Breaking down hurdles of current data citation practices: use cases and benefits of persistent identifiers for dataset elements.

This session introduces the output of the NFDI-funded consortium KonsortSWD, Measure TA.5-M.1 "Enhancing PID services as a base for a FAIR data infrastructure," a service to assign PIDs on the level of the inline data objects, such as survey variables. This technical solution aims to make data findability and accessibility on the lower granularity level of studies more efficient. Particularly in the Social Sciences, PIDs are commonly available on the study level, which is insufficient to unambiguously identify the information used and ensure an accurate data citation. By assigning PIDs to the fine-grained level of attributes, individual elements can be referenced and retrieved with the required metadata. Referencing research data and their inherited entities by Persistent Identifiers (PIDs) supports FAIR data usage. Textual data citations without a unique identifier are non-standard practices that lead to consequences such as making it inefficient to identify critical variables and reuse them. From the technical perspective, it also hinders automated access to variables, making harmonisation very expensive since it is costly and time-consuming. The PIDs for variables registration service simplify FAIR data management and benefit both researchers and research data repositories (RDCs), fostering credibility results and ensuring the sustainable reusability of data. RDCs directly benefit from PIDs regarding data governance activities and the services they provide. PIDs as data identifiers have far advantages in terms of machine-actionable features: enabling citation tracking and aggregating, scientific production combination; empowering authority; promoting digital connections among researchers, organisations, and research outputs. Explicit relations between those elements are possible and favour the formation of a network into a knowledge graph representation. Since PIDs are machine-actionable, they are the technical bridges to the FAIR principles that can increase the traceability of research results in the Social and Economic Sciences.KonsortSWD is funded by the German Research Foundation (DFG) within the framework of the NFDI – project number: 442494171