A Conceptual Modelling Approach to Visualising Linked Data

被引:0
|
作者
McBrien, Peter [1 ]
Poulovassilis, Alexandra [2 ]
机构
[1] Imperial Coll, Dept Comp, 180 Queens Gate, London SW7 2BZ, England
[2] Birkbeck Univ London, Birkbeck Knowledge Lab, Malet St, London WC1E 7HX, England
来源
ON THE MOVE TO MEANINGFUL INTERNET SYSTEMS: OTM 2019 CONFERENCES | 2019年 / 11877卷
关键词
SYSTEM;
D O I
10.1007/978-3-030-33246-4_15
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:227 / 245
页数:19
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