There is an increasingly urgent need to ensure the fullest possible preservation of research findings, both for proper validation of the research in question and to enable its comprehensive reuse. Furthermore, research undertakings are expensive and the return on investment needs to be secured by research funding agencies and public funding bodies through proper management of the knowledge that is required for the effective long-term reuse of results. Awareness of these facts leads to increasingly stringent regulations from funding agencies, which seek to enforce compliance of research data with specific policies. Hence, funding agencies are beginning to make Data Management Plans (DMP) increasingly mandatory before they will fund a research undertaking. In general, a DMP is a full text document that elaborates how the research data is handled, both during and after the project lifetime. In fact, a DMP includes policies for data management on different levels, as e.g. required by a formal framework the research has to comply with, as well as managerial parameters or policies that directly address the data management system level. Nevertheless, besides the pure establishment of policies, funders and researchers have further requirements concerning active aspects of data management, as e.g.: the continuous adoption of DMPs and its execution throughout the research lifecycle or to preserve the knowledge created during research that is needed for comprehensive later research validation. Because of the complexity of these and further requirements, management support is under discussion in various research communities. Within the international Research Data Alliance, these aspects are discussed within the so called Active DMP Interest Group.

This workshop will consider recent research and the outcomes of the next RDA ADMP IG workshop at Cern to discuss ADMP related topics and will address further open research questions around ADMPs, with a special focus on continuous adoption of DMPs and automation support. Hence, the aim of this workshop is to identify on base of submitted contributions and the conclusion of the discussion during the workshop the recent obstacles that prevent the realization of ADMPs and how those could be addressed. The outcome of this workshop will be the preparation of a roadmap towards a reference framework of ADMP management and automation.