Anne Dreller shows that data sharing offers great opportunities and huge value creation potential for the business world. Despite many opportunities that data sharing promises, the business world has not fully operationalized this fact yet, due to various existing challenges. Thus, an exemplary, future-oriented, and platform-based data sharing business model is developed for the startup Quemey. This business model is also equipped with prioritized implementation advice, including measures like focusing on strong values for all platform participants, growing their business into a powerful monopolist position, and eliminating barriers of technological, contractual and legal or data privacy uncertainties.

This open access book presents the foundations of the Big Data research and innovation ecosystem and the associated enablers that facilitate delivering value from data for business and society. It provides insights into the key elements for research and innovation, technical architectures, business models, skills, and best practices to support the creation of data-driven solutions and organizations. The book is a compilation of selected high-quality chapters covering best practices, technologies, experiences, and practical recommendations on research and innovation for big data. The contributions are grouped into four parts: · Part I: Ecosystem Elements of Big Data Value focuses on establishing the big data value ecosystem using a holistic approach to make it attractive and valuable to all stakeholders. · Part II: Research and Innovation Elements of Big Data Value details the key technical and capability challenges to be addressed for delivering big data value. · Part III: Business, Policy, and Societal Elements of Big Data Value investigates the need to make more efficient use of big data and understanding that data is an asset that has significant potential for the economy and society. · Part IV: Emerging Elements of Big Data Value explores the critical elements to maximizing the future potential of big data value. Overall, readers are provided with insights which can support them in creating data-driven solutions, organizations, and productive data ecosystems. The material represents the results of a collective effort undertaken by the European data community as part of the Big Data Value Public-Private Partnership (PPP) between the European Commission and the Big Data Value Association (BDVA) to boost data-driven digital transformation.

This report examines the opportunities of enhancing access to and sharing of data (EASD) in the context of the growing importance of artificial intelligence and the Internet of Things. It discusses how EASD can maximise the social and economic value of data re-use and how the related risks and challenges can be addressed. It highlights the trade-offs, complementarities and possible unintended consequences of policy action – and inaction. It also provides examples of EASD approaches and policy initiatives in OECD countries and partner economies.

Digital technologies have enabled certain opportunities for industries, societies, and companies to change for the better. The service sector has essentially evolved through significant developments in recent decades, such as the increasing adoption of artificial intelligence (AI) applications and automated technologies, including service robots, chatbots, and virtual assistants. Both digital transformation and digital entrepreneurship are multifaceted areas that relate to varied emerging technologies that have recently dominated the current service industry. These technologies serve to enhance various sociotechnical areas, including communication and collaboration, as well as co-creating business value and promoting service automation. Digital Entrepreneurship and Co-Creating Value Through Digital Encounters contributes to the services’ digital transformation and digital entrepreneurship domain by uncovering contemporary innovations used in the modern service industry. It supports modern applications of Industry 4.0, digital transformation, and entrepreneurship to facilitate value co-creation for contemporary businesses. Covering topics such as big data management, industrial relations, and tourist destination selection, this premier reference source is an ideal resource for entrepreneurs, business owners and managers, government officials, policymakers, students and educators of higher education, librarians, researchers, and academicians.

Data sharing can accelerate new discoveries by avoiding duplicative trials, stimulating new ideas for research, and enabling the maximal scientific knowledge and benefits to be gained from the efforts of clinical trial participants and investigators. At the same time, sharing clinical trial data presents risks, burdens, and challenges. These include the need to protect the privacy and honor the consent of clinical trial participants; safeguard the legitimate economic interests of sponsors; and guard against invalid secondary analyses, which could undermine trust in clinical trials or otherwise harm public health. Sharing Clinical Trial Data presents activities and strategies for the responsible sharing of clinical trial data. With the goal of increasing scientific knowledge to lead to better therapies for patients, this book identifies guiding principles and makes recommendations to maximize the benefits and minimize risks. This report offers guidance on the types of clinical trial data available at different points in the process, the points in the process at which each type of data should be shared, methods for sharing data, what groups should have access to data, and future knowledge and infrastructure needs. Responsible sharing of clinical trial data will allow other investigators to replicate published findings and carry out additional analyses, strengthen the evidence base for regulatory and clinical decisions, and increase the scientific knowledge gained from investments by the funders of clinical trials. The recommendations of Sharing Clinical Trial Data will be useful both now and well into the future as improved sharing of data leads to a stronger evidence base for treatment. This book will be of interest to stakeholders across the spectrum of research-from funders, to researchers, to journals, to physicians, and ultimately, to patients.

We live in a time of exciting possibilities. The business world is being transformed as digital technologies shift the basis of competition from machine-intensity to human-intensity. The foundations of success in today's fast-moving global economy are the creative capacities of people, competitive advantage is now based on insight, imagination and innovation. But meeting the challenges of value-creation in this digital era requires a revolution in thought, outlook and practice. New models of business are needed to provide fresh perspectives on creating and sustaining value in an economy founded on human talent. This practical guide explains how to revolutionise your management strategies, create value for your customers and grasp the new opportunities offered by the digital era.

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.