Presentation Open Access

How we tripled our encoding speed in the Digital Victorian Periodical Poetry project

Holmes, Martin; Fralick, Kaitlyn; Fukushima, Kailey; Karlson, Sarah

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    <subfield code="a">&lt;p&gt;The Digital Victorian Periodical Poetry (DVPP) project is a SSHRC-funded digital humanities&lt;br&gt;
project based at the University of Victoria. With the guidance of principal investigator Dr. Alison&lt;br&gt;
Chapman, the DVPP team is creating a digital index of British periodical poetry from the long&lt;br&gt;
nineteenth century. In addition to uncovering periodical poems, writing descriptive metadata, and&lt;br&gt;
compiling prosopographical research, we are currently using TEI and CSS to encode a statistically-&lt;br&gt;
representative sample of indexed poems, looking for quantitative evidence of literary change over&lt;br&gt;
time. Such an endeavour requires a large, robust dataset covering a range of periodicals throughout&lt;br&gt;
the period.&lt;br&gt;
At the time of writing, there are more than 13,000 poems in the database, and we expect that total&lt;br&gt;
to reach 20,000. Of these, around 2,000 will be encoded, focusing on the decade years (1820, 1830,&lt;br&gt;
1840, and so on).&lt;br&gt;
Journal of the Text Encoding Initiative,&lt;br&gt;
1How we tripled our encoding speed in the Digital Victorian Periodical Project&lt;br&gt;
In this presentation, we will showcase the various strategies and tools we have used to speed up&lt;br&gt;
our encoding process. We combine simple tricks like keyboard shortcuts with more sophisticated&lt;br&gt;
processes to minimize drudgery and increase accuracy. Among the more interesting techniques&lt;br&gt;
&amp;bull; Auto-tagging of a complete poem in lines and linegroups using a Schematron QuickFix;&lt;br&gt;
&amp;bull; Use of advanced CSS selectors in the rendition/@selector attribute to reduce encoding&lt;br&gt;
clutter in the poem itself;&lt;br&gt;
A keyboard shortcut to tag rhymes which detects whether the tagged text is a masculine&lt;br&gt;
or feminine rhyme and provides the appropriate attribute value;&lt;br&gt;
Auto-detection of cases where a new line-end rhymes with a previously-encoded rhyme,&lt;br&gt;
and should, therefore, be labelled to match it, leveraging our growing dataset of nearly&lt;br&gt;
30,000 rhymes;&lt;br&gt;
Instant access to to a rendering of the poem which provides a visualization of the rhyme&lt;br&gt;
structure, auto-detection of anaphora, epistrophe and other refrain-like forms, and other&lt;br&gt;
diagnostic feedback.&lt;/p&gt;</subfield>
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