Database with cause-effect pairs

This is a growing database with different data for testing causal detection algorithms. The goal here is to distinguish between cause and effect. We searched for data sets with known ground truth. However, we do not guarantee that all provided ground truths are correct.
The datafiles are .txt-files and contain two variables, one is the cause and the other the effect. For every example there exists a description file
where you can find the ground truth and how the data was derived.
Note that not always the first column is the cause and the second the effect. This is indicated in a meta-data file. Please look at README for further explanations. We also suggest a weighting factor for some pairs which a very similar if you want to calculate the overall performance.
To get all data files at once download all data as a zip file.
Note: pair0001 - pair0041 were taken from the UCI Machine Learning Repository, so if you use these data sets please refer to their
webpage. Here you will find their
citation policy.
If you have any comments, questions or suggestions for additional data sets, please contact Jakob Zscheischler