"Inconsistent representation of the clinical context is among the biggest barriers to broad-scale adoption of precision medicine [and] a consistent approach to the digital representation of clinical features is urgently required.” (Charles Gutteridge, CCIO Barts Hospital, London). The interpretation of health data records (and other complex data) is complicated, with inconsistent recording, interpretation and selection. This may mean that error and bias enters research studies using health records or that error and bias enters the way in which research findings are interpreted. This project aims to conduct methodological work to alleviate the risks of these issues and to increase the possibilities harmonised and repeatable research across different data resources. ALSPAC data can help inform these investigations given its range of complex data collected directly from individuals, from linked records and potentially from 'digital footprint' sources (such as sensors/social media).