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

    Key opportunities and challenges for the use of big data in migration research and policyCrossref
    Timely commentary on how to address knowledge gaps on who moves, where to/from, and why
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        Rated 4.5 of 5.
    Level of importance:
        Rated 4 of 5.
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        Rated 4 of 5.
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        Rated 5 of 5.
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        Rated 5 of 5.
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    Key opportunities and challenges for the use of big data in migration research and policy

    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.

      Review information

      This work has been published open access under Creative Commons Attribution License CC BY 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Conditions, terms of use and publishing policy can be found at www.scienceopen.com.

      migration,humanitarian,Public policymaking,Environmental modelling,Statistics,cross-disciplinary research,health,climate change,environment, data security,Environmental justice and inequality/inequity,displacement,policy,Big data,Health and climate change

      Review text

      It is not new to question how we can better understand who moves where and why. Yet the synthesised debates drawn from a cross-disciplinary workshop on the implementation of big data in migration research do act as a platform for new work in this area.  The explosion of big data and wider developments in computer science mean, increasingly, policy makers, researchers and businesses are redirecting research and action towards the opportunities afford by such data. While it is easy to be swayed by the promise of the sort of temporal and spatial granularity big data can offer, in practice there are significant challenges. This paper clearly summarises these challenges, simultaneously touching on the opportunities that may arise if the challenges are addressed. The paper’s impact might be strengthened by more depth on the latter – though this by no means undermines its value - it is a good discussion of how to create and develop future research agendas on migration with big data.

      In more detail, Table 1 usefully summarises the topics explored, giving hints to the relevant questions within. But a review of this table in relation to the discussion offered does leave space for more. Though the authors do set out to highlight opportunities for big data and migration research, the discussion would benefit from more concrete examples of how. In particular, this would strengthen the paper if seeking to sway those in the research community who may be less receptive to the potential of big data. The section on healthcare is one example where this could be addressed given its brevity: having finished that section I was not sure precisely how big data would improve migrants access to healthcare. The paper does make a strong argument as to the potential of big data in opportunities to identify vulnerable populations through immobility or non-migrations. Yet there is still room to expand and better articulate what this evidence would do, particularly when combined with more targeted research into the lived experience of such groups.

      It is welcome to see the final two topics addressing debates on ethical, privacy and security concerns, and then the role of big data in addressing political narratives. These are closely interlinked and it is perhaps in this space where more research, discussion and innovation need to emerge before big data can truly impact on migration research. The paper evidences some interesting discussion but again, could do more to outline in what ways the significant challenges identified can be overcome.

      The paper does leave you wanting more, asking ‘how’ to realise the opportunities suggested. But this is perhaps beyond the scope of a commentary on a workshop discussion. In fact, the authors insights into how to run future cross-disciplinary workshops which better account for the theoretical, language and knowledge-sharing differences between disciplines are perhaps the next steps in the progression of the ideas summarised in this paper. It is here where cross-disciplinary discussion will work out how, and the authors could have made more of this.



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