TableCanoniser: Interactive Grammar-Powered Transformation of Messy, Non-Relational Tables to Canonical Tables
Year: 2025
Type: conference-paper
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.
Institutions: Zhejiang University, Monash University
Language: English
Subfield: Software
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
Funder: Australian Government
OpenAlex ID: W4409749522