Linking data about the wide range of goods that are stored in the databases of high street shops offers positive outcomes for consumers, the wellbeing of salesperson as part of the UK's rapidly expanding service sector, health of the high street and the UK economy. Despite the tremendous connections that are made through shopping experiences on the internet, the high street remains locked in a 19th Century paradigm in which the cash register is the only interface between material goods, the customer and the stock inventory (database) (Carrier 1995). Shoppers work hard to make their own connections between disconnected shops, salespeople are reduced to scanning barcodes or fixing self-checkout machines, and data between all parties remains in silos. The vision of a 'frictionless shopping experience' (Brynjofsson and Smith 2000) that part an Internet of Things promise (http://www.youtube.com/watch?v=_xNhL39uD7I), in which technology can reduce the bottleneck of the cash register is far from being realised, instead shoppers have turned to 'showrooming' to make their lives easier (Campbell 2013). This timely project explores the potential for reconfiguring the traditional organisation of customer, salesperson, cash register, tangible things and database, allowing shops 'stacks' of both immaterial and material processes to share data that will improve social and economic conditions. That high streets are in trouble is documented by the Portas Review (2011), which describes the impact that internet shopping, out of town shopping centres and the economic downturn have had upon on these spaces of social, economic and environmental exchange (see Miller 1998). One ramification is decreased employment opportunities for local young people. This year the Grimsey Review (2013) offered a deeper 'digital' critique of the state of the High Street, embracing a Digitally Economic perspective "To strengthen the high street, we need to increase the number of mutual connections between the nodes or network participants (retail, services, local government, job centres and all others). The more mutual connections, the more adaptive the high street network becomes in response to changes in the success of individuals shops and services." (Grimsey 2013:17). Our project builds on research and innovation that NCR Consumer Experience (Cx) have initiated in response to the advent of ubiquitous computing in which every shopper carries a cash register in the form of a smart phone. Equipped with a suite of applications, shoppers are able to make purchases, compare prices, track goods, acquire vouchers and group together with friends or strangers to get better deals, all contributing to the consumers range of tactics to make the most from the high street. This project aims to use this sophisticated user knowledge to inform new models for interaction with physical artefacts and their connected data, to improve the high street experience and recover values and relationships that are core to shopping. The research partnership is completed through the investigators expertise and experience in handling the remaining vital component in the context of the connected high street: things. The extraordinary number of products available in a typical high street at any one time is a material manifestation of the big databases and shop inventories that are connected to each thing. Making visible the scale of the goods in the high street to the shopper, through patterns, correlations and recommendations is a critical step in developing a more connected high street. Through a better understanding of how this data can support the shopper and the salesperson to connect 'things that want to be together', new models of shopping will emerge and reinvigorate the role of things, people and architectures. This Internet of Things project is firmly located within a tenet that the re-thinking of things, data and people might unpack and ameliorate established practices.

The vision of this research is to formalise the geometric foundations of computational statistics and provide the tools and analytic results required to realise the ambition of developing the advanced statistical methodology that is essential to address emerging inference problems of major importance across the sciences and industry. As ever more demanding and ambitious applications of existing statistical inference methods are being considered, the capabilities of computational statistics tools are constantly being stretched, often beyond what is practically feasible. For example the potential to gain insights into the mechanisms of cellular function, elucidating ecological dynamics; improving neurological diagnostics, and uncovering the deep mysteries of the cosmos are only some of the ongoing scientific studies that are heavily reliant on statistical inference methods and are placing unparalleled demand on the current capabilities of available statistical methodology. This situation motivates continual innovation in the development of statistical methods for the quantification of uncertainty. The aim of this proposed research is to be more ambitious and go much further in establishing a novel paradigm that underpins the advancement of next generation computational statistical methods by formalising and developing advanced Monte Carlo methods. The geometric foundations of computational statistics will be formalised within this proposed research in a way that reaches beyond traditional interfaces between statistical and mathematical sciences.

The vision of this research is to formalise the geometric foundations of computational statistics and provide the tools and analytic results required to realise the ambition of developing the advanced statistical methodology that is essential to address emerging inference problems of major importance across the sciences and industry. As ever more demanding and ambitious applications of existing statistical inference methods are being considered, the capabilities of computational statistics tools are constantly being stretched, often beyond what is practically feasible. For example the potential to gain insights into the mechanisms of cellular function, elucidating ecological dynamics; improving neurological diagnostics, and uncovering the deep mysteries of the cosmos are only some of the ongoing scientific studies that are heavily reliant on statistical inference methods and are placing unparalleled demand on the current capabilities of available statistical methodology. This situation motivates continual innovation in the development of statistical methods for the quantification of uncertainty. The aim of this proposed research is to be more ambitious and go much further in establishing a novel paradigm that underpins the advancement of next generation computational statistical methods by formalising and developing advanced Monte Carlo methods. The geometric foundations of computational statistics will be formalised within this proposed research in a way that reaches beyond traditional interfaces between statistical and mathematical sciences.

