Falx: Synthesis-Powered Visualization Authoring


Modern visualization tools aim to allow data analysts to easily create exploratory visualizations. When the input data layout conforms to the visualization design, users can easily specify visualizations by mapping data columns to visual channels of the design. However, when there is a mismatch between data layout and the design, users need to spend significant effort on data transformation. We propose Falx, a synthesis-powered visualization tool that allows users to specify visualizations in a similarly simple way but without needing to worry about data layout. In Falx, users specify visualizations using examples of how concrete values in the input are mapped to visual channels, and Falx automatically infers the visualization specification and transforms the data to match the design. In a study with 33 data analysts on four visualization tasks involving data transformation, we found that users can effectively adopt Falx to create visualizations they otherwise cannot implement.

Best Paper
Chenglong Wang
University of Washington, Seattle, Washington, United States
Yu Feng
University of California, Santa Barbara, Santa Barbara, California, United States
Rastislav Bodik
University of Washington, Seattle, Washington, United States
Isil Dillig
University of Texas, Austin, Austin, Texas, United States
Alvin Cheung
University of California, Berkeley, Berkeley, California, United States
Amy J. Ko
University of Washington, Seattle, Washington, United States





会議: CHI 2021

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2021.acm.org/)

セッション: Engineering Interactive Applications

[B] Paper Room 05, 2021-05-14 01:00:00~2021-05-14 03:00:00 / [C] Paper Room 05, 2021-05-14 09:00:00~2021-05-14 11:00:00 / [A] Paper Room 05, 2021-05-13 17:00:00~2021-05-13 19:00:00
Paper Room 05
14 件の発表
2021-05-14 01:00:00
2021-05-14 03:00:00