Mobile Networks Data for Official Statistics

The Mobile Networks Data for Official Statistics project seeks to provide an end-to-end generic production framework for using data generated by mobile networks, which can be adapted to the different statistical needs and statistical domains through a modular approach. It produces a robust, mathematically sound solution to improving timeliness and relevance of official statistical products in order to meet a concrete need of statistical data users.

Innovation Summary

Innovation Overview

The course of action was determined in 2013 through the Scheveningen Memorandum in which European statistical system (ESS) members acknowledged the importance of Big Data for official statistics in the context of rapidly changing economic and social environments, where timely and relevant statistics are the cornerstones of any sound decision-making process. Traditional statistical production systems based on census and survey-collected data are proving to be outpaced by a growing number of underlying issues, ranging from costs, timeliness, and relevance to response burden on statistical units. Mobile network data can provide an efficient and effective data source to circumvent at least some of the issues raised by traditional methods of data collection.
The objectives of this project are:
1. To provide a robust and modular methodological and production framework which can be configured and finely tuned to the needs of any statistical office.
2. To provide proof-of-concept, experimental, statistics in the domain of social and economic statistics.

The innovative aspect is bestowed by the new, modular approach of integrating mobile phone data into the production of official statistics. This approach allows to easily change/update specific modules that are technology dependent within the proposed framework. It is one of the first end-to-end frameworks dealing with mobile phone data, starting from raw data and going up to the final statistical indicators. With access to mobile phone data being problematic, a micro-simulation software was developed to produce synthetic data sets, similar to real ones. This tool was instrumental in developing the methodological framework. All of the project's tools (methodology and IT production framework) were implemented from scratch.

Innovation Description

Innovation Development

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