Integrating Open Research Data into Research Assessment: Insights and Challenges

In recent years, calls for reform in research assessment have intensified, with international initiatives such as DORA or CoARA. These efforts advocate for moving beyond mainstream metrics, particularly the controversial over-reliance on bibliometrics, towards innovative evaluation approaches that recognize diverse research outputs. This shift aligns closely with the Open Science movement, where practices like Open Research Data (ORD) are receiving growing attention. Increasingly, FAIR data production and sharing are expected by universities and funding bodies, prompting to include ORD in the assessment of scientific production. To support researchers in this transition, higher education institutions (HEI) are developing infrastructures, trainings and services in Research Data Management (RDM) to facilitate the integration of ORD into everyday academic practices.

However, integrating ORD into research assessment frameworks remains complex and raises concerns, particularly in the social sciences, where the diversity of data types and their sensitive nature often complicates data sharing. What are the main challenges HEIs face in embedding ORD into evaluation processes? How can these challenges be addressed to ensure effective and equitable research assessments?

Experts in RDM play a crucial role in tackling these issues by identifying challenges to the formal recognition and assessment of ORD. This communication draws on findings from a survey conducted across 30 Swiss higher education institutions, targeting individuals involved in research assessment and ORD policy implementation. While most institutions have some strategies in place, dedicated funding and comprehensive assessment mechanisms remain scarce. Moreover, the analysis identifies four types of barriers–financial, technical, social and epistemic– that impede the recognition of ORD as a legitimate research output. Based on these findings, we will offer a series of recommendations to address these challenges and contribute to the ongoing discussion on applying and assessing ORD to the specificities of social sciences.