Cem Birol, PhD
Research Data Senior Specialist, Koç University
Introduction
When university administrative professionals discuss open science, the conversation often remains normative. Most agree that scientific output should be findable, accessible, interoperable, and reusable – e.g., FAIR (Wilkinson et al, 2016). However, few address how scholars can be motivated to adopt these principles. Institutional policies remain declarative, laying out data management norms and expecting scholars to abide unquestioningly. Even worse, digital services for the FAIRification of scientific output are often overlooked by scholars (O’Neill et al, 2024). This creates the impression that a busy scholar will never fully implement FAIR principles.
At Koç University, we found that responsible open science practices need both scholars’ conviction that they must put in the effort and the relevant skills. The path to understanding and following the FAIR research data principles was neither driven by legal requirements nor supported by infrastructure. Instead, the answer lay in training sessions that addressed the practical needs of sponsored project partners or targeted those involved in the “kitchen” of research data operations.
Koç University (KU), located in Istanbul, Turkey, is a research-focused institution with a growing portfolio of international and nationally funded projects. As these projects became more complex, the need for clear guidance on data management and FAIR compliance also increased. This editorial explains how KU’s administrative units developed policies, services, and training programs that now support its FAIR practices.
The Early Days: From Open Access to Open Data
By 2020, open science in Turkey mainly remained an ideal rather than a practice. Turkish National Science Foundation, TÜBİTAK, introduced its open science policy in 2019. Nationwide digital initiatives, such as TRDizin and DergiPark, focused on indexing institutional repositories and expanding diamond open-access publishing. Meanwhile, the number of deposits of research replication materials in Turkey’s national data repository, APERTA, remained significantly fewer than manuscript uploads. Clearly, there was limited scholarly awareness of data-sharing norms in Turkey despite extant national guidelines.
At Koç University, awareness of open data gained momentum with the transition from the European Union’s Horizon 2020 to the Horizon Europe research sponsorship framework program. Under Horizon 2020, data sharing was merely encouraged. With Horizon Europe (2021-2027), FAIR-aligned data management practices became mandatory. In this context, Suna Kıraç Library (SKL), which had already developed KU’s Open Access policy in 2014, began networking with Western European universities for benchmarking. This initiated a process that would soon evolve into institution-wide efforts.
Foundations: A Cross-Departmental Working Group
In 2021, SKL coordinated the formation of KU’s Research Data Management (RDM) Working Group. Representatives from the Information Technology (IT) Directorate, Legal Counsel, and the Vice Presidency for Research and Development (VPRD) joined forces. Their initial tasks were pragmatic:
- Launching an institutional guide on RDM,
- Organizing webinars for scholars preparing Horizon Europe and TÜBİTAK-mandated data management plans (DMP), and
- Building an institutional research data repository.
The repository and guide quickly filled a gap in the institutional infrastructure. However, a more complex challenge remained: ensuring that scholars followed through on their DMP commitments. Principal investigators showed little interest in hours of highly valuable training videos and were rarely aware of the institutional infrastructure compliant with ISO-27001 standards. When needed, they wrote highly stylized DMPs with administrative help in response to sponsorship organizations’ mandates. Still, their adherence to FAIR principles remained unclear.
Institutionalization and Its Limits
By 2022, KU’s research portfolio had expanded dramatically. Projects involved more sensitive data, industrial collaborations on a greater scale, and scholars had to coordinate with international consortia. Supporting the management of these complexities required specialized expertise. Hence, the RDM working group evolved from a volunteer-based initiative into a structured unit with professional appointments. These new members were experts in the academic or legal aspects of data management.Professionalization in RDM brought consistency to data practices across KU units. Newly developed policy documents clarified academic and administrative responsibilities. More detailed institutional guidelines helped researchers understand expectations throughout the data lifecycle.
Formal structures alone, however, did not ensure that FAIR principles were fully integrated into daily research workflows. Even with clearer policies, adherence to FAIR principles still depended on individual researchers’ priorities. A minority of faculty members, who frequently applied for sponsorship to maintain their research, benefited from the RDM professionalization. Their research designs became more FAIR-oriented, and they wrote more convincing DMPs. All of these improved their chances of securing international funds. Nonetheless, many researchers who did not depend on sponsored projects for academic survival remained oblivious to FAIR principles and RDM group operations. None paid attention to many institution-wide emails sent about RDM trainings, alerts, or info sessions.
