Computational reproducibility, or the ability to reproduce research using the available data, code, and materials, makes it possible to assess the validity of, and build on existing research. The Social Science Reproduction Platform (SSRP) is an open source platform that crowdsources and catalogs attempts to assess and improve the computational reproducibility of published social science research. The SSRP is meant to be used in combination with the Guide for Accelerating Computational Reproducibility (ACRe Guide) and can be incorporated as a module in applied social science courses at both the graduate and undergraduate levels.
The SSRP was developed by the Berkeley Initiative for Transparency in the Social Sciences (BITSS) in collaboration with the American Economic Association Data Editor, and with generous support from Arnold Ventures. A full list of contributors can be found here.
How it works
Assess & Improve
Reproducers can assess and improve the computational reproducibility of published scientific claims through a four-stage process based on the ACRe Guide.
Review & Collaborate
In the Forum, reproducers will be able to review, comment on, and collaborate on reproduction attempts submitted by others.
A forthcoming Metrics Dashboard will aggregate results from reproductions to produce metrics of computational reproducibility across papers, journals, sub-disciplines, and timespans.