We recently published a practical guide to managing Religious Studies research data, from project design to long-term preservation.
For many senior scholars, research data management is no longer a peripheral concern but an integral part of responsible scholarship. Whether working with manuscript collections, fieldwork interviews, digital corpora, or archival materials, researchers increasingly face questions about documentation, preservation, ethics, legal compliance, and long-term accessibility of their research materials.
The newly published Research Data Management for Religious Studies: A Practitioner Guide has been developed to address these challenges. Written specifically for the Religious Studies community, it offers practical, step-by-step guidance on managing research data throughout its lifecycle, from project planning and Data Management Plans (DMPs) to repository deposit and long-term preservation.
Of particular value is the guide’s attention to issues that are central to our field: handling sensitive data related to religious beliefs and practices, working with multilingual and culturally significant materials, navigating GDPR requirements, and balancing openness with ethical and legal responsibilities.
The guide combines practical recommendations with templates, checklists, and real-world examples, helping researchers establish sustainable workflows that improve the transparency, reproducibility, and future reuse of their research outputs. As research becomes increasingly digital and collaborative, such practices are essential for ensuring that the scholarly record remains accessible and meaningful for future generations of researchers.
The guide is now available here.
The Research Data Management for Religious Studies: A Practitioner Guide was developed in the framework of RESILIENCE Preparatory Phase Project by WP2, together with a FAIRification Guide and the report Research Services Useful for the Religious Studies Community. These resources support researchers in collecting, managing, preserving, and sharing research data, software, and related outputs in accordance with good data management practices.