Wednesday 6 May 2026 – Open Access and Responsible Research
Open Access – Publishing Your Results
Instructor: Ineke Luijten
In this session, the history of scholarly publishing is briefly traced, and participants will be introduced to key Open Access models (Green, Gold, Hybrid, Bronze, and Diamond). The sessions includes a discussion on the strengths and weaknesses of traditional publishing, including issues of quality control, cost, access, and commercialization, and describe the shift away from subscription-based models. The session also covers practical aspects of open scholarly publishing, including preprints, collaborative writing and open peer review.
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Parallel Session
Open Access – Code and Models
Instructor: Karin Engström
This hands-on session introduces the essentials of Open Access for code and models, focusing on practical skills. Participants will get started with code versioning using git, learn the basics of reusable data processing pipelines, and explore how to document and share models.
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Supplementary material:
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Open Access Scholarly Books
Instructor: Helena Francke
This discussion-oriented session explores the landscape of Open Access books. Participants will bring their own experiences and questions (or just a curious mind) to a conversation about publishing opportunities, practices, benefits, and challenges. Issues that can be addressed include platforms, publishers, licenses, self-archiving, and more, with regards to both longform publishing and book chapters.
The SOM survey and the Citizen Panel
Instructors: Marcus Weissenbilder and Tilda Ekström
This session highlights key questions around data sharing related to the SOM survey and the Citizen Panel: what types of data can be made accessible, and which forms of data collection require greater caution, especially when dealing with sensitive personal data and the possibility of identifying individuals. We also discuss how these considerations can be integrated already at the planning stage of research projects, concerns particularly relevant for researchers and PhD students preparing to collect their own data.
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Parallel Session
Research with Sensitive Qualitative Data
Instructor: Arin Tham
This session centers around the many ways to pseudonymize qualitative data. General tips and commonly used techniques for pseudonymizing qualitative research data will be discussed.
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Research with Sensitive Quantitative Data
Instructor: Gustav Nilsonne
The most common way to pseudonymize quantitative data is by applying various statistical techniques. These approaches modify the dataset to make it difficult – or impossible – to identify individual research participants. This session gives a hands-on introduction to essential generalization and randomization methods, and also general tips for working with quantitative data.