+1 Recommend
3 collections

      UCL Press journals including UCL Open Environment have now moved website.

      You will now find the journal, all publications, reviews and submission information at https://journals.uclpress.co.uk/ucloe


      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Key opportunities and challenges for the use of big data in migration research and policy

      This is not the latest version for this article. If you want to read the latest version, click here.


            Migration is one of the defining issues of the 21st century. Better data is required to improve understanding about how and why people are moving, target interventions and support evidence-based migration policy. Big data, defined as large, complex data from diverse sources, has been proposed as a solution to help address current gaps in knowledge. The authors participated in a workshop held in London, UK, in July 2019, that brought together experts from the UN, humanitarian NGOs, policy and academia to develop a better understanding of how big data could be used for migration research and policy. We identified six key areas regarding the application of big data in migration research and policy: accessing and utilising data; integrating data sources and knowledge; understanding environmental drivers of migration; improving healthcare access for migrant populations; ethical and security concerns; and addressing political narratives. We advocate the need for increased cross-disciplinary collaborations to advance the use of big data in migration research whilst safeguarding vulnerable migrant communities.


            Author and article information

            UCL Open: Environment Preprint
            UCL Press
            18 June 2020
            [1 ] Institute for Global Health, University College London, London, UK; Centre for Biodiversity and Environment Research, Department of Genetics, Evolution and Environment, University College London, London, UK
            [2 ] Institute for Global Health, University College London, London, UK; Institute of Environment, Health and Societies, Brunel University, London, UK
            [3 ] Centre of Public Health Data Science, Institute of Health Informatics, University College London, London, UK
            [4 ] United Nations’ Displacement Tracking Matrix, International Organization for Migration, International Organization for Migration, Juba, South Sudan
            [5 ] CU Population Center, Institute of Behavioral Science, University of Colorado Boulder Campus, Boulder, CO, USA; Faculty of Environmental Sciences, Technische Universität Dresden, Dresden, Germany
            [6 ] Health Management BD Foundation, Sector 6, Uttara, Dhaka, Bangladesh; Adjunct Faculty, Department of Public Health, North South University, Dhaka, Bangladesh
            [7 ] Department of Information Studies, University College London, London, UK
            [8 ] GMV Innovating Solutions Ltd, HQ Building, Thomson Avenue, Harwell Campus, Didcot, UK
            [9 ] WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK
            [10 ] United Nations’ Displacement Tracking Matrix, International Organization for Migration, United Nations, London, UK
            Author information

            This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY) 4.0 https://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, distribution and reproduction in any medium, provided the original author and source are credited.

            : 18 June 2020
            UCL Grand Challenges, UCL, London, UK 506002-100-156425

            Data sharing not applicable to this article as no datasets were generated or analysed during the current study.
            Earth & Environmental sciences,Computer science,Environmental change,Social & Behavioral Sciences,Ethics,Data analysis,Public health
            climate change,humanitarian,migration,Public policymaking, data security,Environmental justice and inequality/inequity,policy,Big data,displacement,Health and climate change,environment,Environmental modelling,health,Statistics,cross-disciplinary research


            Date: 12 July 2021

            Handling Editor: Dr Ben Milligan and Prof Dan Osborn

            Editorial decision: Request revision. The Handling Editor requested revisions; the article has been returned to the authors to make this revision.

            Additional comments by teh Handling Editor: Please take into particular consideration:

            • The broad thrust of the remarks of both reviewers who are calling for more critical remarks in a number of areas especially with respect some of the points the paper itself makes about the nature of the data that is thus far available.
            • Issues around framing and rational of the work need some further attention
            • A clear statement is probably needed as to the limited circumstances in which big data can help at present
            • Something further might be added on a range of moral or ethical issues linked to migrants and big data and who can access it or use it
            • A little more would be welcomed on the opportunities that would be provided if big data could be used more
            • Table 1 and analysis associated with it might warrant some further attention
            2021-09-10 13:37 UTC

            Decision Date: 19/06/2020

            Handling Editor: Ben Milligan

            This article is a preprint article and has not been peer-reviewed. It is under consideration following submission to UCL Open: Environment Preprint for open peer review.

            2020-09-17 13:09 UTC

            Comment on this article