Literary and Linguistic Computing Advance Access originally published online on April 15, 2009
Literary and Linguistic Computing 2009 24(2):187-192; doi:10.1093/llc/fqp005
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This article appears in the following Literary and Linguistic Computing issue: Special Issue 'Selected papers from Digital Humanities 2008, University of Oulu, Finland, June 25–29' [View the issue table of contents]
TEI Analytics: converting documents into a TEI format for cross-collection text analysis
Center for Digital Research in the Humanities, University of Nebraska, Lincoln, NE, USA
Correspondence: Center for Digital Research in the Humanities, University of Nebraska, Lincoln, NE, USA. E-mail: bpytlikz{at}unlnotes.unl.edu; bzillig1{at}unl.edu
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Abstract |
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For the purposes of large-scale analysis of XML/SGML files, converting humanities texts into a common form of markup represents a technical challenge. The MONK (Metadata Offer New Knowledge) Project has developed both a common format, TEI Analytics (a TEI subset designed to facilitate interoperability of text archives) and a command-line tool, Abbot, that performs the conversion. Abbot relies upon a new technique, schema harvesting, developed by the author to convert text documents into TEI-A. This article has two aims: first, to describe the TEI-A format itself and, second, to outline the methods used to convert files. More generally, it is hoped that the techniques described will lead to greater interoperability of text documents for text analysis in a wider context.