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        Chapter A Network to develop the use of web archives: Three outcomes of the ResPaDon project

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        Author(s)
        Sara Aubry
        Baneyx, Audrey
        Bermes, Emmanuelle
        FAVIER, Laurence
        Alexandre Faye
        Géroudet, Marie-Madeleine
        Ooghe-Tabanou, Benjamin
        Language
        English
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        Abstract
        Web archives represent a huge opportunity for new types of research, offering possibilities for mining and analysis in many scientific disciplines. However, technical, legal, and methodological barriers can prevent researchers from using web archives in their work. The ResPaDon project (Network of partners for the analysis and exploration of digital data) aims to reduce the initial effort required from researchers to get access to web archive collections and understand them. It brings libraries and research teams together to think, experiment, and share practices, in order to analyze the current and potential uses of web archives, to experiment new ways of accessing and exploring corpora, and to issue recommendations about services, roles, skills, and tools.
        URI
        https://library.oapen.org/handle/20.500.12657/96562
        Keywords
        experimentation; services; datasprint; usage
        DOI
        10.36253/979-12-215-0413-2.12
        ISBN
        9791221504132, 9791221504132
        Publisher
        Firenze University Press
        Publisher website
        https://www.fupress.com/
        Publication date and place
        Florence, 2024
        Series
        Proceedings e report, 138
        Classification
        Library, archive and information management
        Bibliographic and subject control
        Archiving, preservation and digitization
        Rights
        https://creativecommons.org/licenses/by/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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