TabbyXL: Software platform for rule-based spreadsheet data extraction and transformation

摘要

Spreadsheets are widely used in science, engineering, business, and other activities. Overall, they conceal a large volume of data in a form intended to be interpreted by humans. We present a novel software platform facilitated for liberating such data. It provides rule-based spreadsheet data extraction and transformation to a structured form. Its core consists of a flexible table object model and a domain-specific rule language for table analysis. They serve to represent knowledge of table layout and content features, as well as their interpretation depending on transformation goals. This enables processing arbitrary tables originating from various domains. Our empirical results demonstrate that one ruleset can be applied to process arbitrary tables having the same features of layout, style, or content. The paper also describes two applications using the software platform to develop programs for rule-based converting data from arbitrary spreadsheet tables.