Data provenance tracking and reporting in a high-security digital research environment. - Bernhard Scheliga; Milan Markovic; Helen Rowlands; Artur Wozniak; Katie Wilde; Jessica Butler (International Journal of Population Data Science, 2022)
Objective To protect privacy, routinely-collected data are processed and anonymised by third parties before being used for research. However, the methods used to do this are rarely shared, leaving the resulting research difficult to evaluate and liable to undetected errors. Here, we present a provenance-based approach for documenting and auditing such methods.