@inproceedings{ren2017chartaccent,
author = {Ren, Donghao and Brehmer, Matthew and Lee, Bongshin and Hollerer, Tobias and Choe, Eun Kyoung},
title = {ChartAccent: Annotation for Data-Driven Storytelling},
year = {2017},
month = {April},
abstract = {Annotation plays an important role in conveying key points in visual data-driven storytelling; it helps presenters explain and emphasize core messages and specific data. However, the visualization research community has a limited understanding of annotation and its role in data-driven storytelling, and existing charting software provides limited support for creating annotations. In this paper, we characterize a design space of chart annotations, one informed by a survey of 106 annotated charts published by six prominent news graphics desks. Using this design space, we designed and developed ChartAccent, a tool that allows people to quickly and easily augment charts via a palette of annotation interactions that generate manual and data-driven annotations. We also report on a study in which participants reproduced a series of annotated charts using ChartAccent, beginning with unadorned versions of the same charts. Finally, we discuss the lessons learned during the process of designing and evaluating ChartAccent, and suggest directions for future research.},
publisher = {IEEE},
url = {http://approjects.co.za/?big=en-us/research/publication/chartaccent-annotation-data-driven-storytelling/},
}