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Modelling Gender Diversity: Research Data Representation Beyond the Binary

Book Chapter

Book Chapter

Viktor J. Illmer, Lisa Poggel, Franziska Diehr, Lindsey Drury – 2022

How may we model gender to account for its diversity while remaining simple enough to implement and query? We address why gender diversity needs to be represented in databases, especially when confronted with historical sources. Analysing examples of gender modelling in established metadata schemata and descriptive data models, we propose a model that strikes a balance between a detailed and flexible ontology that returns valid results even for naïve data queries. We introduce the use of gender qualifiers, which allow nuanced statements on how the gender information was formulated. Use of the proposed modelling strategies are demonstrated following the Wikibase data model.

Title
Modelling Gender Diversity: Research Data Representation Beyond the Binary
Author
Viktor J. Illmer, Lisa Poggel, Franziska Diehr, Lindsey Drury
Location
Tokyo
Keywords
Book Chapter; RA 5: Building Digital Communities
Date
2022
Appeared in
DH2022 Local Organizing Committee (Eds.): Book of Abstracts DH2022: Responding to Asian Diversity, Tokyo, Japan, July 25-29, 2022
Type
Text
Coverage
This publication is the result of work carried out in Research Area 5: Building Digital Communities.
How to cite:
Viktor J. Illmer, Lisa Poggel, Franziska Diehr, and Lindsey Drury. "Modelling Gender Diversity: Research Data Representation beyond the Binary". In Book of Abstracts DH2022: Responding to Asian Diversity, Tokyo, Japan, July 25-29, 2022, edited by the DH2022 Local Organizing Committee, 2022. 10.5281/ZENODO.7060309.