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    Towards data visualisation based on conceptual modelling

    McBrien, P. and Poulovassilis, Alexandra (2018) Towards data visualisation based on conceptual modelling. In: Trujillo, J.C. and Davis, K.C. and Du, X. and Li, Z. and Ling, T.W. and Li, G. and Lee, M.L. (eds.) Conceptual Modeling: 37th International Conference, ER 2018, Xi'an, China, October 22–25, 2018, Proceedings. Lecture Notes in Computer Science 11157. Springer, pp. 91-99. ISBN 9783030008468.

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    Abstract

    Selecting data, transformations and visual encodings in current data visualisation tools is undertaken at a relatively low level of abstraction - namely, on tables of data - and ignores the conceptual model of the data. Domain experts, who are likely to be familiar with the conceptual model of their data, may find it hard to understand tabular data representations, and hence hard to select appropriate data transformations and visualisations to meet their exploration or question-answering needs. We propose an approach that addresses these problems by defining a set of visualisation schema patterns that each characterise a group of commonly-used data visualisations, and by using knowledge of the conceptual schema of the underlying data source to create mappings between it and the visualisation schema patterns. To our knowledge, this is the first work to propose a conceptual modelling approach to matching data and visualisations.

    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: Alexandra Poulovassilis
    Date Deposited: 05 Jun 2019 12:10
    Last Modified: 17 Oct 2019 04:07
    URI: http://eprints.bbk.ac.uk/id/eprint/22914

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