From Services to Adoption
Research data management (RDM) service landscapes are becoming increasingly diverse. Across research communities, infrastructures, consortia, and institutions, many services, tools, training formats, guidance materials, and community-driven solutions already exist or are currently being developed. However, the mere existence of services does not automatically lead to their use. Results from community needs assessments and ongoing service coordination activities highlight a persistent gap between technical service development and user adoption: services may remain difficult to discover, insufficiently explained, poorly linked to practical guidance, or disconnected from the everyday workflows of researchers and institutions.
This contribution presents an emerging FAIRagro concept for Service–Community Integration. It addresses the question of how RDM services and tools can move from isolated development or single-service promotion towards coordinated, user-oriented implementation along supporting the researcher journey. The concept builds on ongoing FAIRagro activities, including service meetings, needs analyses, the development of service portfolio management structures, and first approaches to documenting and coordinating services in a shared service pipeline.
A central assumption is that service uptake requires more than dissemination. Researchers and institutions need a clearer understanding of what a service, tool, resource, or support offer provides; who it is intended for; which problem it addresses; how it connects to other RDM support structures; and how it can be practically integrated into research workflows. At the same time, service developers and researchers who create small but valuable tools need pathways to make these solutions visible, reusable, and connected to broader community support.
We therefore propose a set of benchmarks for Service–Community Integration. These benchmarks include: a actionable service definition and target group description; documented user needs and use cases; links to practical FAIR guidance; integration with training, helpdesk, and support activities; coordinated outreach and dissemination; mechanisms for user feedback; and connection to monitoring, reporting, and portfolio management, including criteria to assess both the effort required for service integration and the impact achieved in practice. Together, these elements can help assess whether a service is not only technically available, but also prepared for sustainable community uptake.
The concept will be illustrated with selected FAIRagro examples, such as central RDMO and DMP services and agricultural-specific tools like the ClimData data application. These examples show how a structured pipeline — from service identification and description to guidance, dissemination, support, feedback, and monitoring — can help bring solutions to users more effectively.
By defining benchmarks for Service–Community Integration, the contribution aims to support a shift from promoting individual services towards supporting the full FAIR journey of researchers, data stewards, and institutions. This provides a practical basis for improving service visibility, strengthening user adoption, and demonstrating impact as a foundation for sustainable service operation.