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Two of the most important developments of this new century are the emergence of cloud computing and big data. However, the uncertainties surrounding the failure of cloud service providers to clearly assert ownership rights over data and databases during cloud computing transactions and big data services have been perceived as imposing legal risks and transaction costs. This lack of clear ownership rights is also seen as slowing down the capacity of the Internet market to thrive. Click-through agreements drafted on a take-it-or-leave-it basis govern the current state of the art, and they do not allow much room for negotiation. The novel contribution of this book proffers a new contractual model advocating the extension of the negotiation capabilities of cloud customers, thus enabling an automated and machine-readable framework, orchestrated by a cloud broker. Cloud computing and big data are constantly evolving and transforming into new paradigms where cloud brokers are predicted to play a vital role as innovation intermediaries adding extra value to the entire life cycle. This evolution will alleviate the legal uncertainties in society by means of embedding legal requirements in the user interface and related computer systems or its code. This book situates the theories of law and economics and behavioral law and economics in the context of cloud computing and takes database rights and ownership rights of data as prime examples to represent the problem of collecting, outsourcing, and sharing data and databases on a global scale. It does this by highlighting the legal constraints concerning ownership rights of data and databases and proposes finding a solution outside the boundaries and limitations of the law. By allowing cloud brokers to establish themselves in the market as entities coordinating and actively engaging in the negotiation of service-level agreements (SLAs), individual customers as well as small and medium-sized enterprises could efficiently and effortlessly choose a cloud provider that best suits their needs. This approach, which the author calls “plan-like architectures,” endeavors to create a more trustworthy cloud computing environment and to yield radical new results for the development of the cloud computing and big data markets.
Clouds are being positioned as the next-generation consolidated, centralized, yet federated IT infrastructure for hosting all kinds of IT platforms and for deploying, maintaining, and managing a wider variety of personal, as well as professional applications and services. Handbook of Research on Cloud Infrastructures for Big Data Analytics focuses exclusively on the topic of cloud-sponsored big data analytics for creating flexible and futuristic organizations. This book helps researchers and practitioners, as well as business entrepreneurs, to make informed decisions and consider appropriate action to simplify and streamline the arduous journey towards smarter enterprises.
This edited collection brings together a series of interdisciplinary contributions in the field of Information Technology Law. The topics addressed in this book cover a wide range of theoretical and practical legal issues that have been created by cutting-edge Internet technologies, primarily Big Data, the Internet of Things, and Cloud computing. Consideration is also given to more recent technological breakthroughs that are now used to assist, and — at times — substitute for, human work, such as automation, robots, sensors, and algorithms. The chapters presented in this edition address these issues from the perspective of different legal backgrounds. The first part of the book discusses some of the shortcomings that have prompted legislators to carry out reforms with regard to privacy, data protection, and data security. Notably, some of the complexities and salient points with regard to the new European General Data Protection Regulation (EU GDPR) and the new amendments to the Japan’s Personal Information Protection Act (PIPA) have been scrutinized. The second part looks at the vital role of Internet intermediaries (or brokers) for the proper functioning of the globalized electronic market and innovation technologies in general. The third part examines an electronic approach to evidence with an evaluation of how these technologies affect civil and criminal investigations. The authors also explore issues that have emerged in e-commerce, such as Bitcoin and its blockchain network effects. The book aims to explain, systemize and solve some of the lingering legal questions created by the disruptive technological change that characterizes the early twenty-first century.
Although there are already some books published on Big Data, most of them only cover basic concepts and society impacts and ignore the internal implementation details-making them unsuitable to R&D people. To fill such a need, Big Data: Storage, Sharing, and Security examines Big Data management from an R&D perspective. It covers the 3S desi
After a short description of the key concepts of big data the book explores on the secrecy and security threats posed especially by cloud based data storage. It delivers conceptual frameworks and models along with case studies of recent technology.
