Authors:
Pierre Vanhulst
1
;
Florian Évéquoz
2
;
Raphaël Tuor
1
and
Denis Lalanne
1
Affiliations:
1
University of Fribourg, Switzerland
;
2
University of Applied Sciences Western Switzerland, Switzerland
Keyword(s):
Data Visualization, Collaboration, User-authored Annotations, Classification.
Related
Ontology
Subjects/Areas/Topics:
Abstract Data Visualization
;
Computer Vision, Visualization and Computer Graphics
;
General Data Visualization
;
Information and Scientific Visualization
;
Visual Analytical Reasoning
;
Visual Data Analysis and Knowledge Discovery
Abstract:
This article introduces a classification system for user-authored annotations in the domain of data visualization. The classification system was created with a bottom-up approach, starting from actual user-authored annotations. To devise relevant dimensions for this classification, we designed a data analysis web platform displaying four visualizations of a common dataset. Using this tool, 16 analysts recorded over 300 annotations that were used to design a classification system. That classification system was then iteratively evaluated and refined until a high inter-coder agreement was found. Use cases for such a classification includes assessing the expressiveness of visualizations on a common ground, based on the types of annotations that are produced with each visualization.