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As software R&D investment increases, the benefits from short feedback cycles using technologies such as continuous deployment, experimentation-based development, and multidisciplinary teams require a fundamentally different strategy and process. This book will cover the three overall challenges that companies are grappling with: speed, data and ecosystems. Speed deals with shortening the cycle time in R&D. Data deals with increasing the use of and benefit from the massive amounts of data that companies collect. Ecosystems address the transition of companies from being internally focused to being ecosystem oriented by analyzing what the company is uniquely good at and where it adds value.
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.
The Tenth International Conference on Ecosystems and Sustainable Development is the latest in a well established series that originated from the work of the late Nobel laureate, Ilya Prigogine, who challenged us to develop the science of "ecodynamics," integrating thermodynamics, ecology and economics. The papers presented at the conference, contained in this book, cover not only new research from all over the world related to ecological problems, but also new ideas and emerging concepts resulting from interdisciplinary efforts of scientists, engineers and economists. The included papers cover such topics as: Energy and the Environment; Environmental Indicators; Sustainable Development and Planning; Ecosystem Modelling; Natural Resources Management; Sustainable Development Studies; Waste Management; Soil Contamination and Recovery; Recovery of Damaged Areas; Protection and Mitigation; Sustainable Energy Systems; Economic and Benefit Analysis; Policies; Environmental Management; Climate Change and Adaptation; Forensic Analysis; Knowledge Dissemination; Social Responsibility; Environmental Monitoring and Assessment; Innovation in Environmental Management; Sustainable Indicators, Monitoring and Assessment; Natural Resources in Periurban Spaces; Territorial Risk Management.
With the rise of information and communication technologies in today’s world, many regions have begun to adapt into more resource-efficient communities. Integrating technology into a region’s use of resources, also known as smart territories, is becoming a trending topic of research. Understanding the relationship between these innovative techniques and how they impact social innovation is vital when analyzing the sustainable growth of highly populated regions. The Handbook of Research on Smart Territories and Entrepreneurial Ecosystems for Social Innovation and Sustainable Growth is a pivotal reference source that provides vital research on the global practices and initiatives of smart territories as well as their impact on sustainable development in different communities. While highlighting topics such as waste management, social innovation, and digital optimization, this publication is ideally designed for civil engineers, urban planners, policymakers, economists, administrators, social scientists, business executives, researchers, educators, and students seeking current research on the development of smart territories and entrepreneurship in various environments.
Using data to build better products is a short, easy to read and illustrated introduction to working with data in product development. It provides a detailed, hands-on and story-driven approach to working with data in product development. It describes the typical steps that companies go through as they build their capability, starting from understanding product use to experimenting with features to, finally, value modeling of features and tracking the delivery of this feature during iterative development. We hope you enjoy reading this short book and manage to apply these principles in your R&D organization and day to day work.
This open access book is part of the LAMBDA Project (Learning, Applying, Multiplying Big Data Analytics), funded by the European Union, GA No. 809965. Data Analytics involves applying algorithmic processes to derive insights. Nowadays it is used in many industries to allow organizations and companies to make better decisions as well as to verify or disprove existing theories or models. The term data analytics is often used interchangeably with intelligence, statistics, reasoning, data mining, knowledge discovery, and others. The goal of this book is to introduce some of the definitions, methods, tools, frameworks, and solutions for big data processing, starting from the process of information extraction and knowledge representation, via knowledge processing and analytics to visualization, sense-making, and practical applications. Each chapter in this book addresses some pertinent aspect of the data processing chain, with a specific focus on understanding Enterprise Knowledge Graphs, Semantic Big Data Architectures, and Smart Data Analytics solutions. This book is addressed to graduate students from technical disciplines, to professional audiences following continuous education short courses, and to researchers from diverse areas following self-study courses. Basic skills in computer science, mathematics, and statistics are required.
The research presented here provides a sound scientific basis for management and policy decisions regarding the productivity and sustainability of forest ecosystems in the context of a rapidly changing global environment. It is the synthesis of 5 years of field and laboratory research on southern forests conducted by the US Department of Agriculture Forest Service to provide scientific assessments to the US Global Change Research Program, and, as such, is invaluable for policy makers and land use managers.