SynthEco: An open-source Python application for the generation of a multi-scale digital ecosystem anchored in synthetic populations

Synthetic populations (SPs) are a special kind of synthetic datasets that are statistical representations of a population at a given geo-spatial granularity, created using individual/household and aggregated census data. The SynthEco project aims to provide a platform for researchers to create a basic SP using an open-source Python package. The basic SP is then enriched by combination with (1) other datasets that capture the many dimensions of individual/household characteristics and real-world behaviors (creating what we call mosaic agents) and (2) with real-world behavioral data for spatially and/or temporally explicit characterization of the environment in which agents evolve for analytics and/or simulations combining individual and environmental characteristics. This package allows for SP creation from any census data and on different geographic granularities and jurisdictions through a simple plug-in system enabling enrichment into multiscale digital ecosystems. The use of SynthEco is illustrated in two use cases.