild based on principles of open innovation. Horizon now encompasses over 50 researchers, spanning Computing, Engineering, Law, Psychology, Social Sciences, Business and the Humanities. It has grown a diverse network of over 200 external partners who are involved in ongoing collaborative research and impact with Horizon, ranging from major international corporations to SMEs, from a wide variety of sectors, alongside government and civil society groups. We have also established a CDT in the third wave of funding that will eventually deliver 150 PhDs. Our critical mass of researchers, partners, students and funding has already led to over 800 peer-reviewed publications, composed of: 277 journal articles, 51 books and book chapters, and 424 conference papers, in a total of 15 different disciplines. Over the years Horizon's focus has evolved from an emphasis on the collection and understanding of personal data to consider the user-centred design and development of data-driven products. This proposal builds on our established interdisciplinary competencies to deliver research and impact to ensure that future data-driven products can be both co-created and trusted by consumers. Core to our current vision is the idea that future products will be hybrids of both the digital and the physical. Physical products are increasingly augmented with digital capabilities, from data footprints that capture their provenance to software that enables them to adapt their behaviour. Conversely, digital products are ultimately physically experienced by people in some real-world context and increasingly adapt to both. This real-world context is social; hence the data is social and often implicates groups, not just individuals. We foresee that this blending of physical and digital will drive the merging of traditional goods, services and experiences into new forms of product. We also foresee that - just as today's social media services are co-created by consumers who provide content and data - so will be these new data-driven products. At the same time, we are also witnessing a crisis of trust concerning the commercial use of personal data that threatens to undermine this vision of data-driven products. Hence, it is vitally important to build trust with consumers and operate within an increasingly complex regulatory environment from the earliest stages of innovating future products. Our user-centred approach involves external partners and the public in "research-in-the-wild", grounding our fundamental research in real world challenges. Our delivery programme combines a bottom-up approach in which researchers are given the opportunity (and provided with the skills) to follow new impact opportunities in collaboration with partners as they arise (our Agile programme), with a top-down approach that strategically coordinates how these activities are targeted at wider communities (our Campaigns programme, with successive focus on Consumables, Co-production and Welfare), and reflective processes that allow us to draw out broader conclusions for the widest possible impact (our Cross-Cutting programme). Throughout we aim to continue to develop the capacity in our researchers, the wider DE research community and more broadly within society, to engage in responsible innovation using personal data within the Digital Economy.

Algorithms and Artificial Intelligence play a key role nowadays in many technological systems that control or affect various aspects of our lives. They optimise our driving routes every day according to traffic conditions; they decide whether our mortgage applications get approved; they even recommend us potential life partners. They work silently behind the scene without much of our notice, until they do not. Few of us would probably think much about it when our credit card application is approved in two seconds. Only when it is rejected, do we start to question the decision. Most of the time, the answers we get are not satisfactory, if we get any at all. The spread of such opaque automated decision-making in daily life has been driving the public demand for algorithmic accountability - the obligation to explain and justify automated decisions. The main concern is that it is not right for those algorithms, effectively black boxes, to take in our data and to make decisions affecting us in ways we do not understand. For this reason, the General Data Protection Regulation requires that we, as data subjects, be provided with "meaningful information about the logic involved, as well as the significance and the envisaged consequences of such processing." Likewise, consumers should be treated fairly when receiving financial services as per financial services regulations and algorithms should be free of discrimination as per data protection, equality and human rights laws. However, as laws and regulations do not prescribe how to meet such requirements, businesses are left with having to interpret those themselves, employing a variety of means, including reports, interactive websites, or even dedicated call centres, to provide explanations to their customers. Against this background, provenance, and specifically its standard PROV, describes how a piece of information or data was created and what influenced its production. Within recorded provenance trails, we can retrace automated decisions to provide answers to some questions, such as what data were used to support a decision, who or what organisation was responsible for the data, who else might have been impacted. While provenance information is structurally simple, provenance captured from automated systems, however, tends to be overwhelming for human consumption. In addition, simply making provenance available to a person does not necessarily constitute an explanation. It would need to be summarised and its essence extracted to be able to construct an explanation addressing a specific regulatory purpose. How we do this is unknown today. PLEAD brings together an interdisciplinary team of technologists, legal experts, commercial companies and public organisations to investigate how provenance can help explain the logic that underlies automated decision-making to the benefit of data subjects as well as help data controllers to demonstrate compliance with the law. In particular, we will identify various types of meaningful explanations for algorithmic decisions in relation to their purposes, categorise them against the legal requirements applicable to UK businesses relating to data protection, discrimination and financial services. Building on those, we will conceive explanation-generating algorithms that process, summarise and abstract provenance logged by automated decision-making pipelines. An Explanation Assistant tool will be created for data controllers to provision their applications with provenance-based explanations capabilities. Throughout the project, we will engage with partners, data subjects, data controllers, and regulators via interviews and user studies to ensure the explanations are fit for purpose and meaningful. As a result, explanations that are provenance-driven and legally-grounded will allow data subjects to place their trust in automated decisions, and will allow data controllers to ensure compliance with legal requirements placed on their organisations.

