Editors:
- Presents the first comprehensive encyclopedic overview of big data
- Pulls together a comprehensive set of multi-disciplinary, cutting edge, and emerging issues
- Encompasses relevant research-based and practice-based topics
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Table of contents (485 entries)
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Front Matter
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A
About this book
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.
Editors and Affiliations
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George Mason University, Fairfax, USA
Laurie A. Schintler, Connie L. McNeely
About the editors
Connie L. McNeely received her Ph.D. from Stanford University in the field of Sociology and is currently Professor in the School of Policy, Government, and International Affairs at George Mason University, where she also serves as Co-Director of the Center for Science and Technology Policy. Dr. McNeely’s teaching and research address various aspects of science, technology, and innovation, organizational behavior, globalization, public policy, law and governance, social theory, and culture. She also is Principal Investigator on major research projects examining national and international scientific networks and policy impacts on diversity in the science and technology workforce, and has received recognition for her work emphasizing complex data analytics, systems mapping, and model construction. Her recent work has included research in the areas of “Big Data” and data science, education, culture and innovation, and health and medical policy, with ongoing projects examining cultural and institutional dynamics and broader matters of inequality and polity participation. Moreover, in addition to new and forthcoming articles in major journals on “Big Data” and the organization of related symposia, she has been an invited speaker and participant in various workshops and conferences on the topic, and has prepared reports for public and private entities on computational scientists and exascale computing activities. She also leads a Research Group on Global Innovation in Science and Technology. Dr. McNeely has numerous publications and is active in several professional associations, serves as a reviewer and evaluator in a variety of programs and venues, and sits on several advisory boards and committees.
Bibliographic Information
Book Title: Encyclopedia of Big Data
Editors: Laurie A. Schintler, Connie L. McNeely
DOI: https://doi.org/10.1007/978-3-319-32010-6
Publisher: Springer Cham
eBook Packages: Business and Management, Reference Module Humanities and Social Sciences, Reference Module Business, Economics and Social Sciences
Copyright Information: Springer Nature Switzerland AG 2022
Hardcover ISBN: 978-3-319-32009-0Published: 23 February 2022
eBook ISBN: 978-3-319-32010-6Published: 11 February 2022
Edition Number: 1
Number of Pages: XXIV, 976
Number of Illustrations: 22 b/w illustrations, 37 illustrations in colour
Topics: Big Data/Analytics, Innovation/Technology Management, Knowledge Management, Database Management, Data Mining and Knowledge Discovery, Statistical Theory and Methods