When Policing Doesn’t Work
In 2023, the RDM group aimed to strengthen institutional oversight by creating a university-wide research data inventory. Each sponsored project was classified by data type, sensitivity level, and storage location. While their goal was to identify institutional risks, the process uncovered a broader challenge common across universities: oversight systems rarely align with academic culture.
Many researchers, already balancing proposal deadlines, teaching duties, and research responsibilities, saw these data management monitoring requests as an extra administrative burden. Others handed off the task to research assistants or lab coordinators, resulting in inconsistent or incomplete reports to RDM professionals. This highlighted a structural reality: monitoring FAIR compliance through audits is hard to scale and often ineffective. This is not unique to KU; it reflects a global pattern in which researchers respond more to support and education than to inspection.
Turning Point: Smart and Practical Education
By 2024, it became clear that lasting progress required a shift from oversight to capacity-building. The faculty members paid minimal attention to the RDM group’s activities because they lacked time to reflect on why research data management deserved more than a few minutes of their already-constrained attention. To address this challenge, the RDM group’s trust-building strategy involved retracing the data-related questions most frequently raised by scholars and designing a webinar to address these concerns directly. This marked a deliberate departure from abstract sessions toward training grounded in researchers’ needs.
Specifically, training programs were redesigned to address real tasks encountered in sponsored projects: managing sensitive data in accordance with national and international regulations, organizing workflows that addressed institutional differences among partners, selecting appropriate storage solutions, and preparing Data Management Plans grounded in actual research needs. Approaching researchers with such relevant content conveyed a clear message: their practical challenges mattered, and institutional data expertise existed to support them. A pilot five-day course in November 2025 served as the first concrete step toward rebuilding trust between faculty and the RDM group. Participants not only received project-relevant training but also were encouraged to openly discuss and collaboratively tackle their real life data management challenges . Instead of limiting instruction to open science specialists, the curriculum brought together contributors from different stages of the research process: legal advisors, IT professionals, ethics board representatives, project managers, TÜBİTAK professionals, and researchers themselves. The success of the event demonstrated the value of this collaborative approach, and subsequent iterations of the webinar received external sponsorship for broader adoption.
Nearly all 30 registered attendees for the pilot course said they were seeking “practical” information to apply in their project management efforts. An end-of-course survey with 20 participants yielded promising results. Over 50% said the course was not only satisfactory but also surpassed their expectations. No one expressed dissatisfaction. Most respondents (≈85%) said they would recommend participation in similar events for a broader audience, including graduate students. On the ” On a 0-10 “would you recommend the event to your colleagues” question, 85.7% of respondents scored 8 or above.
The initiative also recognized that sustainable cultural change relies on those who work most closely with data. Therefore, KU is developing a broader data literacy training campaign aimed at graduate students, postdoctoral researchers, and lab coordinators. As part of this campaign, introductory modules like “Intro to R” and “Intro to Stata” are being designed to focus on data organization, cleaning, metadata, and documentation rather than advanced analytics. The goal is to instill good data habits early in researchers’ careers so that FAIR-aligned practices become a habit.
The Broader Lesson
Koç University’s experience offers a broader lesson for institutions navigating the intersection of Open Science, compliance, and academic freedom, particularly in emerging research systems. Building FAIR infrastructures and policies is essential, but it does not alter scholarly behavior. Monitoring and enforcement have limited value in academic contexts that depend on trust, autonomy, and intellectual initiative. Innovative training strategies, on the other hand, turn abstract obligations into concrete skills. It transforms FAIR from a symbolic and virtuous acronym into an everyday practice.
Looking Forward
KU’s experience emphasizes the importance of institutions turning high-level FAIR principles into practical actions. As more universities in Turkey and other countries start developing their own FAIR strategies, SKL intends to share lessons learned and support new initiatives.
This outward engagement highlights a broader understanding: FAIR is more than just a technical standard; it’s a collaborative framework. Institutions that have already addressed the challenges of policy development, training, and implementation can play a key role in assisting others in developing similar capabilities. KU’s journey demonstrates how such experience can be used to strengthen national and regional research environments.
Conclusion
Adherence to FAIR principles requires trust among all stakeholders of science: researchers, universities, and society. Control mechanisms can enforce minimum standards. However, trust cannot flourish in the absence of relevant education and awareness (Poteete et al 2010).
When researchers internalize why FAIR matters, compliance follows naturally. When graduate students and junior faculty learn to manage their data properly today, they not only reduce their principal investigators’ (PI) workload but also become tomorrow’s responsible PIs. Meanwhile, when institutions invest in targeted training, they likely reduce the need for policing. Koç University’s experience affirms that the road to FAIR compliance runs through awareness, not coercion.
