This White Paper sets out clearly how the UK will continue to unlock and seize the benefits of data sharing in the future in a responsible way. Firstly by ensuring equality in access to data; secondly in building greater trust in public data; and thirdly by ensuring that public services are more personalised and efficient by being smarter with the data public bodies hold. The UK is currently co-chairing the Open Government Partnership of 55 governments whose theme is 'Transparency drives prosperity' with the belief that opening up data will empower citizens, foster innovation and reform public services. It is also, therefore, about how others participate. About businesses and organisations becoming more transparent themselves and pushing data into the public domain and individuals taking that data and using it to make better decisions or press for different types of services.

In this book readers will find technological discussions on the existing and emerging technologies across the different stages of the big data value chain. They will learn about legal aspects of big data, the social impact, and about education needs and requirements. And they will discover the business perspective and how big data technology can be exploited to deliver value within different sectors of the economy. The book is structured in four parts: Part I “The Big Data Opportunity” explores the value potential of big data with a particular focus on the European context. It also describes the legal, business and social dimensions that need to be addressed, and briefly introduces the European Commission’s BIG project. Part II “The Big Data Value Chain” details the complete big data lifecycle from a technical point of view, ranging from data acquisition, analysis, curation and storage, to data usage and exploitation. Next, Part III “Usage and Exploitation of Big Data” illustrates the value creation possibilities of big data applications in various sectors, including industry, healthcare, finance, energy, media and public services. Finally, Part IV “A Roadmap for Big Data Research” identifies and prioritizes the cross-sectorial requirements for big data research, and outlines the most urgent and challenging technological, economic, political and societal issues for big data in Europe. This compendium summarizes more than two years of work performed by a leading group of major European research centers and industries in the context of the BIG project. It brings together research findings, forecasts and estimates related to this challenging technological context that is becoming the major axis of the new digitally transformed business environment.

Public Policy Analytics: Code & Context for Data Science in Government teaches readers how to address complex public policy problems with data and analytics using reproducible methods in R. Each of the eight chapters provides a detailed case study, showing readers: how to develop exploratory indicators; understand ‘spatial process’ and develop spatial analytics; how to develop ‘useful’ predictive analytics; how to convey these outputs to non-technical decision-makers through the medium of data visualization; and why, ultimately, data science and ‘Planning’ are one and the same. A graduate-level introduction to data science, this book will appeal to researchers and data scientists at the intersection of data analytics and public policy, as well as readers who wish to understand how algorithms will affect the future of government.

This book examines the recent evolution of the concept of data as an economic and managerial phenomenon. The author first describes and discusses open data and then introduces the concept of linked data, with a focus on assets for reuse. Furthermore, he addresses the main challenges of big data. Value is identified as the main incentive for the adoption of linked data; accordingly, the next two chapters study sources of data value from a macroeconomic and micro economic perspective, respectively. This contributes to the systematization of important issues at the crossroads of enterprise data and data sharing: data ownership, personal data, and data privacy. In turn, the book reveals the role of innovation as a main vehicle for creating value by unifying big, open, and linked data. It studies the ways in which value can be created, transferred, and captured in the form of business models, before the closing chapter verifies the data unification model by combining open and linked geographical data with big data from a major telecom company.

Recent years have witnessed considerable speculation about the potential of open data to bring about wide-scale transformation. The bulk of existing evidence about the impact of open data, however, focuses on high-income countries. Much less is known about open data’s role and value in low- and middle-income countries, and more generally about its possible contributions to economic and social development. Open Data for Developing Economies features in-depth case studies on how open data is having an impact across the developing world-from an agriculture initiative in Colombia to data-driven healthcare projects in Uganda and South Africa to crisis response in Nepal. The analysis built on these case studies aims to create actionable intelligence regarding: (a) the conditions under which open data is most (and least) effective in development, presented in the form of a Periodic Table of Open Data; (b) strategies to maximize the positive contributions of open data to development; and (c) the means for limiting open data’s harms on developing countries.

The main objectives of this book are to expose key aspects that have a relevance when dealing with open data viewed from different perspectives and to provide appealing examples of how open data is implemented worldwide. The concept of open data as we know it today is the result of many different initiatives, both of a legislative and non-legislative nature, and promoted by a wide range of actors. Numerous regulatory antecedents to foster the concept of open data and embed it in national and international policy agendas have been undertaken on both sides of the Atlantic, as well as at a supranational level. The book highlights a number of the efforts made to promote open data in Europe, Asia and the United States. In addition to new insights, practical guidance and multiple disciplinary perspectives on open data, the book also addresses the transformation of current developments towards open data, which may be referred to as the democratisation of data. This book will support open data practitioners as well as open data scholars in their endeavours to promote open data implementation and research. Bastiaan van Loenen is associate professor and director of the Knowledge Centre Open Data at the Faculty of Architecture and The Built Environment of Delft University of Technology in the Netherlands, as is Glenn Vancauwenberghe, who is a post-doctoral researcher, and Joep Crompvoets is a professor at the Public Governance Institute of the KU Leuven in Belgium.

This book constitutes the proceedings of the 20th International Conference on Conceptual Structures, ICCS 2013, held in Mumbai, India, in January 2013. The 22 full papers presented were carefully reviewed and selected from 43 submissions for inclusion in the book. The volume also contains 3 invited talks. ICCS focuses on the useful representation and analysis of conceptual knowledge with research and business applications. It advances the theory and practice in connecting the user's conceptual approach to problem solving with the formal structures that computer applications need to bring their productivity to bear. Conceptual structures (CS) represent a family of approaches that builds on the successes of artificial intelligence, business intelligence, computational linguistics, conceptual modeling, information and Web technologies, user modeling, and knowledge management.