Counting social data and positing correlations between different sets of data is becoming increasingly sophisticated and accessible. But correlation is not the same as causation, and the best explanations of change feature rich contextual information. Projects under this pillar include historical records relating to health and data on Australian attitudes towards inclusion/exclusion. They highlight the importance of strong, trusted data and the importance of being able to interpret it accurately in explanations of change.