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  • 标题:Modeling Citable Textual Analyses for the Homer Multitext
  • 本地全文:下载
  • 作者:Christopher Blackwell ; Neel Smith
  • 期刊名称:Data Science Journal
  • 电子版ISSN:1683-1470
  • 出版年度:2016
  • 卷号:15
  • DOI:10.5334/dsj-2016-017
  • 语种:English
  • 出版社:Ubiquity Press
  • 摘要:The Homer Multitext project ( hmt ) is documenting the language and structure of Greek epic poetry, and the ancient tradition of commentary on it. The project’s primary data consist of editions of Greek texts; automated and manually created readings analyze the texts across historical and thematic axes. This paper describes an abstract model we follow in documenting an open-ended body of diverse analyses. The analyses apply to passages of texts at different levels of granularity; they may refer to overlapping or mutually exclusive passages of text; and they may apply to non-contiguous passages of text. All are recorded in with explicit, concise, machine-actionable canonical citation of both text passage and analysis in a scheme aligning all analyses to a common notional text. We cite our texts with urns that capture a passage’s position in an Ordered Hierarchy of Citation Objects ( ohco2 ). Analyses are modeled as data-objects with five properties. We create collections of ‘analytical objects’, each uniquely identified by its own urn and each aligned to a particular edition of a text by a urn citation. We can view these analytical objects as an extension of the edition’s citation hierarchy; since they are explicitly ordered by their alignment with the edition they analyze, each collection of analyses meets satisfies the ( ohco2 ) model of a citable text. We call these texts that are derived from and aligned to an edition ‘analytical exemplars’.
  • 关键词:rdf; greek; text; canonical; citation
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