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Modest XML for Corpora: Not a standard, but a suggestion Cover

Modest XML for Corpora: Not a standard, but a suggestion

By: Andrew Hardie  
Open Access
|Apr 2014

Abstract

This paper argues for, and presents, a modest approach to XML encoding for use by the majority of contemporary linguists who need to engage in corpus construction. While extensive standards for corpus encoding exist - most notably, the Text Encoding Initiative’s Guidelines and the Corpus Encoding Standard based on them - these are rather heavyweight approaches, implicitly intended for major corpus-building projects, which are rather different from the increasingly common efforts in corpus construction undertaken by individual researchers in support of their personal research goals. Therefore, there is a clear benefit to be had from a set of recommendations (not a standard) that outlines general best practices in the use of XML in corpora without going into any of the more technical aspects of XML or the full weight of TEI encoding. This paper presents such a set of suggestions, dubbed Modest XML for Corpora, and posits that such a set of pointers to a limited level of XML knowledge could work as part of the normal, general training of corpus linguists.

The Modest XML recommendations cover the following set of things, which, according to the foregoing argument, are sufficient knowledge about XML for most corpus linguists’ day-to-day needs: use of tags; adding attribute value pairs; recommended use of attributes; nesting of tags; encoding of special characters; XML well-formedness; a collection of de facto standard tags and attributes; going beyond the basic de facto standard tags; and text headers.

DOI: https://doi.org/10.2478/icame-2014-0004 | Journal eISSN: 1502-5462 | Journal ISSN: 0801-5775
Language: English
Page range: 73 - 103
Published on: Apr 28, 2014
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2014 Andrew Hardie, published by The International Computer Archive of Modern and Medieval English
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.