Resources
Contents
Resources¶
For additional resources like videos and reference papers on reproducibility, see the Further Reading and Additional Material sections.
What to Learn Next?¶
Open Research would be a good chapter to read next. If you want to start learning hands-on practices, we recommend reading the Version Control chapter next.
Further Reading¶
Baker, M. (2016). 1,500 scientists lift the lid on reproducibility. Nature, 533(7604), 452–454. https://doi.org/10.1038/533452a
Barba, L. (2017): Barba-group Reproducibility Syllabus. figshare. Paper. https://doi.org/10.6084/m9.figshare.4879928.v1
Piwowar, H. A., & Vision, T. J. (2013). Data reuse and the open data citation advantage. PeerJ, 1, e175. https://doi.org/10.7717/peerj.175
Whitaker, Kirstie (2018): Barriers to reproducible research (and how to overcome them). figshare. Paper. https://doi.org/10.6084/m9.figshare.7140050.v2
Additional Material¶
Useful Links¶
Reproducibility¶
Markowetz, F. (2018). 5 selfish reasons to work reproducibly. Slides available at https://osf.io/a8wq4/. Recording from a talk at Data Stewardship TU Delft in 2019. https://youtu.be/yVT07Sukv9Q.
Leipzig, J (2020). Awesome Reproducible Research: A curated list of reproducible research case studies, projects, tutorials, and media. Github repo. https://github.com/leipzig/awesome-reproducible-research
Data Science¶
Data science: A guide for society. Ask for Evidence. (2019). Retrieved October 26, 2021, from https://askforevidence.org/articles/data-science-a-guide-for-society.
Riley, E. (2019). Data Science Guide for Society. London; senseaboutscience.org.
The Open Data Institute. (2019). Knowledge & opinion. The ODI. Retrieved October 26, 2021, from https://theodi.org/article/data-ethics-canvas.