Big data analytics is transforming the water sector at the national and international levels. Its potential impact on transboundary water resource governance is being assessed, in the context of selected basins in this book.
The rise of the Data Cloud is ushering in a new era of computing. The world’s digital data is mass migrating to the cloud, where it can be more effectively integrated, managed, and mobilized. The data cloud eliminates data siloes and enables data sharing with business partners, capitalizing on data network effects. It democratizes data analytics, making the most sophisticated data science tools accessible to organizations of all sizes. Data exchanges enable businesses to discover, explore, and easily purchase or sell data—opening up new revenue streams. Business leaders have long dreamed of data driving their organizations. Now, thanks to the Data Cloud, nothing stands in their way.
Data sharing – broadly defined as the exchange of health-related data among multiple controllers and processors – has gained increased relevance in the health sciences over recent years as the need and demand for collaboration has increased. This includes data obtained through healthcare provisions, clinical trials, observational studies, public health surveillance programs, and other data collection methods. The practice of data sharing presents several notable challenges, however. Compliance with a complex and dynamic regulatory framework is essential, with the General Data Protection Regulation being a prominent example in a European context. Recent regulatory developments related to clinical trial transparency, trade secrecy, data access, AI training data, and health data spaces further contribute to the difficulties. Simultaneously, government initiatives often encourage scientists to embrace principles of “open data” and “open innovation.” The variety of regulations in this domain has the potential to impede widespread data sharing and hinder innovation. This edited volume, therefore, compiles comparative case studies authored by leading scholars from diverse disciplines and jurisdictions. The book aims to outline the legal complexities of data sharing. By examining real-world scenarios from diverse disciplines and a global perspective, it explores the normative, policy, and ethical dilemmas that surround data sharing in the health sciences today. Chapter Patient Perspectives on Data Sharing, Chapter Supplementary Measures and Appropriate Safeguards for International Transfers of Health Data after Schrems II are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
Regulators have been more permissive for medical devices compared to their drug and biologic counterparts. While innovative products can thereby reach consumers more quickly, this approach raises serious public health and safety concerns. Additionally, the nature of medical devices is rapidly changing, as software has become as important as hardware. Regulation must keep pace with the current developments and controversies of this technology. This volume provides a multidisciplinary evaluation of the ethical, legal, and regulatory concerns surrounding medical devices in the US and EU. For medical providers, policymakers, and other stakeholders, the book offers a framework for the opportunities and challenges on the horizon for medical device regulation. Readers will gain a nuanced overview of the latest developments in patient privacy and safety, innovation, and new regulatory laws. This book is also available as Open Access on Cambridge Core.
Cloud computing has emerged as a successful paradigm of service-oriented computing and has revolutionized the way computing infrastructure is used. This success has seen a proliferation in the number of applications that are being deployed in various cloud platforms. There has also been an increase in the scale of the data generated as well as consumed by such applications. Scalable database management systems form a critical part of the cloud infrastructure. The attempt to address the challenges posed by the management of big data has led to a plethora of systems. This book aims to clarify some of the important concepts in the design space of scalable data management in cloud computing infrastructures. Some of the questions that this book aims to answer are: the appropriate systems for a specific set of application requirements, the research challenges in data management for the cloud, and what is novel in the cloud for database researchers? We also aim to address one basic question: whether cloud computing poses new challenges in scalable data management or it is just a reincarnation of old problems? We provide a comprehensive background study of state-of-the-art systems for scalable data management and analysis. We also identify important aspects in the design of different systems and the applicability and scope of these systems. A thorough understanding of current solutions and a precise characterization of the design space are essential for clearing the "cloudy skies of data management" and ensuring the success of DBMSs in the cloud, thus emulating the success enjoyed by relational databases in traditional enterprise settings. Table of Contents: Introduction / Distributed Data Management / Cloud Data Management: Early Trends / Transactions on Co-located Data / Transactions on Distributed Data / Multi-tenant Database Systems / Concluding Remarks