TableCanoniser: Interactive Grammar-Powered Transformation of Messy, Non-Relational Tables to Canonical Tables
Kai Xiong, Cynthia A. Huang, Michael Wybrow, Yingcai Wu
Abstract
TableCanoniser is a declarative grammar and interactive system for constructing relational tables from messy tabular inputs such as spreadsheets. We propose the concept of axis alignment to categorise input types and characterise the expanded scope of our system relative to existing tools. The declarative grammar consists of match conditions, which specify repeating patterns of input cells, and extract operations, which specify how matched values map to the output table. In the interactive interface, users can specify match and extract patterns by interacting with an input table, or author more advanced specifications in the coding panel. To refine and verify specifications, users interact with grammar-based provenance visualisations such as linked highlighting of input and output values, tree-based visualisation of matching patterns, and a mini-map overview of matched instances of patterns with annotations showing where cells are extracted to. We motivate and illustrate our work with real-world usage scenarios and workflows.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Builds on9
- "Help Me Help the AI": Understanding How Explainability Can Support Human-AI InteractionSunnie S. Y. Kim, Elizabeth Anne Watkins, Olga Russakovsky, Ruth Fong et al.CHI 2023 · 178 citations
- Untidy Data: The Unreasonable Effectiveness of TablesLyn Bartram, Michael Correll, Melanie ToryIEEE VIS 2021 · 56 citations
- How Do Analysts Understand and Verify AI-Assisted Data Analyses?Ken Gu, Ruoxi Shang, Tim Althoff, Chenglong Wang et al.CHI 2024 · 36 citations
- Diff in the Loop: Supporting Data Comparison in Exploratory Data AnalysisApril Yi Wang, Will Epperson, Robert A. DeLine, Steven Mark DruckerCHI 2022 · 34 citations
- Auto-Tables: Synthesizing Multi-Step Transformations to Relationalize Tables without Using ExamplesPeng Li, Yeye He, Cong Yan, Yue Wang et al.VLDB 2023 · 29 citations
Related papers
- Rigel: Transforming Tabular Data by Declarative MappingRan Chen, Di Weng, Yanwei Huang, Xinhuan Shu et al.IEEE VIS 2022 · 21 citations
- Table Illustrator: Puzzle-based interactive authoring of plain tablesYanwei Huang, Yurun Yang, Xinhuan Shu, Ran Chen et al.CHI 2024 · 5 citations
- Semantic table structure identification in spreadsheetsYakun Zhang, Xiao Lv, Haoyu Dong, Wensheng Dou et al.ISSTA 2021 · 11 citations
- CAST: Authoring Data-Driven Chart AnimationsTong Ge, Bongshin Lee, Yunhai WangCHI 2021 · 33 citations
- HiRegEx: Interactive Visual Query and Exploration of Multivariate Hierarchical DataGuozheng Li, Haotian Mi, Chi Harold Liu, Takayuki Itoh et al.IEEE VIS 2024 · 2 citations
