ReSED API - Re-Use Standards for Editions Data with Application Programming Interfaces
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Abstract
ReSED API is a project funded by Swissuniversities within its Open Research Data (ORD) Track A program. It aims to enhance the re-use of digital scholarly editions—critical digital representations of historical, literary, and other significant texts—by promoting machine-readable access through standardized Application Programming Interfaces (APIs). While such editions have long been re-used manually for research, teaching, and reference, modern digital formats now enable automated processing and large-scale analysis. However, re-use remains limited due to technical barriers, inconsistent practices, and a lack of widely adopted standards.
Re-using edition data offers considerable benefits: enabling large-scale text analysis, supporting historical and literary research, potentially training AI models, and integrating scholarly resources into broader digital archives. To fully realize this potential, the project emphasizes alignment with FAIR principles (Findable, Accessible, Interoperable, and Reusable), ensuring that digital editions can be reliably discovered and re-used across disciplines.
The project pursues two primary goals:
- Explore ORD practices related to data-re-use and APIs within the field of editions;
- Specify ORD standards based on the analysis of the needs and desiderata of the community.
To achieve these goals, the ReSED API project will conduct structured interviews with key stakeholders, organize interdisciplinary workshops and training sessions, and produce deliverables such as reports on data-sharing practices, training materials, guidelines for data re-use, and drafted API specifications tailored to scholarly needs.
By fostering a culture of data re-use and promoting technical standardization, the project will make edition data more accessible and reusable, advance digital humanities research, and support broader applications such as federated search, large-scale computational analysis, and machine learning training. Ultimately, this initiative will ensure that digital scholarly editions remain discoverable, interoperable, and reusable for future generations of researchers.
