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Research Principles is a forum designed to facilitate cooperative research projects by offering a means through which researchers can, with minimal administrative burden: share projects, recruit additional participating laboratories, and expand the use of collected data. Whereas was developed initially to facilitate a specific research project funded by the German Research Foundation (DFG), this platform supports additional research projects that adhere with the cooperative principles upheld by this network. Distinct from a general crowdsourcing infrastructure for various research plans (see Psychological Science Accelerator), brings together smaller groups of researchers to join forces for specific projects.

This is how it works: Grounded in the principles of cooperative forking path analysis (cFPA, Wacker 2018) groups of five or more researchers from different labs share the load of data collection for testing a set of registered hypotheses using an agreed-upon design. Further, the collaborative group of researchers discuss and systematically explore analysis options for the data to minimize undisclosed flexibility (researcher degrees of freedom, garden of forking paths) that leads to an increased likelihood of false-positive results (Simmons, Nelson & Simonsohn, 2011).

Following registration of a project on, a public abstract of the project is posted along with a list of members who have already agreed to contribute to data collection. After joining and accepting its ground rules, researchers may apply for membership of a specific project wherein they will contribute regularly to the joint data collection effort and subsequent cooperative data analysis. Members of may also request data from completed projects for additional analyses not previously registered. Both the registration of additional objectives/hypotheses by project members and data requests by other researchers are discussed among the extant project members in an open peer-review on

It is our hope that, by reducing undisclosed researcher flexibility in data analysis, promoting increased statistical power, and facilitating open expert discussions of hypotheses and analysis options, and the principles of cFPA will be instrumental in improving (psychological) science.

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