Authors: Alexandra Poulovassilis, Peter McBrien
Tags: 2018, conceptual modeling
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.Read the full paper here: https://link.springer.com/chapter/10.1007/978-3-030-00847-5_8
