Readers, you may find this blog posting of interest:
http://datamining.typepad.com/data_mining/2010/08/the-interpretation-of-tables-in-texts-2000.html
First, this guy (not to be rude, his name is Matthew Hurst) did his PhD on the depiction of data in tables. This is interesting in of itself. By tables I mean a plain old box with fields in rows and columns. It may seem “useless” or “stupid” to a lot of people but how many of us read data in this format today? Excel alone means probably millions. I, for one, am glad that people are working on ways to improve this.
Now comes the value added part. The author goes on to reference an article, “Exploiting a Web of Semantic Data for Interpreting Tables”, which can be found here:
http://journal.webscience.org/322/
The abstract states:
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.
I’m looking forward to what this collaboration yields.