Rethink how you plan your management activities with OpenDMP software: from describing research outputs to connecting research workflows

Planning research data management (RDM) activities is essential to establish a strong foundation for responsible and reproducible research. This includes adhering to best practices and meeting requirements in order to produce high-quality, validated research outcomes. Data Management Plans (DMPs) are crucial in implementing RDM policies and outlining the necessary activities, means, and effort required to manage research data effectively. In response to their growing demand, DMP software platforms and resources have emerged to give researchers a head start into planning their data management activities. Lately, the concept of DMPs is expanding to support the management not only of data, but of software, workflows and other research outputs (EC Horizon Europe DMP requirements). As a result, DMP platforms need to be flexible to accommodate the rapidly changing landscape, especially in the European Open Science Cloud (EOSC), to make adoption of RDM best practices easy by all research stakeholders.

The poster is about OpenDMP software that ARGOS service is based (https://code-repo.d4science.org/MaDgiK-CITE/argos) and its deployment in different countries, institutions and infrastructures. It aims to showcase the software’s flexibility in adapting to both policy and technical RDM needs and maturity of diverse research and innovation ecosystems. To do so, it presents the features that contribute to its dynamic configuration by stakeholders to then communicate how these are combined each time to support the national research communities of Spain (https://pgd.consorciomadrono.es), Portugal (https://opendmp.portaberta.pt), Poland (https://mitraria.man.poznan.pl) and internationals through OpenAIRE (https://argos.openaire.eu) and RSpace digital research platform (https://www.researchspace.com). Moreover, the poster will specify how the OpenDMP software is used by:

• Researchers - for writing and publishing FAIR DMPs and making the links with other research outputs.

• Data stewards, librarians and research support staff - for structuring machine actionable templates and customising resources and APIs.

• Universities and Research Institutions - for connecting to other services to automate data management planning and creating custom templates.

• Funders - for supporting their RDM policies.

Finally, ongoing work and next steps are presented as part of the team’s efforts towards seamless, validated and automated data, software and other outputs management planning.