Critical Reflections on Visualization Authoring Systems
Name
1907.13568.pdf
Description
Accepted version
Size
3.91 MB
Format
Adobe PDF
Checksum (MD5)
094a410656cd897bbfac46c03ea942d4
Author(s)
Satyanarayan, Arvind
Lee, Bongshin
Ren, Donghao
Heer, Jeffrey
Stasko, John
Thompson, John
Brehmer, Matthew
Liu, Zhicheng
Date Issued
2019
Journal
IEEE Transactions on Visualization and Computer Graphics
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Version
Author's final manuscript
Abstract
© 1995-2012 IEEE. An emerging generation of visualization authoring systems support expressive information visualization without textual programming. As they vary in their visualization models, system architectures, and user interfaces, it is challenging to directly compare these systems using traditional evaluative methods. Recognizing the value of contextualizing our decisions in the broader design space, we present critical reflections on three systems we developed-Lyra, Data Illustrator, and Charticulator. This paper surfaces knowledge that would have been daunting within the constituent papers of these three systems. We compare and contrast their (previously unmentioned) limitations and trade-offs between expressivity and learnability. We also reflect on common assumptions that we made during the development of our systems, thereby informing future research directions in visualization authoring systems.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/TVCG.2019.2934281
