Home News FAIRsFAIR Implementation story: Leveraging machine-actionable DMPs to build RDM infrastructures

FAIRsFAIR Implementation story: Leveraging machine-actionable DMPs to build RDM infrastructures

Article written by Samah Jaber, FAIR Office Austria

The work on DAMAP and the FAIR Data Austria (FDA) project are featured in an implementation story published by the FAIRsFAIR project. The work supports “Turning FAIR into Reality” as recommended in the EC Expert Group on FAIR report.

The FAIRsFAIR Implementation & Adoption Stories team interviewed Tomasz Miksa to share the good practice and provide an insight into creating a machine-actionable DMP tool, DAMAP, that helps researchers to plan for FAIR data and support the creation of FAIR data and to integrate this tool with institutional services that respond to the needs identified in the DMP.

This effort has gained support from FAIR Data Austria, a project running from January 2020 to December 2022 to strengthen knowledge exchange between Austrian universities and develop training, tools and support services to manage data in accordance with the FAIR principles throughout the whole research lifecycle. (Blumesberger et al., 2021)

Overview of the DAMAP tool integration with other systems, from Castellano (2021)

• Taking advantage of a new standard

Funding bodies and other policy-makers are more concerned with DMPs. The machine-actionable DMP is used to make the DMP interoperable, automated and increasingly standardized.
The Center for Research Data Management at TU Wien offers support to researchers to put the machine-actionable DMP idea into practice across the whole research data lifecycle.

• Coordinating service provision within and across universities

DAMAP aims to improve university internal workflows, e.g. allowing reporting on storage needs that have been highlighted in DMPs and using this information to provision for the expected storage needs, that would help the relevant units in the university reflect on their own workflows and market their offers better to researchers.

When a researcher now picks one of the storage options in the DAMAP tool, details on data storage are automatically populated for them. This should support researchers in making the right storage choices, to ensure the data can be made FAIR.

• Making the most of standards

DAMAP follows the DMP template guidelines issued by Science Europe and applies the RDA maDMP application profile taking their guidance and evaluation criteria into account when supporting the researcher in answering the questions.

• Integrating the DMP tool with institutional workflows

Managing expectations and demand for services as researchers’ awareness of these available services is a core challenge in integrating the DMP tool with institutional workflows. The DMP workflow integration with storage provision has led to useful synergies being identified, which may help bring researchers and providers in closer contact. For DAMAP we get synergies by asking the service providers quality of service questions and they had to figure these questions out for the first time. Further conversations are ongoing to address DAMAP’s adoption of standards.


DAMAP is currently being developed by TU Wien and TU Graz and it is available open source for everyone to install at their premises [code below]. It is based on data management plans (maDMPs) concept to facilitate the creation of data management plans (DMPs) for researchers. The tool is closely integrated into the institutional environment and it helps researchers to generate an initial DMP that they can export as a Word document and then customize it further to be communicated and shared across stakeholders, repositories and institutions.
The content of DAMAP is based on Science Europe’s Practical Guide to the International Alignment of Research Data Management.

Further Readings and References