Modelling Gender Diversity: Research Data Representation Beyond the Binary
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.
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. Tokyo: Alliance of Digital Humanities Organizations (ADHO), 2022. 10.5281/ZENODO.7060309.
