Lyra 2: Designing Interactive Visualizations by Demonstration
Name
2008.09576.pdf
Description
Accepted version
Size
11.35 MB
Format
Adobe PDF
Checksum (MD5)
6a7c8f69fdb9704b729c0bfd4236206f
Author(s)
Zong, Jonathan
Barnwal, Dhiraj
Neogy, Rupayan
Satyanarayan, Arvind
Date Issued
2021
Journal
IEEE Transactions on Visualization and Computer Graphics
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Version
Author's final manuscript
Abstract
Recent graphical interfaces offer direct manipulation mechanisms for authoring visualizations, but are largely restricted to static output. To author interactive visualizations, users must instead turn to textual specification, but such approaches impose a higher technical burden. To bridge this gap, we introduce Lyra 2, a system that extends a prior visualization design environment with novel methods for authoring interaction techniques by demonstration. Users perform an interaction (e.g., button clicks, drags, or key presses) directly on the visualization they are editing. The system interprets this performance using a set of heuristics and enumerates suggestions of possible interaction designs. These heuristics account for the properties of the interaction (e.g., target and event type) as well as the visualization (e.g., mark and scale types, and multiple views). Interaction design suggestions are displayed as thumbnails; users can preview and test these suggestions, iteratively refine them through additional demonstrations, and finally apply and customize them via property inspectors. We evaluate our approach through a gallery of diverse examples, and evaluate its usability through a first-use study and via an analysis of its cognitive dimensions. We find that, in Lyra 2, interaction design by demonstration enables users to rapidly express a wide range of interactive visualizations.
MIT Department
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.2020.3030367
