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    Data Democracy

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

    AvFeras A. Batarseh,Ruixin Yang

    Häftad, Engelska, 2020

    1 521 kr

    Beställningsvara. Skickas inom 10-15 vardagar. Fri frakt över 249 kr.

    Beskrivning

    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.



    • 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

    Produktinformation

    • Utgivningsdatum:2020-01-13
    • Mått:191 x 235 x 14 mm
    • Vikt:540 g
    • Format:Häftad
    • Språk:Engelska
    • Antal sidor:266
    • Förlag:Elsevier Science
    • ISBN:9780128183663

    Utforska kategorier

    • Biokemisk teknik inom Naturvetenskap och teknik
    • Biomedicinsk teknik inom Medicin

    Mer om författaren

    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. 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.

    Recensioner i media

    "Not sure what data democracy is? But your interest is piqued because it has sounds “data” in the title? Well, you should be interested and you’ll understand the term well if you give Data Democracy a thorough read.The author claims the book to be a manifesto for data democracy, and it succeeds in that challenge. Everybody is part of the “data republic” and therefore needs to be aware of their data… who has access to it, how they got access to it, how it is being used, how it is protected, and more. In short, data democracy is the concept of sharing data instead of letting it be monopolized by a few large concerns. Of course, it is not quite that simple, so a book is needed… this book. If you consume or create data – and at this point who does not – you will benefit by reading Data Democracy." --Data and Technology Today

    Innehållsförteckning

    • Section I The data republic1. Data democracy for you and me (bias, truth, and context)2. Data citizens: rights and responsibilities in a data republic3. The history and future prospects of open data and open source software4. Mind mapping in artificial intelligence for data democracy5. Foundations of data imbalance and solutions for a data democracySection II Implications of a data democracy6. Data openness and democratization in healthcare: an evaluation of hospital ranking methods7. Knowledge formulation in the health domain: a semiotics-powered approach to data analytics and democratization8. Landsat’s past paves the way for data democratization in earth science9. 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
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