The vision of this research is to formalise the geometric foundations of computational statistics and provide the tools and analytic results required to realise the ambition of developing the advanced statistical methodology that is essential to address emerging inference problems of major importance across the sciences and industry. As ever more demanding and ambitious applications of existing statistical inference methods are being considered, the capabilities of computational statistics tools are constantly being stretched, often beyond what is practically feasible. For example the potential to gain insights into the mechanisms of cellular function, elucidating ecological dynamics; improving neurological diagnostics, and uncovering the deep mysteries of the cosmos are only some of the ongoing scientific studies that are heavily reliant on statistical inference methods and are placing unparalleled demand on the current capabilities of available statistical methodology. This situation motivates continual innovation in the development of statistical methods for the quantification of uncertainty. The aim of this proposed research is to be more ambitious and go much further in establishing a novel paradigm that underpins the advancement of next generation computational statistical methods by formalising and developing advanced Monte Carlo methods. The geometric foundations of computational statistics will be formalised within this proposed research in a way that reaches beyond traditional interfaces between statistical and mathematical sciences.

Knowledge Exchange Hub Design In Action (KEH DIA) is a national network of organisations (academia and industry,) committed to working in effective collaborations, through the ethos of knowledge exchange to deliver a working model of multi-sector participation that meets the requirements for products, processes and services designed for the demands of tomorrows users. It will build economic capability through design-led innovation to ensure that Scotland can maximise its capacity to operate effectively and meet the imperatives of building new economies for future world markets. The aims of KEH DIA are to: Engage design and mobilise entrepreneurial capacity in five key sectors of food, sport, ICT, rural economies and wellbeing Develop a knowledge exchange model for innovation Develop a collaborative partnership model for Scotland that builds upon existing public support mechanisms Understand opportunities for growth in international markets Develop hard and soft metrics for the creative economy KEH DIA offers a genuine alternative to the existing approach to knowledge exchange, which is project-based and demand-led. It currently occurs in isolation and when the need for it has been identified. The KEH DIA is a unique proactive model of knowledge exchange, harnessing the strategic thinking capabilities of design and designers to work on problem identification through dialogue with multiple stakeholders, in order to envision multiple perspectives / scenarios for emerging issues and single complex problems. The core KE activities undertaken by the strategic partners include 15 'Sandpit' events (which is an extreme model for facilitating innovation) resulting in a minimum of 20 Small Grant Scheme awards to develop prototypes, 10-40 support grants for micro-enterprises to fully engage in the process, an interactive Design Portal, Virtual Incubator and a series of 40 Change Audit Grants. The four Scottish art colleges - Duncan of Jordanstone College of Art & Design, Edinburgh College of Art, Glasgow School of Art, Gray's School of Art, University of Abertay Dundee, University of St Andrews, Creative Scotland, Cultural Enterprise, Scottish Enterprise, DC Thomson, and the V&A at Dundee are the key partners, working in conjunction with an additional 30 companies. These companies, range widely from independents to SMEs to multi-nationals and collectively our partners have pledged £1, 470, 563 in-kind support. They are drawn to the project by the KEH DIA's approach to participatory knowledge exchange with many more keen to engage with the truly collaborative approach that the Hub will take. Developing strong networks between academic institutions and various companies to disseminate the research and working practices that arise as a result of the KEH DIA will be key to strengthening the creative economy and to embedding the innovative approach of design throughout these networks. KEH DIA will adopt a wide-ranging dissemination strategy working in partnership with all of its strategic partners to build understanding of design across Scotland for all audiences. It will also use a variety of visual means to articulate design as strategy for innovation; these will be distributed and exhibited across Scotland in a variety of traditional and non-traditional spaces to build momentum, visibility and an appetite to engage with the people and process that are design. Design is the strategy for effective innovation through partnership and provides a model that places design excellence at the heart of its delivery, building an inclusive culture with design values, which will generate a perceptual change in the image of Scotland as a design driven culture. The legacy is to embed in each region in Scotland an innovation strategy, that demonstrates the transformational effect of design to a range of audiences, enabling insights gained to become an established framework for companies to use strategically as a tool for growth.