Presentation Open Access
Holmes, Martin;
Fralick, Kaitlyn;
Fukushima, Kailey;
Karlson, Sarah
<?xml version='1.0' encoding='utf-8'?> <resource xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="http://datacite.org/schema/kernel-4" xsi:schemaLocation="http://datacite.org/schema/kernel-4 http://schema.datacite.org/meta/kernel-4.1/metadata.xsd"> <identifier identifierType="DOI">10.5281/zenodo.3449241</identifier> <creators> <creator> <creatorName>Holmes, Martin</creatorName> <givenName>Martin</givenName> <familyName>Holmes</familyName> <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0002-3944-1116</nameIdentifier> <affiliation>University of Victoria HCMC</affiliation> </creator> <creator> <creatorName>Fralick, Kaitlyn</creatorName> <givenName>Kaitlyn</givenName> <familyName>Fralick</familyName> <affiliation>University of Victoria</affiliation> </creator> <creator> <creatorName>Fukushima, Kailey</creatorName> <givenName>Kailey</givenName> <familyName>Fukushima</familyName> <affiliation>University of Victoria</affiliation> </creator> <creator> <creatorName>Karlson, Sarah</creatorName> <givenName>Sarah</givenName> <familyName>Karlson</familyName> <affiliation>University of Victoria</affiliation> </creator> </creators> <titles> <title>How we tripled our encoding speed in the Digital Victorian Periodical Poetry project</title> </titles> <publisher>Zenodo</publisher> <publicationYear>2019</publicationYear> <dates> <date dateType="Issued">2019-09-19</date> </dates> <language>en</language> <resourceType resourceTypeGeneral="Text">Presentation</resourceType> <alternateIdentifiers> <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/3449241</alternateIdentifier> </alternateIdentifiers> <relatedIdentifiers> <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.3449240</relatedIdentifier> <relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://zenodo.org/communities/tei2019</relatedIdentifier> </relatedIdentifiers> <rightsList> <rights rightsURI="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights> <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights> </rightsList> <descriptions> <description descriptionType="Abstract"><p>The Digital Victorian Periodical Poetry (DVPP) project is a SSHRC-funded digital humanities<br> project based at the University of Victoria. With the guidance of principal investigator Dr. Alison<br> Chapman, the DVPP team is creating a digital index of British periodical poetry from the long<br> nineteenth century. In addition to uncovering periodical poems, writing descriptive metadata, and<br> compiling prosopographical research, we are currently using TEI and CSS to encode a statistically-<br> representative sample of indexed poems, looking for quantitative evidence of literary change over<br> time. Such an endeavour requires a large, robust dataset covering a range of periodicals throughout<br> the period.<br> At the time of writing, there are more than 13,000 poems in the database, and we expect that total<br> to reach 20,000. Of these, around 2,000 will be encoded, focusing on the decade years (1820, 1830,<br> 1840, and so on).<br> Journal of the Text Encoding Initiative,<br> 1How we tripled our encoding speed in the Digital Victorian Periodical Project<br> In this presentation, we will showcase the various strategies and tools we have used to speed up<br> our encoding process. We combine simple tricks like keyboard shortcuts with more sophisticated<br> processes to minimize drudgery and increase accuracy. Among the more interesting techniques<br> are:<br> &bull; Auto-tagging of a complete poem in lines and linegroups using a Schematron QuickFix;<br> &bull; Use of advanced CSS selectors in the rendition/@selector attribute to reduce encoding<br> clutter in the poem itself;<br> &bull;<br> A keyboard shortcut to tag rhymes which detects whether the tagged text is a masculine<br> or feminine rhyme and provides the appropriate attribute value;<br> &bull;<br> Auto-detection of cases where a new line-end rhymes with a previously-encoded rhyme,<br> and should, therefore, be labelled to match it, leveraging our growing dataset of nearly<br> 30,000 rhymes;<br> &bull;<br> Instant access to to a rendering of the poem which provides a visualization of the rhyme<br> structure, auto-detection of anaphora, epistrophe and other refrain-like forms, and other<br> diagnostic feedback.</p></description> </descriptions> </resource>
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