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A Descriptive Attribute-{{Based Framework for Annotations in Data Visualization
Publicatietype: In proceedings
Citatie: vanhulst_descriptive_2019
Boektitel: Computer Vision, Imaging and Computer Graphics Theory and Applications
Jaar: 2019
Pagina's: 143-166
Uitgever: {Springer International Publishing}
ISBN: 978-3-030-26756-8
DOI: 10.1007/978-3-030-26756-8_7
Samenvatting: Annotations are observations made during the exploration of a specific data visualization, which can be recorded as text or visual data selection. This article introduces a classification framework that allows a systematic description of annotations. To create the framework, a real dataset of 302 annotations authored by 16 analysts was collected. Then, three coders independently described the annotations by eliciting categories that emerged from the data. This process was repeated for several iterative phases, until a high inter-coder agreement was reached. The final descriptive attribute-based framework comprises the following dimensions: insight on data, multiple observations, data units, level of interpretation, co-references and detected patterns. This framework has the potential to provide a common ground to assess the expressiveness of different types of visualization over the same data. This potential is further illustrated in a concrete use case.
Trefwoorden:
Auteurs Vanhulst, Pierre
Evéquoz, Florian
Tuor, Raphaël
Lalanne, Denis
Redacteurs Bechmann, Dominique
Chessa, Manuela
Cláudio, Ana Paula
Imai, Francisco
Kerren, Andreas
Richard, Paul
Telea, Alexandru
Tremeau, Alain
Toegevoegd door: []
Totaalscore: 0
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