# D4D-Senegal: The Second Mobile Phone Data for Development Challenge

arXiv: https://arxiv.org/abs/1407.4885 · HTML: https://mlsanity.com/paper/1407.4885/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 18 Jul 2014.

## Built on by (most cited first, 4 of 4)

- [Differentially Private Diffusion Models Generate Useful Synthetic Images](https://mlsanity.com/paper/2302.13861/) (2023)
- [Fairness in Federated Learning for Spatial-Temporal Applications](https://mlsanity.com/paper/2201.06598/) (2022)
- [Satellites Reveal Mobility: A Commuting Origin-destination Flow Generator for Global Cities](https://mlsanity.com/paper/2505.15870/) (2025)
- [Explainability in Practice: Estimating Electrification Rates from Mobile Phone Data in Senegal](https://mlsanity.com/paper/2211.06277/) (2022)

## Abstract (arXiv)

The D4D-Senegal challenge is an open innovation data challenge on anonymous call patterns of Orange's mobile phone users in Senegal. The goal of the challenge is to help address society development questions in novel ways by contributing to the socio-economic development and well-being of the Senegalese population. Participants to the challenge are given access to three mobile phone datasets. This paper describes the three datasets. The datasets are based on Call Detail Records (CDR) of phone calls and text exchanges between more than 9 million of Orange's customers in Senegal between January 1, 2013 to December 31, 2013. The datasets are: (1) antenna-to-antenna traffic for 1666 antennas on an hourly basis, (2) fine-grained mobility data on a rolling 2-week basis for a year with bandicoot behavioral indicators at individual level for about 300,000 randomly sampled users, (3) one year of coarse-grained mobility data at arrondissement level with bandicoot behavioral indicators at individual level for about 150,000 randomly sampled users