An organization that supplies performance data to governments, NGOs, other bodies or the public, or that holds databases of sensitive information, can strengthen trust in how it gathers and manages data by carrying out detailed reviews. These aim to raise confidence that the data others receive is correct, to make data and information more credible, and to confirm that the systems keeping data secure and private can be relied on. Reviews of this kind may be triggered by legal rules on reporting emissions or pollutants, data owed to funders about programmes, conditions in environmental permits, or worries about financial, medical or personal data. Independent people or teams, from inside or outside, should look at how data is gathered, recorded, stored, handled and used, to find where it is exposed to mistakes or unauthorised access. Accuracy also improves when those collecting data are trained, when it is clear who answers for accuracy, when people who make errors are told directly, and when quality checks compare reported figures with earlier and comparable ones.
The graph holds this control, the 0 it maps to, and the evidence behind each claim, over MCP and REST.