Gaps remain in our understanding of how different combinations of business, technology and relationship strategies influence the growth of small and medium-size enterprises (SMEs), especially in the context of networked interactions by SMEs at regional, extra-regional, and sectoral levels. In each new round of economic and technological development, these strategies evolve, highlighting the importance of tracking in close to real-time the nuances of emerging enterprise strategies. In this project, we will probe differential strategies for SME growth and the role of regional clustering in the growth of innovative companies, building on new and unobtrusive methods of web mining to gain timely information about enterprise developmental pathways. Three key research questions will be addressed: (1) What differentiates the business strategies, technology pathways, and relationships of innovative companies that stay in business and grow? (2) How does regional clustering influence the business strategies, technology pathways, and relationships of innovative companies that stay in business and grow? (3) What are the contributions of policy-induced resources in supporting innovative companies that stay in business and grow? These questions will be probed through a mixed-methods approach using both quantitative and qualitative data. We focus our research on the emerging green goods sector (GGS) - comprising firms producing outputs that benefit the environment or conserve natural resources, with an international comparative element involving the UK, the US, and China. We will identify 300 GGS companies in each country established during the time period 2004-2007, for a total study sample of 900 companies. We will apply a stratified sample selection procedure, to match the distribution of the UK GGS sector by broad product classes with the US and Chinese GGS sectors. We will then combine structured and unstructured data sources to track the origins, business, technology, and relationship strategies, and performance outcomes of these firms through to 2011. Structured data will include corporate databases, corporate patents and publication records. Unstructured data will be derived from new methods of web-scraping and data mining the current and archived web-sites of the sample enterprises. Survival analysis will indicate the pathway of firms from the founding period through to the current period. Hierarchical cluster analysis will be applied to explore differential business strategies by the three countries and by types of metropolitan location and product class. Multivariate regression will relationships between high growth (and other) outcomes and business strategies, technological approach, and the role of regional relationships and policy instruments, controlling for country and other factors. Insights from US and Chinese enterprise growth strategies will be compared with those of UK firms. In the subsequent phase, we will undertake case studies with selected UK enterprises, to test and refine propositions about differential strategies, regional and policy interactions, and outcomes. Interviews (60) will be conducted with high growth firms, stable firms, and other key informants in five UK metropolitan areas. The interviews will examine what differentiates the most successful firms, trace the use and benefit of technology-related and other programmes, and probe for wider policy-related locational attractiveness. The project will be led by the University Manchester in partnership with Experian UK, Georgia Institute of Technology (US), and Beijing Institute of Technology (China). An active dissemination and engagement programme will be pursued with the academic and non-academic worlds, including mechanisms for advanced training and outreach to users in the business sector, including start-up firms and business support programmes, to university and other technology transfer managers, and to local and national policymakers.

