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    A Conceptual Modelling Approach to Visualising Linked Data

    McBrien, P. and Poulovassilis, Alexandra (2019) A Conceptual Modelling Approach to Visualising Linked Data. In: Panetto, H. and Debruyne, C. and Hepp, M. and Lewis, D. and Agostino Ardagna, C. and Meersman, R. (eds.) Proceedings of On the Move to Meaningful Internet Systems, OTM 2018 Conferences. Lecture Notes in Computer Science 11877. Springer, pp. 227-245. ISBN 9783030332457.

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    Abstract

    Increasing numbers of Linked Open Datasets are being published, and many possible data visualisations may be appropriate for a user's given exploration or analysis task over a dataset. Users may therefore find it difficult to identify visualisations that meet their data exploration or analyses needs. We propose an approach that creates conceptual models of groups of commonly used data visualisations, which can be used to analyse the data and users' queries so as to automatically generate recommendations of possible visualisations. To our knowledge, this is the first work to propose a conceptual modelling approach to recommending visualisations for Linked Data.

    Metadata

    Item Type: Book Section
    Additional Information: The final publication is available at Springer via the link above.
    School: Birkbeck Schools and Departments > School of Business, Economics & Informatics > Computer Science and Information Systems
    Research Centre: Birkbeck Knowledge Lab, Innovation Management Research, Birkbeck Centre for
    Depositing User: Alex Poulovassilis
    Date Deposited: 27 Nov 2019 10:28
    Last Modified: 29 Nov 2019 02:17
    URI: http://eprints.bbk.ac.uk/id/eprint/28782

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