Serving Literary Knowledge as Data: Building and Documenting DH APIs with PostgreSQL
Tuesday, September 09 at 12:10–13:00
In Digital Humanities (DH), the challenge of making interpretive research—such as literary symbolism, historical analysis, or cultural studies—queryable and accessible can be met through powerful APIs built on relational databases. In this talk, we’ll demonstrate how PostgreSQL can serve as the backbone for creating an API that transforms subjective analysis into structured and queryable data.
Using examples from symbolic analysis of cultural texts, we'll walk through key PostgreSQL features, like jsonb, views, and full-text search, that enable the modeling, querying, and retrieval of interpretive knowledge.
Additionally, we'll cover best practices for generating API documentation using tools such as Swagger and MkDocs, ensuring that your APIs are accessible not just to developers, but also to scholars who may not be familiar with the underlying data models. The session will also address the epistemological implications of exposing interpretive data as a public dataset: How to manage uncertainty, signal multiple interpretations, and what it means to present human analysis in a structured and queryable format.
Viewers will gain practical insights into using PostgreSQL to support Digital Humanities projects and learn how to create and manage APIs that make interpretive knowledge more accessible to a broader audience.
