Laurie A Schintler – författare

Recent technological advancements and other related factors and trends are contributing to the production of an astoundingly large and rapidly accelerating collection of data, or ‘Big Data’. This data now allows us to examine urban and regional phenomena in ways that were previously not possible. Despite the tremendous potential of big data for regional science, its use and application in this context is fraught with issues and challenges. This book brings together leading contributors to present an interdisciplinary, agenda-setting and action-oriented platform for research and practice in the urban and regional community. This book provides a comprehensive, multidisciplinary and cutting-edge perspective on big data for regional science. Chapters contain a collection of research notes contributed by experts from all over the world with a wide array of disciplinary backgrounds. The content is organized along four themes: sources of big data; integration, processing and management of big data; analytics for big data; and, higher level policy and programmatic considerations. As well as concisely and comprehensively synthesising work done to date, the book also considers future challenges and prospects for the use of big data in regional science.Big Data for Regional Science provides a seminal contribution to the field of regional science and will appeal to a broad audience, including those at all levels of academia, industry, and government.

Recent technological advancements and other related factors and trends are contributing to the production of an astoundingly large and rapidly accelerating collection of data, or ‘Big Data’. This data now allows us to examine urban and regional phenomena in ways that were previously not possible. Despite the tremendous potential of big data for regional science, its use and application in this context is fraught with issues and challenges. This book brings together leading contributors to present an interdisciplinary, agenda-setting and action-oriented platform for research and practice in the urban and regional community. This book provides a comprehensive, multidisciplinary and cutting-edge perspective on big data for regional science. Chapters contain a collection of research notes contributed by experts from all over the world with a wide array of disciplinary backgrounds. The content is organized along four themes: sources of big data; integration, processing and management of big data; analytics for big data; and, higher level policy and programmatic considerations. As well as concisely and comprehensively synthesising work done to date, the book also considers future challenges and prospects for the use of big data in regional science.Big Data for Regional Science provides a seminal contribution to the field of regional science and will appeal to a broad audience, including those at all levels of academia, industry, and government.

This ground-breaking Handbook presents a state-of-the-art exploration of entropy, complexity, and spatial dynamics from fundamental theoretical, empirical and methodological perspectives. It considers how foundational theories can contribute to new advances, including novel modeling and empirical insights at different sectoral, spatial, and temporal scales.With the help of leading experts worldwide, the Handbook examines how and to what extent entropic and non-entropic forces and processes in complex spatial socio-economic systems shape and are shaped by their structure and dynamics. Moreover, considering current concerns that big data and related data-driven methods may signal an end to theory, this Handbook is intended to investigate the potential and possibilities for complexity science to engage, revitalize, and advance theory in spatial economics. Overall, this Handbook reaches beyond qualitative generalizations, contributing to the identification of fundamental structural and dynamic properties of the complex space-economy.Drawing upon diverse foundations and perspectives, the Handbook on Entropy, Complexity and Spatial Dynamics: A Rebirth of Theory? will be an essential resource for researchers and students of many fields and disciplines, including economics, urban planning and geography, regional science, information science, physics, and biology.

This encyclopedia will be an essential resource for our times, reflecting the fact that we currently are living in an expanding data-driven world.  Technological advancements and other related trends are contributing to the production of an astoundingly large and exponentially increasing collection of data and information, referred to in popular vernacular as “Big Data.”  Social media and crowdsourcing platforms and various applications ― “apps” ― are producing reams of information from the instantaneous transactions and input of millions and millions of people around the globe. The Internet-of-Things (IoT), which is expected to comprise tens of billions of objects by the end of this decade, is actively sensing real-time intelligence on nearly every aspect of our lives and environment.  The Global Positioning System (GPS) and other location-aware technologies are producing data that is specific down to particular latitude and longitude coordinates and seconds of theday.  Large-scale instruments, such as the Large Hadron Collider (LHC), are collecting massive amounts of data on our planet and even distant corners of the visible universe.  Digitization is being used to convert large collections of documents from print to digital format, giving rise to large archives of unstructured data.  Innovations in technology, in the areas of Cloud and molecular computing, Artificial Intelligence/Machine Learning, and Natural Language Processing (NLP), to name only a few, also are greatly expanding our capacity to store, manage, and process Big Data.  In this context, the Encyclopedia of Big Data is being offered in recognition of a world that is rapidly moving from gigabytes to terabytes to petabytes and beyond.  While indeed large data sets have long been around and in use in a variety of fields, the era of Big Data in which we now live departs from the past in a number of key respects and with thisdeparture comes a fresh set of challenges and opportunities that cut across and affect multiple sectors and disciplines, and the public at large.  With expanded analytical capacities at hand, Big Data is now being used for scientific inquiry and experimentation in nearly every (if not all) disciplines, from the social sciences to the humanities to the natural sciences, and more.  Moreover, the use of Big Data has been well established beyond the Ivory Tower.  In today’s economy, businesses simply cannot be competitive without engaging Big Data in one way or another in support of operations, management, planning, or simply basic hiring decisions.  In all levels of government, Big Data is being used to engage citizens and to guide policy making in pursuit of the interests of the public and society in general.  Moreover, the changing nature of Big Data also raises new issues and concerns related to, for example, privacy, liability, security, access, and even the veracity of the data itself.Given the complex issues attending Big Data, there is a real need for a reference book that covers the subject from a multi-disciplinary, cross-sectoral, comprehensive, and international perspective.  The Encyclopedia of Big Data will address this need and will be the first of such reference books to do so. Featuring some 500 entries, from "Access" to "Zillow," the Encyclopedia will serve as a fundamental resource for researchers and students, for decision makers and leaders, and for business analysts and purveyors.  Developed for those in academia, industry, and government, and others with a general interest in Big Data, the encyclopedia will be aimed especially at those involved in its collection, analysis, and use.  Ultimately, the Encyclopedia of Big Data will provide a common platform and language covering the breadth and depth of the topic for different segments, sectors, and disciplines.

The volume offers new insights into the modelling and analysis of transportation and telecommunications networks, utilizing perspectives from North America, Europe and other areas of the world. It probes interesting questions that can help us to understand the dynamics of our modern networked society: Do properties found in one network fail to exist in other networks and are there geographic factors that can explain this? Are there social, economic or cultural factors that contribute to differences in network properties and dynamics across regions? Can planning models such as those used for traffic forecasting or freight demand modelling be universally applied to networks situated in different regions, and how should this problem be dealt with when a system spans multiple spatial locations? What are the implications for policy analysis and decision-making? These issues are related to the need for a Transatlantic synthesis of current transport methods and their applications. The book attempts to offer a prospectus in this respect, together with the emerging reflections on the desirable future evolution of research.