Sometimes, there are good reasons to use synthetic data in research. In my case I am using data from Synthea, a program that simulated patient data including medications, names and addresses. I know that no hospital would hand me such real data, so there is no alternative. In my thesis I want to reveal specific patterns in patient records.
My idea is to test some statistical methods and neural networks to predict which disease a patient will have when he or she comes to the doctor next visit. Therefore a known statistical process in generating those patterns makes sense as I want to test some methods. I also want to infer which factors are the most important ones to predict the next disease. Therefore a mass of data is needed.
I am still not sure if using such data is useful in research. On the one hand, data protection or confidentiality in my case I would rate as positive cases using fake data, same as simulated data. As I have an ordinary private laptop it is a good idea to work with artificial datasets, as there is no need for special data security and data protection. Medical data are very sensitive and should not be stored on students' computers. Artificial data is also good for testing code and programs, as one knows what is going on under the hoods if the data generating source is documented well.
On the other hand, using faked data is considered as betraying sciences a lot of papers are retracted or removed when using faked data. Data fabrication is also listed as a scientific misconduct incident on the English Wikipedia.
What should I do?