Rule-Based Canonicalization of Arbitrary Tables in Spreadsheets

Arbitrary tables presented in spreadsheets can be an important data source in business intelligence. However, many of them have complex layouts that hinder the process of extracting, transforming, and loading their data in a database. The paper is devoted to the issues of rule-based data transformation from arbitrary tables presented in spreadsheets to a structured canonical form that can be loaded into a database by regular ETL-tools. We propose a system for canonicalization of arbitrary tables presented in spreadsheets as an implementation of our methodology for rule-based table analysis and interpretation. It enables the execution of rules expressed in our specialized rule language called CRL to recover implicit relationships in a table. Our experimental results show that particular CRL-programs can be developed for different sets of tables with similar features to automate table canonicalization with high accuracy.