Data Democracy
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Data Democracy

At the Nexus of Artificial Intelligence, Software Development, and Knowledge Engineering

1st Edition - January 13, 2020

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  • Authors: Feras Batarseh, Ruixin Yang
  • eBook ISBN: 9780128189399
  • Paperback ISBN: 9780128183663

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Description

Data Democracy: At the Nexus of Artificial Intelligence, Software Development, and Knowledge Engineering provides a manifesto to data democracy. After reading the chapters of this book, you are informed and suitably warned! You are already part of the data republic, and you (and all of us) need to ensure that our data fall in the right hands. Everything you click, buy, swipe, try, sell, drive, or fly is a data point. But who owns the data? At this point, not you! You do not even have access to most of it. The next best empire of our planet is one who owns and controls the world’s best dataset. If you consume or create data, if you are a citizen of the data republic (willingly or grudgingly), and if you are interested in making a decision or finding the truth through data-driven analysis, this book is for you. A group of experts, academics, data science researchers, and industry practitioners gathered to write this manifesto about data democracy.

Key Features

  • The future of the data republic, life within a data democracy, and our digital freedoms
  • An in-depth analysis of open science, open data, open source software, and their future challenges
  • A comprehensive review of data democracy's implications within domains such as: healthcare, space exploration, earth sciences, business, and psychology
  • The democratization of Artificial Intelligence (AI), and data issues such as: Bias, imbalance, context, and knowledge extraction
  • A systematic review of AI methods applied to software engineering problems

Readership

AI, data science, and machine learning researchers; Data scientists and policy makers; Data analysts interested in open data, open science, and open code; Academics and practitioners deploying data for earth sciences, healthcare, government, and psychology; All citizens of the data republic

Table of Contents

  • Section I The data republic
    1. Data democracy for you and me (bias, truth, and context)
    2. Data citizens: rights and responsibilities in a data republic
    3. The history and future prospects of open data and open source software
    4. Mind mapping in artificial intelligence for data democracy
    5. Foundations of data imbalance and solutions for a data democracy

    Section II Implications of a data democracy
    6. Data openness and democratization in healthcare: an evaluation of hospital ranking methods
    7. Knowledge formulation in the health domain: a semiotics-powered approach to data analytics and democratization
    8. Landsat’s past paves the way for data democratization in earth science
    9. Data democracy for psychology: how do people use contextual data to solve problems and why is that important for AI systems?
    10. The application of artificial intelligence in software engineering: a review challenging conventional wisdom

Product details

  • No. of pages: 266
  • Language: English
  • Copyright: © Academic Press 2020
  • Published: January 13, 2020
  • Imprint: Academic Press
  • eBook ISBN: 9780128189399
  • Paperback ISBN: 9780128183663

About the Authors

Feras Batarseh

Feras A. Batarseh is an Associate Professor with the Department of Biological Systems Engineering at Virginia Tech (VT) and the Director of A3 (AI Assurance and Applications) Lab. His research spans the areas of AI Assurance, Cyberbiosecurity, AI for Agriculture and Water, and Data-Driven Public Policy. His work has been published at various prestigious journals and international conferences. Additionally, Dr. Batarseh published multiple chapters and books, his two recent books are: "Federal Data Science", and "Data Democracy", both by Elsevier’s Academic Press. Dr. Batarseh is a senior member of the Institute of Electrical and Electronics Engineers (IEEE), the Agricultural and Applied Economical Association (AAEA), and the Association for the Advancement of Artificial Intelligence (AAAI). He has taught AI and Data Science courses at multiple universities including George Mason University (GMU), University of Maryland - Baltimore County (UMBC), Georgetown University, and George Washington University (GWU). Dr. Batarseh obtained his Ph.D. and M.Sc. in Computer Engineering from the University of Central Florida (UCF) (2007, 2011), a Juris Masters of Law from GMU (2022), and a Graduate Certificate in Project Leadership from Cornell University (2016). He currently holds courtesy appointments with the Center for Advanced Innovation in Agriculture (CAIA), National Security Institute (NSI), and the Department of Electrical and Computer Engineering at VT.

Affiliations and Expertise

Associate Professor, Department of Biological Systems Engineering at Virginia Tech (VT) USA

Ruixin Yang

Ruixin Yang is an Associate Professor in the Department of Geography and GeoInformation Sciences (GGS) — College of Science at George Mason University (GMU), Fairfax, VA. He received his PhD in Aerospace Engineering from University of Southern California (USC) in 1990. His research work ranged from Fluid Dynamics to Astrophysics and General Relativity to Data Science, Information Systems, Data Mining, and Earth Systems Science. Dr. Yang led a software development team that built several prototypes for earth science information systems. His recent research is focused on data mining methods for hurricane-related earth science. He has published several referred papers on earth science data search, online analysis, metadata management, content-based search, and big data analytics.

Affiliations and Expertise

Associate Professor, College of Science, Geography and Geoinformation Services, George Mason University

Ratings and Reviews

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  • Xue L. Tue Jan 21 2020

    Chapter 10!

    Chapter 10 is a must read if you are a programmer...... watch-out! your job is under attack by robots, learn AI or checkout!

  • Amanda I. Mon Jan 13 2020

    the future of data

    this helped me in doing my job as a data analyst - I am still learning how to improve on my data science skills, but it allows me to understand outliers, data ownership, context and other concepts.... love it!

  • John G. Thu Jan 09 2020

    a great reference

    this is a great reference to data science, and the future of data democracy.