Enhancing FAIR Research Data Management by enabling fine-grained data citation by PIDs for dataset elements

Persistent Identifiers (PIDs) at the study or dataset level are insufficient for addressing the complexity of data management in research. The lack of granularity citation at the level of inline data objects, such as individual survey variables, qualitative data files, and even smaller data points, leads to ambiguities in data citation, inadequate metadata, and data discovery and reusability challenges. The PID registration service introduced by KonsortSWD, part of the German National Research Data Infrastructure (NFDI), significantly advances the granularity of PIDs. This service supports the assignment of PIDs to these finer dataset elements and ensures accurate data citation since researchers usually use only a subset of the elements in a dataset. The service boosts data referencing practices and also ensures adherence to FAIR principles by enabling precise referencing of individual data elements. A single data point, the PID, enhances data citation, reuse, and direct access for automated access (i.e., by a computer program and under some requirements). In terms of implementation, the technical solution employs the ePic API and relies on the Handle standard. Tests PIDs have been successfully applied to diverse datasets, including survey variables from GESIS and the German Institute for Economic Research (DIW). Tests are also currently taking place at the German Center for University and Science Research (DZHW) in 2024 and are planned at Qualiservice in 2025. By serving as a base service under the umbrella of PID4NFDI, KonsortSWD's PID service provides a scalable framework that can adapt to many domains across the NFDI.