Höhn, A. , Rice, H., Colasanti, R., Heppenstall, A. , Elsenbroich, C. , Meier, P. and Lomax, N. (2026) COMPASS - Combinatorial Optimisation for Microdata Population Assembly and Spatial Synthesis. [Data Collection]
Collection description
Simulation models, such as agent-based or microsimulation models capturing urban contexts, increasingly draw on spatially explicit, attribute-rich synthetic population datasets as real-world data inputs. Despite their growing relevance, the creation of such datasets via simulated annealing still faces significant limitations. Addressing key limitations, we present the open-source software package Combinatorial Optimisation for Microdata Population Assembly and Spatial Synthesis (COMPASS). The algorithm implemented in COMPASS enables; aggregate-level representativeness at different levels of counts (e.g., households and individuals); the processing of nested input data (e.g., retaining survey household and kinship structures); and systematic monitoring of uncertainty arising at creation stage. We provide COMPASS as a compiled multi-platform software package, suitable for reproducible workflows via R and Python. This paper introduces COMPASS and illustrates one potential workflow using open access data created to reflect an artificial population – transferable to many national contexts.
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| College / School: | College of Medical Veterinary and Life Sciences > School of Health and Wellbeing > Public Health College of Social Sciences > School of Social and Political Sciences > Urban Studies & Social Policy |
| Date Deposited: | 28 Sep 2026 08:50 |
| URI: | https://researchdata.gla.ac.uk/id/eprint/2433 |
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