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 the day. 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 this departure 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 Principles aim to help judges, legislators, and others make aggregation decisions correctly, and to improve the management of cases in which aggregation is allowed. In addition to formal aggregation in litigated settings, such as with class actions, the work addresses a broader array of cases that are bundled together and settled or tried to test the value of related claims.

These essays in honor of Professor Gerhard Tintner are substantive contributions to three areas of econometrics, (1) economic models and applications,. (2) estimation, and (3) stochastic programming, in each of which he has labored with outstanding success. His own work has extended into multivariate analysis, the pure theory of decision-making under un certainty, and other fields which are not touched upon here for reasons of space and focus. Thus, this collection is appropriate to his interests but covers much less than their full range. Professor Tintner's contributions to econometrics through teaching, writing, editing, lecturing and consulting have been varied and inter national. We have tried to highlight them in "The Econometric Work of Gerhard Tintner" and to place them in historical perspective in "The Invisible Revolution in Economics: Emergence of a Mathematical Science. " Professor Tintner's career to date has spanned the organizational life of the Econometric Society and his contributions have been nearly coextensive with its scope. His principal books and articles up to 1968 are listed in the "Selected Bibliography. " Professor Tintner's current research involves the intricate problems of specification and application of stochastic processes to economic systems, particularly to growth, diffusion of technology, and optimal control. As always, he is moving with the econometric frontier and a portion of the frontier is moving with him. IV Two of the editors wrote dissertations under Professor Tintner's sup- vision; the third knew him as a colleague and friend.

Il libro descrive e affronta alcune questioni tutt’ora aperte nel campo della costruzione di indicatori compositi. Si propone come complemento a riferimenti consolidati quali OECD handbook of composite indicators, e approfondisce temi che saranno certo oggetto di ampio sviluppo nel prossimo futuro, soprattutto nell’ambito degli indicatori di benessere e progresso umano. La prima parte del libro illustra lo stato dell’arte delle metodologie per la costruzione di indicatori compositi mentre la seconda parte affronta specifici nodi critici piu’ recenti. Il libro fornisce strumenti utili sia a ricercatori con una conoscenza limitata degli indicatori compositi, che a studiosi interessati ad un aggiornamento su temi più avanzati.

This book is for developers who want an alternative way to store and process data within their applications. No previous graph database experience is required; however, some basic database knowledge will help you understand the concepts more easily.

These proceedings contain more than 80 of the best papers presented at the INCOM '92 Symposium, and relate to the vast changes which are occurring worldwide in manufacturing technology. Research oriented technical papers cover subjects such as: simulation of manufacturing processes; sensor based robots; information systems; general aspects of CIM and manufacturing networks.

Describes use of observed patterns in understanding and modelling hydrological response, for researchers and graduate students.