Conference Agenda

Across Europe, universities and public authorities increasingly rely on monitoring instruments to assess research performance and inform funding decisions. Yet most existing monitoring systems remain heavily focused on output indicators such as publication counts doctorates, and citation metrics. These output driven approaches have been widely criticised for narrowing academic practice, reinforcing inequalities, distorting incentives and stimulating questionable research behaviours (Bruton, Medlin, Brown, & Sacco, 2020; Collyer, 2023). They risk prioritising quantities over qualities, amplifying internal competition and discouraging ambitious or high-risk research trajectories (Collyer, 2023; D’Angelo, 2025).

In response, many institutions are exploring alternative approaches. One approach is to combine output data with administrative information and survey based insights. Survey data can illuminate important aspects of academic work (e.g. workload, autonomy, and wellbeing) yet they are seldom linked systematically to administrative datasets or performance indicators. Administrative data (e.g. careers, resource allocation) also remain underused, despite their potential to reveal structural patterns that shape research environments. When these datastreams are brought together, monitoring systems can capture both the conditions under which research is conducted and the outcomes it produces which can lead to robust evidence-based policies.

A key rationale for integrating diverse data sources is that working conditions and behavioural intentions influence research practices long before outcomes become visible. Frameworks such as the Job Demand–Control model and the Job Demands–Resources model (Bakker & Demerouti, 2017) point to how structural and psychosocial factors shape academic work, while the Theory of Planned Behaviour (Azjen, 2011) highlights how intentions can signal likely behavioural change at an early stage. These perspectives are essential to understanding what drives research activity, although participants may draw on their own theoretical or analytical frameworks when sharing their experiences.

Developing such integrated monitoring systems, however, poses substantial challenges. Beyond technical issues—data quality, interoperability, GDPR compliance and the lawfulness of linkages—institutions grapple with governance, accountability pressures, and sensitivities across faculties and disciplines. Many of these challenges are shared, yet rarely discussed collectively. Practical knowledge about development processes, design choices, pitfalls and organisational dynamics thus remains fragmented (Sakshaug & Steorts, 2023).

This workshop is designed as an open, practice oriented learning space where participants exchange experiences about how they have designed, adapted, or are developing their own monitoring systems. The workshop does not present a single model or best practice. Instead, it recognises that multiple institutions are experimenting in parallel, and that mutual learning is central to improving each institution’s approach. Participants are invited to share concrete examples, design dilemmas, early stage explorations, partial solutions or failed attempts—insights that are often under documented but highly instructive.

Structured discussion rounds guide participants in exploring how different institutions organise the development process, decide which indicators to include, arrange governance, and engage with disciplinary sensitivities and concerns. While data integration is one topic within this broader landscape, the workshop emphasises the full developmental pathway—from conceptualisation and stakeholder engagement to governance, communication and institutional embedding.

The workshop aims for three outcomes:
(1) to identify good practices that can inform the ongoing development of participants’ own systems;
(2) to understand recurring challenges and structural obstacles, enabling more deliberate decision making; and
(3) to appreciate the diversity of approaches without striving for uniformity, recognising that monitoring must be context sensitive and meaningful for the communities it serves.

In doing so, the workshop aligns with SIG23’s interest in policy instruments as sociopolitical technologies that shape academic identities, autonomy and governance relations. By bringing together institutions engaged in similar work, the workshop contributes to understanding how monitoring systems emerge, operate in practice, and can be designed to support—rather than distort—the academic mission.