TY  - CONF
ID  - vanhulst_descriptive_2019
T1  - A Descriptive Attribute-{{Based Framework for Annotations in Data Visualization
A1  - Vanhulst, Pierre
A1  - Evéquoz, Florian
A1  - Tuor, Raphaël
A1  - Lalanne, Denis
ED  - Bechmann, Dominique
ED  - Chessa, Manuela
ED  - Cláudio, Ana Paula
ED  - Imai, Francisco
ED  - Kerren, Andreas
ED  - Richard, Paul
ED  - Telea, Alexandru
ED  - Tremeau, Alain
TI  - Computer Vision, Imaging and Computer Graphics Theory and Applications
Y1  - 2019
SP  - 143
EP  - 166
PB  - {Springer International Publishing}
SN  - 978-3-030-26756-8
M2  - doi: 10.1007/978-3-030-26756-8_7
N2  - 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.
ER  -