Data Management Plans (DMPs) are free-form text documents describing data used and produced in research projects. The workload and bureaucracy often associated with tradi- tional DMPs can be reduced when they become machine- actionable. However, there is no common definition of what machine-actionable DMPs really are. This hinders the com- munication between stakeholders and leads to scepticism, or conversely to exaggerated expectations. This paper aims to clarify what machine-actionable DMPs are and provides examples of how involved stakeholders can benefit from them. It describes an open stakeholder con- sultation performed by the RDA DMP Common Standards working group. The main objective was to define the scope of information covered by machine-actionable DMPs and formulate an initial set of requirements for a common data model for machine actionable DMPs. To do this we used methodology known from system and software requirements engineering to collect information on how needs for infor- mation of particular stakeholders evolve over phases of the research data lifecycle. Data Management Plans (DMPs) are free-form text documents describing data used and produced in research projects. The workload and bureaucracy often associated with tradi- tional DMPs can be reduced when they become machine- actionable. However, there is no common definition of what machine-actionable DMPs really are. This hinders the com- munication between stakeholders and leads to scepticism, or conversely to exaggerated expectations. This paper aims to clarify what machine-actionable DMPs are and provides examples of how involved stakeholders can benefit from them. It describes an open stakeholder con- sultation performed by the RDA DMP Common Standards working group. The main objective was to define the scope of information covered by machine-actionable DMPs and formulate an initial set of requirements for a common data model for machine actionable DMPs. To do this we used methodology known from system and software requirements engineering to collect information on how needs for infor- mation of particular stakeholders evolve over phases of the research data lifecycle.