Abstract
International migration statistics suffer from extensive gaps and shortcomings. Recently, national statistical institutions (NSIs) have started using big data to complement traditional statistics, including on migration. Although these are promising developments, we still lack answers on the extent to which NSIs are currently using big data for migration and to what extent it complements the gaps in traditional data. We gathered data by interviewing experts from 29 NSIs to investigate how big data is used for official migration statistics. We show that 15 out of 29 NSIs either used big data for migration, had a pilot project or have been involved in joint initiatives. We reveal the specific implications of big data in human migration (e.g. internal mobility, stocks, flows and mobility patterns, among others and the most common sources used to extract official statistics). Moreover, we discuss the challenges and barriers preventing NSIs from using such data. Factors deterring countries from utilising big data include limited data accessibility, an absence of legal frameworks for big data usage, ethical concerns, the possession of already high-quality data, a deficit in expertise and methodologies and a lack of perceived necessity for supplementary data or approaches. Moreover, many countries did not know which data to use and were concerned about the quality and accuracy of such data. Legal barriers were more of an issue than the ethical aspects, and overall, participating countries believe that there is a high potential for big data in the future.
Original language | English |
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Number of pages | 13 |
Journal | Big Data and Society |
Volume | 10 |
Issue number | 2 |
DOIs | |
Publication status | Published - 1 Jul 2023 |
Bibliographical note
Funding Information:The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Horizon 2020 Framework Programme (grant number 870661).
Funding Information:
The authors highly appreciate the cooperation of the National Statistical Institutions and their experts in providing the data and for their insightful input to the questionnaire. They particularly thank Andrés Felipe Copete Martínez, Diego Iturralde, Han Nicolaas, Julia Schuster, Mariana Francisca Ospina Bphórquez, Patrick Lusyne, Ruta Beinare, Tomas Rudys and Vilma Malinauskienė among others who preferred to remain anonymous for their time and outstanding support. The authors would like to thank the European Commission for their generous funding of the project which was conducted as part of the Horizon 2020 project HumMingBird. The authors are particularly grateful for the constructive and guiding comments and corrections by the reviewers and the editors of the journal.
Publisher Copyright:
© The Author(s) 2023.
Keywords
- big data for migration
- big data for official statistics
- Migration statistics
- national statistical institutions