Datamator: An Authoring Tool for Creating Datamations via Data Query Decomposition

Yi Guo, Nan Cao*, Ligan Cai, Yanqiu Wu, Daniel Weiskopf, Danqing Shi, Qing Chen*

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

2 Citations (Scopus)
43 Downloads (Pure)

Abstract

Datamation is designed to animate an analysis pipeline step by step, serving as an intuitive and efficient method for interpreting data analysis outcomes and facilitating easy sharing with others. However, the creation of a datamation is a difficult task that demands expertise in diverse skills. To simplify this task, we introduce Datamator, a language-oriented authoring tool developed to support datamation generation. In this system, we develop a data query analyzer that enables users to generate an initial datamation effortlessly by inputting a data question in natural language. Then, the datamation is displayed in an interactive editor that affords users the ability to both edit the analysis progression and delve into the specifics of each step undertaken. Notably, the Datamator incorporates a novel calibration network that is able to optimize the outputs of the query decomposition network using a small amount of user feedback. To demonstrate the effectiveness of Datamator, we conduct a series of evaluations including performance validation, a controlled user study, and expert interviews.

Original languageEnglish
Article number9709
Number of pages18
JournalApplied Sciences (Switzerland)
Volume13
Issue number17
DOIs
Publication statusPublished - Sept 2023
MoE publication typeA1 Journal article-refereed

Keywords

  • authoring tool
  • data visualization
  • natural language interface

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