Regular Table Language for Data Extraction from Document Tables Accessible in Machine-Readable Formats

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Abstract
This paper introduces ‘‘Regular Table Language’’ (RTL), a novel domain-specific language designed for extracting recordsets from arbitrary tables presented in machine-readable documents, such as spreadsheets, rich text, web pages (HTML), etc. The foundation of RTL rests on the hypothesis that any table can be aligned with a pattern that defines its structure. Furthermore, a whole class of tables designed by one template can be specified by one pattern. RTL offers a formalized way to express such patterns in a clear and concise manner. It is also proposed the ‘‘Interpretable Table Model’’ (ITM) as an intermediary between source tables and target recordsets. This model extends the conventional table structures found in widely used formats by adding semantics that provide the automatic inference of recordsets from tables. This semantics is recovered through matching appropriate RTL-patterns with ITM-instances generated from source tables. Both RTL and ITM have been implemented as core components of RegTab, an open-source software library designed to streamline the development of custom applications where data sources are various tables presented in electronic documents.

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