Detail
Event details | Reproducibility in science: How and why?
Code | Start date | End date | Location | Organisation/Contact | OT-ST-WS-07 | 31.08.-02.09.2022 (10:00-12:00; 13:00-15:00, each day) | In person, ZMT, Room 1009/1010 | 31.08.2022 | 02.09.2022 | In person, ZMT, Room 1009/1010 | Data Train data-trainprotect me ?!vw.uni-bremenprotect me ?!.de 0421-218 56788 |
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Free places | Max. participants | 0 | 15 |
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Description
The reproducibility crisis in science stems not only from historically poor data availability, but also from a lack of the context used to glean knowledge from the data. Reproducible science seeks to package the analytical context of data – software environment, data organization, analytical interdependencies, expert comments – into an operational product. This has great benefits in multiplying the impact and usefulness of your scientific work for scientists, journalists – and yourself.
Learning contents
- Why is reproducibility important in science?
- Why should I make my work reproducible?
- What does reproducible analysis mean?
- How can I rethink my workflow to be reproducible?
- Which tools help me to perform reproducible analysis?
Learning outcomes
- Conceptual and operational understanding of reproducibility
- Structuring workflows for individual or collaborative work
- Tools for reproducible workflow management and data collaboration
- Guidance towards structuring projects
Prior knowledge
- Useful for participants who (plan to) use programming in their analytical work: python, R, julia, etc
- Some basic knowledge of version control (git)
Technical requirements
- Own PC, laptop
- Internet (access to eduroam), web browser (up-to-date)
Further reading
- en.wikipedia.org/wiki/Reproducibility
- Miyakawa "No Raw Data, No Science: Another Possible Source of the Reproducibility Crisis." Molecular Brain 13, no. 1 (2020): 24. molecularbrain.biomedcentral.com/articles/10.1186/s13041-020-0552-2
- Stodden et al. "An Empirical Analysis of Journal Policy Effectiveness for Computational Reproducibility." Proceedings of the National Academy of Sciences 115, no. 11 (2018): 2584-89. www.pnas.org/doi/full/10.1073/pnas.1708290115
Program/Schedule
Wednesday, 31 August (in person, ZMT, Room 1009/1010) | 10:00-12.00 | break | 13:00-15:00 |
Thursday, 01 September (in person,ZMT, Room 1009/1010) | 10:00-12.00 | break | 13:00-15:00 |
Friday, 02 September (in person, ZMT, Room 1009/1010) | 10:00-12.00 | break | 13:00-15:00 |