TEI Analytics: converting documents into a TEI format for cross-collection text analysis
Identifieur interne : 000116 ( Main/Merge ); précédent : 000115; suivant : 000117TEI 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.
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.
Links toward previous steps (curation, corpus...)
- to stream PascalFrancis, to step Corpus: 000018
- to stream PascalFrancis, to step Corpus: 000023
- to stream PascalFrancis, to step Curation: 000027
- to stream PascalFrancis, to step Checkpoint: 000013
Links to Exploration step
Pascal:10-0030973Le document en format XML
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<author><name sortKey="Pytlik Zillig, Brian L" sort="Pytlik Zillig, Brian L" uniqKey="Pytlik Zillig B" first="Brian L." last="Pytlik Zillig">Brian L. Pytlik Zillig</name>
<affiliation wicri:level="2"><inist:fA14 i1="01"><s1>Center for Digital Research in the Humanities, University of Nebraska</s1>
<s2>Lincoln, NE</s2>
<s3>USA</s3>
<sZ>1 aut.</sZ>
</inist:fA14>
<country>États-Unis</country>
<placeName><region type="state">Nebraska</region>
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<date when="2009">2009</date>
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<sourceDesc><biblStruct><analytic><title xml:lang="en" level="a">TEI Analytics: converting documents into a TEI format for cross-collection text analysis</title>
<author><name sortKey="Pytlik Zillig, Brian L" sort="Pytlik Zillig, Brian L" uniqKey="Pytlik Zillig B" first="Brian L." last="Pytlik Zillig">Brian L. Pytlik Zillig</name>
<affiliation wicri:level="2"><inist:fA14 i1="01"><s1>Center for Digital Research in the Humanities, University of Nebraska</s1>
<s2>Lincoln, NE</s2>
<s3>USA</s3>
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<country>États-Unis</country>
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<series><title level="j" type="main">Literary and linguistic computing</title>
<title level="j" type="abbreviated">Lit. linguist. comput.</title>
<idno type="ISSN">0268-1145</idno>
<imprint><date when="2009">2009</date>
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<seriesStmt><title level="j" type="main">Literary and linguistic computing</title>
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<idno type="ISSN">0268-1145</idno>
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<profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Data conversion</term>
<term>Markup</term>
<term>Text</term>
<term>XML language</term>
</keywords>
<keywords scheme="Pascal" xml:lang="fr"><term>Texte</term>
<term>Conversion de données</term>
<term>Balisage (document)</term>
<term>Langage XML</term>
<term>TEI (Text Encoding Initiative)</term>
</keywords>
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<front><div type="abstract" xml:lang="en">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>
</front>
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