Depicting historical persons and identities: A faceted approach

Brian Dobreski, Jian Qin, Melissa Resnick

Research output: Contribution to journalArticlepeer-review

Abstract

Archives are responsible for presenting historical materials to users while also placing them in context. Historical individuals and their identities pose specific challenges for the archive, including how to negotiate changing cultural perspectives on identity and how to convey and explain contexts to modern audiences. Contemporary subject representation practices in cultural heritage tend to offer a reductivist view of personal identity. Using a collection of visual images of nineteenth and twentieth century sideshow performers, the present work explored a faceted approach to representing personal identity in order to: 1) offer a more holistic view of historical individuals, their identities, and relationships; and 2) help place historical terms and perspectives into context in order to better support user understanding. Utilizing an inductive approach, the researchers developed a framework of seven facets of personal identity. A textual keyword analysis of existing title metadata for images in the collection was implemented in order to identify distinct individuals depicted and any facets associated with them. Finally, collection-based language and closest matches from several controlled vocabularies were used to assign values to the facets for all individuals. The resulting metadata offers a flexible, richer, more holistic analysis of personal identity for these materials, while also exposing some deeper issues concerning identity, performance, and visual imagery. Opportunities exist for further automation and application of this faceted system to other historical collections.

Original languageEnglish (US)
Pages (from-to)668-679
Number of pages12
JournalKnowledge Organization
Volume47
Issue number8
DOIs
StatePublished - 2020

Keywords

  • Facet analysis
  • Facets
  • Keywords
  • Persons

ASJC Scopus subject areas

  • Library and Information Sciences

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