TEI Analytics: converting documents into a TEI format for cross-collection text analysis
Identifieur interne : 000085 ( Main/Exploration ); précédent : 000084; suivant : 000086TEI Analytics: converting documents into a TEI format for cross-collection text analysis
Auteurs : Brian L. Pytlik Zillig [États-Unis]Source :
- Literary and Linguistic Computing [ 0268-1145 ] ; 2009-06.
Descripteurs français
- Pascal (Inist)
English descriptors
- KwdEn :
Abstract
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.
Url:
DOI: 10.1093/llc/fqp005
Affiliations:
Links toward previous steps (curation, corpus...)
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Le document en format XML
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<term>Conversion de données</term>
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<front><div type="abstract">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.</div>
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