Data management plans (DMPs) are formal and structured documents that capture all relevant information along the data lifecycle and beyond. A DMP typically describes data handling, archiving, sharing, access, usage and interpretation. A DMP instance applies a certain DMP template in order to address a specific funder or institution for a given use case. However, the structure of existing DMP templates is often designed for funder’s requirements and is consequently generic in scope to address diverse research projects and communities. Thus, these templates often lack guidance on how to structure discipline-specific information in a DMP and information on related consequences, when not following recommended steps. Moreover, additional guidance is often provided in consultations or as unstructured text in specific DMP tools or separate documents and is therefore not prepared for discovery or reuse. To address these challenges, we propose to structure DMP guidance by applying a pattern concept. The pattern concept was developed to collect proven solutions for frequently occurring problems. First patterns covered architecture elements, like specific window forms for specific house forms. By now, the pattern concept is well-established in several disciplines, in particular as software design patterns tackling frequently occurring IT problems and providing solution blueprints. ... With our proposed DMP guidance template, we provide a common structure for DMP guidance facilitating (1) DMP writing across disciplines, (2) the provision of concrete examples (best practices), and (3) the provision of consequences to foster awareness for certain data management topics.