We will train a cohort of 65 PhD students to tackle the challenge of Data Creativity for the 21st century digital economy. In partnership with over 40 industry and academic partners, our students will establish the technologies and methods to enable producers and consumers to co-create smarter products in smarter ways and so establish trust in the use of personal data. Data is widely recognised by industry as being the 'fuel' that powers the economy. However, the highly personal nature of much data has raised concerns about privacy and ownership that threaten to undermine consumers' trust. Unlocking the economic potential of personal data while tackling societal concerns demands a new approach that balances the ability to innovate new products with building trust and ensuring compliance with a complex regulatory framework. This requires PhD students with a deep appreciation of the capabilities of emerging technology, the ability to innovate new products, but also an understanding of how this can be done in a responsible way. Our approach to this challenge is one of Data Creativity - enabling people to take control of their data and exercise greater agency by becoming creative consumers who actively co-create more trusted products. Driven by the needs of industry, public sector and third sector partners who have so far committed £1.6M of direct and £2.8M of in kind funding, we will explore multiple sectors including Fast Moving Consumer Goods and Food; Creative Industries; Health and Wellbeing; Personal Finance; and Smart Mobility and how it can unlock synergies between these. Our partners also represent interests in enabling technologies and the cross cutting concerns of privacy and security. Each student will work with industry, public, third sector or international partners to ensure that their research is grounded in real user needs, maximising its impact while also enhancing their future employability. External partners will be involved in PhD co-design, supervision, training, providing resources, hosting placements, setting industry-led challenge projects and steering. Addressing the challenges of Data Creativity demands a multi-disciplinary approach that combines expertise in technology development and human-centred methods with domain expertise across key sectors of the economy. 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. We currently provide access to a network of >80 potential supervisors, ranging from leading Professors to talented early career researchers. This extends to academic partners at other Universities who will be involved in co-hosting and supervising our students, including the Centre for Computing and Social Responsibility at De Montfort University. We run an integrated four-year training programme that features: a bespoke core covering key topics in Future Products, Enabling Technologies, Innovation and Responsibility; optional advanced specialist modules; internship and international exchanges; industry-led challenge projects; training in research methods and professional skills; modules dedicated to the PhD proposal, planning and write up; and many opportunities for cross-cohort collaboration including our annual industry conference, retreat and summer schools. Our Impact Fund supports students in deepening the impact of their research. Horizon has EDI considerations embedded throughout, from consideration of equal opportunities in recruitment to ensuring that we deliver an inclusive environment which supports diversity of needs and backgrounds in the student experience.

Cities are the driver of regional, national and indeed global economies. The complex inter-relationship between urban areas and their hinterlands is a vital aspect of a city's economic success. Hinterlands supply resources such as water, food and energy; while being economically-tied to the urban area through trade. Creating resilient, sustainable, water-secure cities depends on our understanding of the potential future risks of changing hydro-hazards (floods and droughts) and our ability to increase our resilience to them. Worldwide, in 2014, hydro-hazards resulted in over $16Bn (floods) and $7.5Bn (droughts) in damages. While, in the UK over the past five years there have been significant challenges to water management posed by hydro hazards. Since 2000, flooding has caused over £5Bn worth of damage, of which £3Bn was caused by the 2007 floods, and over £1Bn from the 2013/14 winter storms, impacting households and businesses alike. Similarly direct costs (estimated at £70-165M) from the recent UK drought (2011-12) arose from impacts to urban water supplies, and industry. Projections of future climate recognise that there is an added uncertainty in temperature and precipitation trends which may exacerbate the frequency and severity of such hazards. To respond to the stated challenge of transforming our cities to be resilient, sustainable urban centres and in the context of 'adapting to and mitigating climate change', I will quantify uncertainty in future hydro-hazards and design engineering/policy interventions to increase urban resilience which informs future urban water security adaptation for cities and their hinterlands. My fellowship will: 1. quantify future urban hydro-hazard uncertainty in a warming climate using novel techniques, 2. design engineering and policy interventions to mitigate the risk arising from these uncertainties, and 3. improve urban living through enhanced resilience to hydro-hazards. I will achieve this by capturing uncertainty in hydro-hazard events and cascading this through to hazard assessment, challenging the current deterministic paradigm. I will characterise the vulnerability profile of newly exposed populations or sectors, and develop a ground breaking systems approach to ameliorate risk in order to design transformative resilience strategies. The delivery of this vision is challenging yet possible through combining advances in uncertainty quantification from a variety of fields, with my research which has consistently sought to challenge the deterministic paradigm. Awarding this fellowship will create a unique opportunity to improve our understanding of the role of climate projections on the systematic risk to urban living and how such risks can be addressed. Output will include: 1. detailed understanding of the change to hydro hazards across the UK as a result of climate projections (and associated uncertainty), communicated in the context of climate variability, 2. probabilistic frameworks to capture climate uncertainty into assessments of systematic risk posed by changing hydro hazards at the urban scale, 3. analysis of the changing urban vulnerability, the uncertainty associated with this and exploration of the newly exposed population using new, and highly discretised vulnerability metrics, 4. a systems approach to urban resilience to changing hydro hazards, and 5. resilience strategies; e.g. transformative engineering interventions.