RAISE Suite contributed to TPDL 2026 in Faro, Portugal, with research addressing one of the key challenges in machine-actionable Data Management Plans: turning policy requirements into information that machines can interpret and act upon.
During the 30th International Conference on Theory and Practice of Digital Libraries (TPDL 2026), RAISE Suite partners from OpenAIRE presented the paper:
“Enhancing Machine-Actionable DMPs with Policy Entities Expressed in ODRL”
The presentation took place within Session 1 – Data Management Plans and FAIR Assessment, bringing the RAISE Suite work on machine-actionable Data Management Plans to the international digital libraries and research data management community.
Making policy compliance more machine-actionable
The paper presents a systematic mapping of the RDA DMP Common Standard to ODRL constructs, exploring how policy information can be formally represented within machine-actionable DMPs.
The research was motivated by empirical evidence from the OSTrails project, where policy compliance emerged as one of the most demanded, yet least automatable, dimensions of maDMP evaluation. By addressing this gap, the work investigates how DMPs can move beyond static planning documents and become more actionable components of research data management workflows.
Connecting the research to RAISE Suite
Machine-actionable DMPs are a core element of the RAISE Suite approach to FAIR-by-design research data management. The project aims to use maDMPs to guide processes across the research data lifecycle, from data collection and transformation to management, sharing, reuse and exploitation.
Presenting this work at TPDL 2026 provided an opportunity to exchange knowledge with researchers and practitioners working on FAIR Data, research data management, interoperability and Open Science, while contributing to ongoing discussions on how DMPs can better support automated and policy-aware research workflows.
The paper was authored by Elli Papadopoulou, Maria Kontopidi, George Konstantinidis, Christopher Maidens, Dimosthenis Natsos, Georgios Kakaletris, Natalia Manola, Diamantis Tziotzios and Evdokimos Konstantinidis.
RAISE Suite will continue working towards making research data management more automated, interoperable and FAIR from collection to exploitation.