Dataset of Multi-Aspect Integrated Migration Indicators

Abstract

Nowadays, new branches of research are proposing the use of non-traditional data sources for the study of migration trends in order to find an original methodology to answer open questions about cross-border human mobility. New knowledge extracted from these data must be validated using traditional data, which are however distributed across different sources and difficult to integrate. In this context we present the Multi-aspect Integrated Migration Indicators (MIMI) dataset, a new dataset of migration indicators (flows and stocks) and possible migration drivers (cultural, economic, demographic and geographic indicators). This was obtained through acquisition, transformation and integration of disparate traditional datasets together with social network data from Facebook (Social Connectedness Index). This article describes the process of gathering, embedding and merging traditional and novel variables, resulting in this new multidisciplinary dataset that we believe could significantly contribute to nowcast/forecast bilateral migration trends and migration drivers.

Fundings

This work is supported by the European Union—Horizon 2020 Program through the project “HumMingBird—Enhanced migration measures from a multidimensional perspective”, Grant Agreement n.870661, and under the scheme “INFRAIA-01-2018-2019—Integrating Activities for Advanced Communities”, Grant Agreement n.871042, “SoBigData++: European Integrated Infrastructure for Social Mining and Big Data Analytics”.

Data Availability Statement

The MIMI dataset v2.0 presented in this study is openly available on Zenodo at the following link: https://doi.org/10.5281/zenodo.6493325.