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Handling sensitive data responsibly is becoming an essential part of research. Yet for many researchers, formal training in safe, legal and ethical data use remains limited. This is exactly the gap that Dr. Frederic Gerdon is helping to address as a new member of the ASSURED project at GESIS – Leibniz Institute for the Social Sciences.
Frederic brings a combination of skills that align closely with ASSURED’s mission. His background rests on three core areas: empirical research, teaching, and data ethics. Trained in quantitative methods, he has worked extensively with data throughout his academic career. This experience gives him a strong understanding of how sensitive data are produced, what makes them valuable, and why they require careful handling.
Alongside his research expertise, Frederic has a clear commitment to teaching. He has taught at both Bachelor’s and Master’s levels and has completed formal training in higher education and learning. For him, teaching is not just about delivering content, but about designing materials that people actively engage with. This perspective plays an important role in ASSURED, where the goal is not simply to inform researchers, but to support meaningful learning and fostering the motivation to keep engaging with the covered topics.
A third pillar of his work is a long-standing interest in data ethics and privacy. Since his Master’s studies, Frederic has been engaged with questions around privacy and responsible data use. He is also involved in collaborative efforts to integrate data ethics more systematically into university teaching, including work with researchers at LMU Munich. This focus feeds directly into ASSURED’s aim to promote the ethical use of sensitive data.
Within the project, Frederic is primarily involved in developing and reviewing training modules. These modules cover key topics such as data ethics, legal frameworks for data protection, and statistical disclosure control. They are designed to support researchers working with sensitive data, particularly in secure environments such as Trusted Research Environments.
The first of these modules is already in use, providing guidance for researchers accessing data through the Secure Data Center at GESIS. Further core modules are currently in development and will expand the training offering in the near future.
What motivates Frederic most is the potential impact of this work. While researchers generally care about ethical and legal considerations, these topics are often addressed only in the context of specific projects. ASSURED aims to change that by offering structured, accessible training that researchers can use proactively.
Looking ahead, Frederic is particularly interested in seeing the training adopted more widely, across research data centers and beyond. The longer-term vision is to make high-quality training in secure data use easier to access, more consistent across institutions, and ultimately more embedded in everyday research practice.
Registration is now OPEN for our essential workshop at the International Data Curation Conference (IDCC) 2026! The ASSURED Project is developing an accreditation scheme for handling sensitive research data. This workshop is your opportunity to gain critical expertise.
What You Will Learn: • Safe Outputs: Explore the issues emerging from sensitive data results and learn the principles for producing non-disclosive, safe outputs. • Key Techniques: Focus on methods like Statistical Disclosure Control (SDC) to minimise harm and protect privacy. • Interactive Training: This is a highly interactive-focused session, encouraging rich discussion among researchers and data professionals.
Who Should Attend? This training is important for: • Researchers working with sensitive data. • Data Curators and professionals involved in data access. • Anyone responsible for ethical data release.
Elevate your professional standards. Secure your spot and become more confident in working with sensitive data.
👉 Register Today for the Workshop at IDCC 2026: https://t1p.de/8ltfu
Learn more and apply here: https://lnkd.in/ejpuSYnv
Are you passionate about the intersection of FAIR data, open science, and researcher education? Join the Data Services for the Social Sciences department, where you'll play a vital role in ensuring safe, reproducible research.
This role is centered on our GESIS Secure Data Center and the exciting, multi-partner ASSURED project. You will be key in developing a new Safe Researcher Training program both in Germany and internationally.
Your Impact Will Include:
• Lead the coordination and communication for the multi-consortium ASSURED project.
• Design and continuously improve digital learning materials (video tutorials, interactive exercises) in spatial transcriptomics data processing.
• Contribute to high-impact research activities on data governance, privacy, and secure data infrastructures.
• Provide essential support for the Secure Data Center, including conducting statistical disclosure reviews.
What We Are Looking For:
• A completed Master’s degree and a completed or in-progress Ph.D. 🎓
• Proven experience working in Trusted Research Environments (TREs) or with sensitive data.
• Strong command of quantitative methods and statistical programs like Python, R, and Stata.
We offer an international, interdisciplinary environment with flexible working hours, mobile working options, and excellent benefits, including subsidies for childcare.
Ready to shape the future of secure social science research?
Learn more and apply here: https://lnkd.in/ejpuSYnv
We are currently looking for someone to join the ASSURED team for 3 years to develop and deliver training to researchers and data professionals working with sensitive data. We're an international team, spread across multiple sites, although this role sits within the Secure Data Center at GESIS Cologne. If you want to work in a small but dynamic team and play your part in the exciting development work here at ASSURED and GESIS, then please get in touch!
The ASSURED team had an amazing time at the #EOSCSymposium2024 in Berlin! We spent three days discussing FAIR sensitive data and training opportunities. Presenting our poster was a highlight. Let´s foster FAIRness and trust in research and researchers. #OpenScience #FAIRData #SensitiveData #SafeP...