Recommendations for the Academic Citation of Digital Resources

Introduction and Background

The reuse of digital research data is a key concern in the Digital Humanities. While recent years have seen the creation of numerous high-quality digital resources and tools, the humanities still lack an established culture of citing and reusing such data. To address this challenge, a project based at the University of Vienna – conducted within the framework of CLARIAH-AT – has developed uniform and adaptable citation standards for digital resources. The initiative enhances the visibility, legal clarity, and scholarly interoperability of digital sources, thus addressing a core objective of the DHA-2021+ Strategy (Section 2.3).

Project Information

The aim of the project Recommendations for the Academic Citation of Digital Resources is to develop practical and consensus-based citation standards that can be applied both in university teaching and in research. Building on the existing citation guidelines of the Department of History at the University of Vienna, an expanded version was created that particularly addresses the challenges of working with digital materials. The standards cover six central types of resources:

• Software packages
• Datasets
• Digitized resources
• Social media
• Ephemeral content (e.g., livestreams, stories)
• AI-generated content and prompts

A comprehensive list of potential citation information for each of the six sections has been generated and can be found here .

The core of the project work was a workshop held in March 2025, attended by data experts from across Austria. Discussions addressed, among other things, the recognition of specialized contributions (e.g., annotation, schema design), the role of repositories, transparency of licensing, and the proper archiving and identification of ephemeral content. The handling of AI-generated content was also examined in depth: recommendations include providing transcripts and details of the models and prompt texts used – without attributing authorship to the AI system itself.

The developed citation formats are available in both footnote and bibliography formats and are designed to be modular. This allows them to meet the varied needs of research, teaching, and institutional documentation alike.