Modelling gender diversity: research data representation beyond the binary

w/ Lisa Poggel, Franziska Diehr, Lindsey Drury
DH2022: Responding to Asian Diversity Tokyo/Online

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.

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