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 NameIVAPP 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.