Session 3 - Open Data: Challenges and Opportunties
Managing Research Tools
| Foundational | Intermediate |
|---|---|
| 1. Manage research data | |
| • Identifies sources of information, and assesses if data is trustworthy, valid, reliable and pertinent. • Uses, transforms, and analyses non-sensitive research data transparently and to legal and privacy requirements. |
• Organises data sets to be FAIR, and easily stored and retrieved in a structured environment. • Trains and empowers other team members to work with data in a structured, transparent, and accessible way. |
| 2. Promote citizen science | |
| • Understands that citizens are knowledge-holders with the ability to contribute to the research process in some areas of research. | • Is inclusive and transparent in the research process and understands how best to engage with citizens in each specific context. |
Learn
Watch the following interview with Dr. Bastian Greshake Tzovaras, Independent Researcher in participatory research, who works with Open Data and governance of Open projects.
Practice
The work of this practice exercise should take a maximum of 1 hour.
Step 1 - Identify a dataset that has relevance for your research
- This could be from a Zenodo search, the UK Biobank, an iNaturalist project, the SciLifeLab Data Repository, or other sources.
- It does not have to replace an experiment that you have planned, but could complement the data you are producing by facilitating a pilot experiment, meta-analysis, or another use.
Step 2 - Assess the metadata of this dataset
- Can you understand:
- what the purpose of the dataset is
- who collected or generated the dataset
- how and when the data were collected
- any data processing or quality assurance that occurred
- the format of the data
Step 3 - Create a one-page document evaluating if you would reuse this or generate your own data.
- You can write, draw, diagram, create a table, a slide, or a graphic to document your evaluation
- The document should evaluate:
- Would you need to generate additional data, or could you totally or partially reuse this dataset?
- Are there any concerns you would have with reusing data collected by other researchers?
- Will the data you produce be able to be reused by other researchers?
- Who decides if your data can be reused?
- Any reflections you have on data production and sustainability.
Discuss
- At the webinar, your facilitators will lead a discussion about your experience of this exercise.
- If you are facilitating, please take a look at the Facilitation Guide.
Next level
Four (optional!) exercises for Open Data
If you’re interested in deepening your expertise within Open Data, here are four additional exercises:
Watch this lecture from Lynda Kellam of the Data Rescue Project, part of the KTH Seminar Series on Democracy and Academic Freedom. Reflect on when public data should be preserved or deleted.
Read this article in Science about the UK Biobank’s data breach. How would you respond if your data was leaked?
Review the section ‘Can you trust the data?’ in this slideshow on Data Reuse given by David Rayner from the Swedish National Data Service. Did the dataset you chose fulfill the checklist requirements?
The Open Science in the Swedish Context and Intro to Data Management Practices courses are excellent SciLifeLab offerings to develop your knowledge on Open Science and Data Management. Email the course coordinator and ask to be notified when the next registration opens!
Citation
The materials from this session are available for reuse under 
Please cite this material as:
Greshake Tzovaras, B., Luijten, I. and Schroeder, K. (2026). SciLifeLab PULSE Transferrable Skills Training Session 3 - Open Data: Challenges and Opportunities. Retrieved from https://scilifelab-training.github.io/PULSE/0001/session3.html. DOI: (pending)
If you use this material, we’d love to know! Get in touch with us at pulse.training@scilifelab.se