The ideal situation from the research perspective is the free sharing of data.[1] Since privacy for research participants is a priority, though, various proposals for protecting participants have been made for different purposes.[1] Replacing the real data with synthetic data allows the researchers to show data which gives a conclusion equivalent to the one drawn by the researchers, but the data may have problems such as being unfit for repurposing for other research.[1] Other strategies include "noise addition" by making random value changes or "data swapping" by exchanging values across entries.[1][2] Still another approach is to separate the identifiable variables in the data from the rest, aggregate the identifiable variables and reattach them with the rest of the data. This principle has been used successfully in creating maps of diabetes in Australia [3] and the United Kingdom [4] using confidential General Practice clinic data.