Exploiting a Web of Semantic Data for Interpreting Tables

Abstract

Much of the world’s knowledge is contained in structured documents like spreadsheets, database relations and tables in documents found on the Web and in print. The information in these tables might be much more valuable if it could be appropriately exported or encoded in RDF, making it easier to share, understand and integrate with other information. This is especially true if it could be linked into the growing linked data cloud. We describe techniques to automatically infer a (partial) semantic model for information in tables using both table headings, if available, and the values stored in table cells and to export the data the table represents as linked data. The techniques have been prototyped for a subset of linked data that covers the core of Wikipedia.