1 Introduction  
2 Methodology of the survey process  
2.1 Strategy for collecting datasets  
2.2 Bayesian network  
2.3 Fairness metrics  
3 Datasets for fairness  
3.1 Financial datasets  
3.2 Criminological datasets  
3.3 Healthcare and social datasets  
3.4 Educational datasets  
4 Experimental evaluation  
4.1 Evaluation setup  
4.2 Experimental results  
5 Open issues on datasets for fairness-aware ML  
5.1 Adult reconstruction and ACS PUMS datasets  
5.2 Synthetic datasets  
5.3 Sequential datasets  
6 Conclusion and outlook