Designing a classification for user-authored annotations in data visualization

TitleDesigning a classification for user-authored annotations in data visualization
Publication TypeConference Paper
Year of Publication2018
AuthorsVanhulst, P, Evéquoz, F, Tuor, R, Lalanne, D
Conference NameProceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications {(VISIGRAPP} 2018) - Volume 3: IVAPP, Funchal, Madeira, Portugal, January 27-29, 2018.
Date Published02/2018
Conference LocationFunchal, Madeira - Portugal
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 such visualizations.