"Big data," as it has become known in business and information technology circles, has the potential to improve our knowledge about human behavior, and to help us gain insight into the ways in which we organize ourselves, our cultures, and our external and internal lives. Libraries stand at the center of the information world, both facilitating and contributing to this flood as well as helping to shape and channel it to specific purposes. But all technologies come with a price. Where the tool can serve a purpose, it can also change the user's behavior to fit the purposes of the tool. Big Data Shocks: An Introduction to Big Data for Librarians and Information Professionals examines the roots of big data, the current climate and rising stars in this world. The book explores the issues raised by big data and discusses theoretical as well as practical approaches to managing information whose scope exists beyond the human scale. What’s at stake ultimately is the privacy of the people who support and use our libraries and the temptation for us to examine their behaviors. Such tension lies deep in the heart of our great library institutions. This book addresses these issues and many of the questions that arise from them, including: What is our role as librarians within this new era of big data? What are the impacts of new powerful technologies that track and analyze our behavior? Do data aggregators know more about us and our patrons than we do? How can librarians ethically balance the need to demonstrate learning and knowledge creation and privacy? Do we become less private merely because we use a tool or is it because the tool has changed us? What's in store for us with the internet of things combining with data mining techniques? All of these questions and more are explored in this book

Intelligence and security communities have access to an overwhelming amount of information. More data is better in an information-hungry world, but too much data paralyzes individual and institutional abilities to process and use information effectively. Robert Mandel calls this phenomenon "global data shock." He investigates how information overload affects strategic ambiguity, deception, and surprise, as well as the larger consequences for international security. This book provides not only an accessible framework for understanding global data shock and its consequences, but also a strategy to prepare for and respond to information overload. Global Data Shock explores how information overload facilitates deception, eroding international trust and cooperation in the post-Cold War era. A sweeping array of case studies illustrates the role of data shock in shaping global events from the 1990 Iraqi attack on Kuwait to Brexit. When strategists try to use an overabundance of data to their advantage, Mandel reveals, it often results in unanticipated and undesirable consequences. Too much information can lead to foreign intelligence failures, security policy incoherence, mass public frustrations, curtailment of democratic freedoms, and even international political anarchy. Global Data Shock addresses the pressing need for improved management of information and its strategic deployment.

Big Data is playing a vital role in HCI projects across a range of industries: healthcare, cybersecurity, forensics, education, business organizations, and scientific research. Big data analytics requires advanced tools and techniques to store, process and analyze the huge volume of data. Working on HCI projects requires specific skill sets to implement IT solutions. Big Data Analytics for Human-Computer Interactions: A New Era of Computation is a comprehensive guide that discusses the evolution of Big Data in Human Computer Interaction from promise to reality. This book provides an introduction to Big Data and HCI, followed by an overview of the state-of-the-art algorithms for processing big data, Subsequent chapters also explain the characteristics, applications, opportunities and challenges of big data systems, by describing theoretical, practical, and simulation concepts of computational intelligence and big data analytics used in designing HIC systems. The book also presents solutions for analyzing complex patterns in user data and improving productivity. Readers will be able to understand the technology that drives big data solutions in HCI projects and understand its capacity in transforming an organization. The book also helps the reader to understand HCI system design and explains how to evaluate an application portfolio that can be used when selecting pilot projects. This book is a resource for researchers, students, and professionals interested in the fields of HCI, artificial intelligence, data analytics, and computer engineering.

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.

This proceedings volume contains selected papers from the Fourth International Conference on Big Data Applications and Services (BigDAS 2017), held in Tashkent, Uzbekistan on August 15-18, 2017. Big data has become a core technology providing innovative solutions in many fields including social media, healthcare and manufacturing. The Fourth International Conference on Big Data Applications and Services (BigDAS 2017) presented innovative results, encouraged academic and industrial interaction, and promoted collaborative research in the field of big data worldwide. The conference was organized by the Korea Big Data Services Society and National University of Uzbekistan.

This book focuses mainly on the usages of three key technologies: IoT, big data, and AI for various day to day applications. Further, it explores the possibilities of future research based on the usages of latest information systems. This book explores the current research and challenges to be faced by different researchers for building intelligent information solutions using key technologies; IoT, big data, and AI in improving quality of lives in smart cities and explores the limitations and capabilities of these three key computing technologies. The book is organized into three major parts; each part includes chapters exploring a specific topic, and there are: PART-1: IoT for Real World Solutions , (ii) Part-2: Big Data And Cloud Computing for Innovative Solutions For Day to Day Lives, and (iii) Part-3 Artificial Intelligence for Everyday Lives. This book may be useful to the scientists, scholars, and researchers who are working in the field of computer science and engineering, and communication engineering, along with the students in these subjects who are working or willing to work on IoT, big data, and AI technologies for improving quality of everyday life. Specialists as well as student readers find the book chapters encouraging and helpful. IoT, data science & cloud, and AI all are the undergraduate (UG/ bachelor) subjects. Use of these three key technologies for building new applications for better world is helpful for UG and postgraduate (PG/ MS) Programmes students (as an elective and core course). This book may also be very useful for the Ph.D. (research scholars) during their course work and may be used as an instrument to identify the different challenges associated with information systems.

There has been a multitude of studies focused on the COVID-19 pandemic across fields and disciplines as all sectors of life have had to adjust the way things are done and adapt to the constantly shifting environment. These studies are crucial as they provide support and perspectives on how things are changing and what needs to be done to stay afloat. Connecting COVID-19-related studies and big data analytics is crucial for the advancement of industrial applications and research areas. Applied Big Data Analytics and Its Role in COVID-19 Research introduces the most recent industrial applications and research topics on COVID-19 with big data analytics. Featuring coverage on a broad range of big data technologies such as data gathering, artificial intelligence, smart diagnostics, and mining mobility, this publication provides concrete examples and cases of usage of data-driven projects in COVID-19 research. This reference work is a vital resource for data scientists, technical managers, researchers, scholars, practitioners, academicians, instructors, and students.