This presentation, delivered at the CoMeCT TCB–CCB joint meeting in June 2024, described how machine-actionable data management plans (maDMPs), developed using the Argos platform, were leveraged to strengthen FAIR data adoption and enable more effective collaboration among trial and cohort partners. It outlined how maDMPs move beyond static documentation by structuring key information on data collection, governance, standards, and access conditions in a machine-readable format, enabling aggregation via APIs and integration into the OpenAIRE Knowledge Graph. This approach was presented as a critical mechanism for building earlier and closer collaboration between related data partners, as it enables visibility into data structures, standards, and governance decisions at the start of a project rather than after data collection is complete. By generating a dynamic knowledge graph of relationships among studies, the approach supports identifying gaps, alignment opportunities, and barriers to semantic and syntactic interoperability across consortia. The presentation emphasised that this early, structured coordination is essential for achieving FAIR convergence, informing investment in interoperability, and enabling scalable linkage of trials and cohorts. It also highlighted how iterative updates to maDMPs, combined with monitoring tools such as OpenAIRE, can support continuous assessment of FAIR implementation and foster a more connected, transparent, and collaborative data ecosystem.