In 2019, the International Organization for Migration (IOM) estimated that the number of migrants worldwide had reached 272 million, a figure that has tripled since 1970. Though most of these migrants fled their countries searching for better job opportunities, about 26 million people have been driven away from their homes by armed conflict, violence and climate change. In the hope of shedding light on the issue and calling for policy action, in 2000 the General Assembly of the United Nations proclaimed December 18 as International Migration Day. This global scenario brings with it many hardships and opportunities for migrants, as well as for the receiving countries.

For those seeking to understand more about the phenomenon and inform policymaking, the greatest challenge is quantifying it at a granular level and in a comprehensive manner. In that sense, the Pew Research Center has stated that the issue with migration data is first that by definition migrants are on the move, making it hard to know where they are heading or where they came from. Moreover, because they don’t always use legal means to enter a country, it is difficult to obtain registries of their activity. Finally, given the lack of a shared understanding of who a migrant is, data collection and comparability between datasets become highly complex matters.

Withstanding the hard work many national governments and international institutions have conducted to gather and assemble migration data using traditional methods (e.g. national population census, surveys or administrative records), a large gap in the quantity and quality of available data still remains. According to the IOM, the problem stems from lack of updated information and the significant financial cost attached to these methods. In recent years, Big Data has stepped in to try and fill the gap that traditional sources have left in mapping and analyzing the dynamics of national and international migration. Initiatives such as the Joint Data Center, created by the UNHCR and the World Bank, have dived into the use of different types of Big Data to monitor migration patterns and migrants’ locations around the world. In addition, different research papers (see Facebook Data Science team 2013, Clements et. al 2010, WIlliams and Ralph 2013, State, Weber and Zagheni 2020), have looked into how the use of Big Data sources — IP geo locations, Google search queries, and Flickr geotags, etc. — can contribute to gathering sociodemographic information, as well as the real-time location of migrants. 

The main argument for leveraging Big Data for migration is that these sources can inform the response of government and global institutions to increasing migration influxes, and therefore help in the development of adequate public policies that take into account migrants’ needs from a human rights standpoint. With that in mind, this edition of Links We Like addresses the topic of Big Data for migration and explores some of the key challenges, limitations and opportunities brought forward by this developing area of work.