Andreas Metzger – författare

The ebook edition of this title is Open Access and freely available to read online.ENACT is a research project funded by the European Commission under its H2020 program. The project consortium consists of twelve industry and research member organisations spread across the whole EU.The overall goal of the ENACT project was to provide a novel set of solutions to enable DevOps in the realm of trustworthy Smart IoT Systems. Smart IoT Systems (SIS) are complex systems involving not only sensors but also actuators with control loops distributed all across the IoT, Edge and Cloud infrastructure. Since smart IoT systems typically operate in a changing and often unpredictable environment, the ability of these systems to continuously evolve and adapt to their new environment is decisive to ensure and increase their trustworthiness, quality and user experience. DevOps has established itself as a software development life-cycle model that encourages developers to continuously bring new features to the system under operation without sacrificing quality.This book reports on the ENACT work to empower the development and operation as well as the continuous and agile evolution of SIS, which is necessary to adapt the system to changes in its environment, such as newly appearing trustworthiness threats.

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 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 open access book explores cutting-edge solutions and best practices for big data and data-driven AI applications for the data-driven economy. It provides the reader with a basis for understanding how technical issues can be overcome to offer real-world solutions to major industrial areas.The book starts with an introductory chapter that provides an overview of the book by positioning the following chapters in terms of their contributions to technology frameworks which are key elements of the Big Data Value Public-Private Partnership and the upcoming Partnership on AI, Data and Robotics. The remainder of the book is then arranged in two parts. The first part “Technologies and Methods” contains horizontal contributions of technologies and methods that enable data value chains to be applied in any sector. The second part “Processes and Applications” details experience reports and lessons from using big data and data-driven approaches in processes and applications. Its chapters are co-authored with industry experts and cover domains including health, law, finance, retail, manufacturing, mobility, and smart cities. Contributions emanate from the Big Data Value Public-Private Partnership and the Big Data Value Association, which have acted as the European data community's nucleus to bring together businesses with leading researchers to harness the value of data to benefit society, business, science, and industry.The book is of interest to two primary audiences, first, undergraduate and postgraduate students and researchers in various fields, including big data, data science, data engineering, and machine learning and AI. Second, practitioners and industry experts engaged in data-driven systems, software design and deployment projects who are interested in employing these advanced methods to address real-world problems.

This open access book explores cutting-edge solutions and best practices for big data and data-driven AI applications for the data-driven economy. It provides the reader with a basis for understanding how technical issues can be overcome to offer real-world solutions to major industrial areas.The book starts with an introductory chapter that provides an overview of the book by positioning the following chapters in terms of their contributions to technology frameworks which are key elements of the Big Data Value Public-Private Partnership and the upcoming Partnership on AI, Data and Robotics. The remainder of the book is then arranged in two parts. The first part “Technologies and Methods” contains horizontal contributions of technologies and methods that enable data value chains to be applied in any sector. The second part “Processes and Applications” details experience reports and lessons from using big data and data-driven approaches in processes and applications. Its chapters are co-authored with industry experts and cover domains including health, law, finance, retail, manufacturing, mobility, and smart cities. Contributions emanate from the Big Data Value Public-Private Partnership and the Big Data Value Association, which have acted as the European data community's nucleus to bring together businesses with leading researchers to harness the value of data to benefit society, business, science, and industry.The book is of interest to two primary audiences, first, undergraduate and postgraduate students and researchers in various fields, including big data, data science, data engineering, and machine learning and AI. Second, practitioners and industry experts engaged in data-driven systems, software design and deployment projects who are interested in employing these advanced methods to address real-world problems.

This book constitutes the thoroughly refereed proceedings of three international workshops held in Essen, Germany, in conjunction with the 29th International Conference on Advanced Information Systems Engineering, CAiSE 2017, in June 2017.The 11 full papers presented were carefully reviewed and selected from 27 submissions.The workshops were the 4th International Workshop on Advances in Services Design Based on the Notion of Capability (ASDENCA); the 5th International Workshop on Cognitive Aspects of Information Systems Engineering (COGNISE); and the First International Workshop on Teaching for Smart Information Systems – Smart Information Systems for Teaching (T4SIS4T), which took place as a dedicated session under the umbrella of the COGNISE workshop.

This book constitutes the thoroughly refereed proceedings of three international workshops held in Essen, Germany, in conjunction with the 29th International Conference on Advanced Information Systems Engineering, CAiSE 2017, in June 2017.

The 11 full papers presented were carefully reviewed and selected from 27 submissions.

The workshops were the 4th International Workshop on Advances in Services Design Based on the Notion of Capability (ASDENCA); the 5th International Workshop on Cognitive Aspects of Information Systems Engineering (COGNISE); and the First International Workshop on Teaching for Smart Information Systems – Smart Information Systems for Teaching (T4SIS4T), which took place as a dedicated session under the umbrella of the COGNISE workshop.

S-Cube’s Foundations for the Internet of Services Today’s Internet is standing at a crossroads. The Internet has evolved from a source of information to a critical infrastructure which underpins our lives and economies. The demand for more multimedia content, more interconnected devices, more users, a richer user experience, services available any time and anywhere increases the pressure on existing networks and service platforms. The Internet needs a fundamental rearrangement to be ready to meet future needs. One of the areas of research for the Future Internet is the Internet of S- vices, a vision of the Internet where everything (e. g. , information, software, platforms and infrastructures) is available as a service. Services available on the Internet of Services can be used by anyone (if they are used according to the policies de?ned by the provider) and they can be extended with new services by anyone. Advantages of the Internet of Services include the p- sibility to build upon other people’s e?orts and the little investment needed upfront to develop an application. The risk involved in pursuing new business ideas is diminished, and might lead to more innovative ideas being tried out in practice. It will lead to the appearance of new companies that are able to operate in niche areas, providing services to other companies that will be able to focus on their core business.