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        Data Visualization in Society

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        Author(s)
        Engebretsen, Martin
        Kennedy, Helen
        Language
        English
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        Abstract
        Today we are witnessing an increased use of data visualization in society. Across domains such as work, education and the news, various forms of graphs, charts and maps are used to explain, convince and tell stories. In an era in which more and more data are produced and circulated digitally, and digital tools make visualization production increasingly accessible, it is important to study the conditions under which such visual texts are generated, disseminated and thought to be of societal benefit. This book is a contribution to the multi-disciplined and multi-faceted conversation concerning the forms, uses and roles of data visualization in society. Do data visualizations do 'good' or 'bad'? Do they promote understanding and engagement, or do they do ideological work, privileging certain views of the world over others? The contributions in the book engage with these core questions from a range of disciplinary perspectives.
        URI
        http://library.oapen.org/handle/20.500.12657/22273
        Keywords
        Media studies; information; visualization; data analysis
        DOI
        10.5117/9789463722902
        ISBN
        9789463722902
        Publisher
        Amsterdam University Press
        Publisher website
        https://www.aup.nl/
        Publication date and place
        Amsterdam, 2020
        Grantor
        • The Research Council of Norway - 25936
        Imprint
        Amsterdam University Press
        Classification
        Data science and analysis: general
        Media studies
        Information visualization
        Pages
        441
        Rights
        http://creativecommons.org/licenses/by-nc-nd/4.0/
        • Imported or submitted locally

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        License

        • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

        Credits

        • logo EU
        • This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 683680, 810640, 871069 and 964352.

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