Although well-trained staff at the facility can help with research data management requests, they are generally not able to handle all cases or are not provided for in the facilities. This is where domain-specific helpdesks come into play, providing additional expertise. However, even these staff soon reach their limits in tricky scenarios resulting from variety of data formats, workflows and available repositories. Agricultural data management requests for example may range from large geodata to growth parameters all the way to genetic information and the proper handling of qualitative data. In these cases, it is paramount to be able to rely on a functioning network of associated data stewards who are experts in their (sub)field of research to engage with expertise requested. In this talk, we will present our concept of associated data stewards: When a request reaches a helpdesk and goes beyond its respective expertise, it is forwarded to a committed data steward, researcher or pool thereof, from another - in this case European - institution to which the request fits thematically, methodologically or locally. The associated data stewards may answer the request and return it, or several data stewards from interlinking fields may discuss and iterate the request. Currently, the Leibniz Centre for Agricultural Landscape Research (ZALF, Germany), the Wageningen Data Competence Center (WDCC, The Netherlands) and the Swedish University of Agricultural Sciences (SLU, Sweden) are piloting a domain-specific associated data steward network for agricultural research data management. In this talk, we will highlight the proposed setup and advantages of this network which has three important prerequisites: a) a clear definition of the agricultural sub-domains covered by each helpdesk including expertise of each data steward, b) a mutual understanding of each other's workflows and technical solutions and c) a structured workflow used to distribute requests which also re-informs the original receiving helpdesk of the result of the request (monitoring and feedback) - all the while complying with data protection regulations. The presentation uses agricultural data as a real-life example but reflects on issues and possible solutions that apply to a variety of research domains.