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Encyclopedia of Big Data


Encyclopedia of Big Data Laurie Schintler, Connie McNeely

This encyclopedia will be an indispensable resource for our time as it reflects the fact that we are currently living in an expanding data-driven world.

Advances in technology and other related trends are contributing to the production of an incredibly large and exponentially growing collection of data and information popularly known as "Big Data". Social media and crowdsourcing platforms and various apps - "apps" generate tons of information from instant transactions and inputs from millions and millions of people around the world. The Internet of Things (IoT), which is set to comprise tens of billions of objects by the end of this decade, is actively detecting real-time information about almost every aspect of our lives and our environment.

The Global Positioning System (GPS) and other positioning technologies generate data that is specific to certain latitude and longitude coordinates and seconds of the day. Large instruments like the Large Hadron Collider (LHC) collect huge amounts of data on our planet and even in remote corners of the visible universe. Digitization is used to convert large collections of documents from printed to digital, resulting in large archives of unstructured data. Technological innovations in the areas of cloud and molecular computing, artificial intelligence / machine learning and natural language processing (NLP), to name just a few, also greatly increase our ability to store, manage and process big data. In this context, the Big Data Encyclopedia is being offered in recognition of a world that is rapidly moving from gigabyte to terabyte to petabyte and beyond.

While large data sets have been around for a long time and are used in a wide variety of areas, the era of big data that we now live in is moving away from the past in some important ways and with this awakening comes a new set of opportunities to that span and affect multiple sectors and disciplines as well as the general public. With extensive analytical capabilities, big data is used today in almost all disciplines (if not all) for scientific research and experiments, from the social sciences to the humanities to the natural sciences and more.

In addition, the use of big data is established beyond the ivory tower. In today's economy, companies simply cannot compete without involving big data in one way or another to aid operation, management, planning, or just basic hiring decisions. Big data is used at all levels of government to engage citizens and guide policymaking in the interests of the public and society at large. In addition, the changing nature of big data also raises new questions and concerns about privacy, accountability, security, access, and even the veracity of the data itself.

Given the complexity of big data topics, there is an urgent need for a reference work that covers the topic from a multidisciplinary, intersectoral, global and international perspective. The Big Data Encyclopedia addresses this need and will be the first of these reference books to do so. With around 500 entries from "Access" to "Zillow", the encyclopedia will serve as a fundamental resource for researchers and students, for policy makers and executives, as well as for business analysts and suppliers. The encyclopedia is designed for academics, industry and government, and others with a general interest in big data, and is specifically aimed at those involved in its collection, analysis, and use. Ultimately, the Big Data Encyclopedia will provide a common platform and language that covers the breadth and depth of the topic for different segments, sectors and disciplines.

Encyclopedia of Big Data author: Laurie A. Schintler

Laurie A. Schintler is Associate Professor in the School of Policy, Government, and International Affairs at George Mason University. Dr. Schintler received his PhD in Urban and Regional Planning from the University of Illinois at Champaign-Urbana and is a well-known computational sociologist and expert in big data, network analysis, geoanalysis, science and technology, health and medicine. , transport and regional science. . Dr. Schintler has over 70 peer-reviewed articles, book chapters and technical reports, as well as a co-edited book titled New Advances in Transportation and Telecommunications Modeling: Cross-Atlantic Perspectives (2005) and numerous blog posts. , guest presentations and media appearances. She is also the holder of the patent "System and method of analysis of the structure of logical networks" (USPTO: 20100306372, July 2010; S. Gorman, R. Kulkarni, L. Schintler and R. Stough). Dr. Schintler has been a Principal Investigator or Co-Principal Investigator on a number of grants from various sponsors, including the United States Department of Transportation, the National Institutes of Health, the Department of Homeland Security, and the National Park Service.

She is currently Associate Director of the Center for Study of International Medical Practices and Policies and Director of the Masters Program in Transportation, Policy, Operations and Logistics at George Mason University. She teaches advanced analytical methods and big data. Laurie Schintler is also a co-founder of Fortiusone (Geoiq), a geospatial intelligence company (acquired by ESRI, Inc.).

Encyclopedia of Big Data author: Connie L. McNeely

Connie L. McNeely received her doctorate. from Stanford University in Sociology and is currently a Professor in the School of Policy, Government, and International Affairs at George Mason University, where she is also Co-Director of the Center for Science and Technology Policy. Dr. McNeely's teaching and research covers various aspects of science, technology and innovation, organizational behavior, globalization, public order, law and governance, theory social and cultural. She is also a principal investigator on major research projects examining national and international scientific networks and the policy implications for diversity in science and technology, and has been recognized for her work focused on complex data analysis, systems mapping and model building. His most recent work has included research in big data and data science, education, culture and innovation, and medical and health policy.

In addition to new and upcoming articles in major journals on the topic of Big Data and the organization of corresponding symposia, she has been a guest speaker and participant in various workshops and conferences on this topic and has prepared reports for public and private institutions on computer scientists and exascale computing activities. She also heads a research group on global innovation in science and technology. Dr. McNeely has published extensively and is active in several professional associations, acts as a reviewer and examiner in a variety of programs and institutions, and sits on several boards and advisory committees.

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