Getting Started

If you don't know where to start, here are 10 easy steps, that you can take towards a more transparent and reproducible research practice. Every step will add a little more scientific value to your research.

1. Create an account on OSF (http://osf.io/)
2. Upload the material for an existing study (questionnaires, maybe reproducible analysis scripts) to an OSF project.
3. Add an open license to all of your figures (so that you can reuse them in later publications, blog posts, or presentations: „Figure available under a CC-BY4.0 license at osf.io/XXXX.“. For details, see this blog post by Malte Elson.
4. For the next project: Change the consent forms in a way that open data would be possible for that project (see https://osf.io/mgwk8/wiki/Consent%20form%20templates%20for%20open%20data/).
5. Sign the PRO initiative and expect openness (or a justification why not) if you review another paper (https://opennessinitiative.org/)
6. For the next data analysis: Practice to create scripts for reproducible data analysis (e.g., SPSS syntax, R scripts). All analytic steps that lead from raw data to the final results should be reproducible.
7. Let a master student preregister his/her thesis. Can be either a „local preregisteration“, or a proper preregistration at OSF or at https://aspredicted.org/. See this workshop material for how to do a preregistration: https://osf.io/yd487/https://osf.io/mx7yp/
8. Do you own first preregistration: https://cos.io/prereg/
9. Publish your first open data set: Ensure anonymity, provide a codebook. See here for details: http://econtent.hogrefe.com/doi/pdf/10.1026/0033-3042/a000341
10. Team up with colleagues and establish a local open science initiative (enter your name and affiliation in this list and see other colleagues that want to engage in a local initiative)