A General Temporal Data Model and the Structured Population Event History Register

Samuel J. Clark, University of Washington

Multi-site longitudinal investigations including large scale vaccine and behavioral intervention trials are becoming more common, making it an urgent matter to develop a standard temporal framework to guide the storage and manipulation of complex temporal data describing the histories of people (and households and other aggregations of people) living in multiple populations. This work begins to address this challenge by presenting 1) an abstract temporal data model that can represent an arbitrary range of inter-related temporal trajectories – the General Temporal Data Model or GTDM, 2) a relational database implementation of the GTDM that is able to store an arbitrary range of inter-related temporal trajectories with a single static relational schema – the Structured Population Event History Register (SPEHR), and 3) a relational database schema based on SPEHR that can store the contents of many SPHER-based databases allowing data from different longitudinal projects to be easily merged and managed together.