Use of Simulation Models for the Development of a Statistical Production Framework for Mobile Network Data with the simutils Package

TL;DR

This paper introduces a simulation framework using the simutils R package to generate and analyze geospatial mobile network data for statistical development, integrating external simulation tools and real metadata validation.

Contribution

It presents a novel R package that manages external mobile network simulations, constructs geospatial data structures, and incorporates metadata validation for statistical analysis.

Findings

The simutils package enables parameterization and execution of external simulation tools.

It provides methods to build geospatial data structures from simulation output.

The package includes functionalities for metadata validation and data aggregation.

Abstract

We propose to use agent-based simulation models for the development of statistical methods in Official Statistics, especially in relation with the new digital data sources. We present a mobile network data simulator which is managed through the simutils R package which provides geospatial representations of the simulated data. While the synthetic data are produced by an external tool, our simutils package allows an R user to parameterize and run this external simulation tool, to build geospatial data structures from the simulation output or to compute several aggregates. The geospatial data structures were designed with the purpose of using them in a visualization package too. Useful simulation models require the incorporation of real metadata from mobile telecommunication networks driving us to the inclusion of functionalities allowing the user to specify and validate them. All metadata are specified using XML file whose structure are defined in corresponding XSD files. Our R package includes example data sets and we show here how validate the metadata, how to run a simulation and how build the geospatial data structures and how to compute different aggregates.