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

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.

As already indicated by the first reviewer, this paper provides a very readable and accessible contribution on the question of using big data in the field of migration research. It brings together insights from a very interdisciplinary and indeed cross sector (academic and non-academic) set of actors in debates surrounding migration and/or new data sources. I find the presentation of debates useful and illuminating in terms of how such a diverse set of actors approach and engage with these very topical questions. I can recommend the paper but think that it can be made even stronger by more clearly laying out its rational, by thinking about framing the discussion in terms of open questions and challenges (instead of just challenges) and by engaging at least somewhat with a more nuanced appraisal of the difficulties that are inherent in the very broad definition of big data that the authors chose – where engaging with these points would also offer opportunities to engage with more recent debates on very important challenges that the big data hubris brings with it.

Let me address each point in turn. The authors in their introduction note that they hope that the paper will “to assist migration experts in deciding whether the use of big data is appropriate for their work”. However, I feel that the paper as it progresses does not leave sufficient room to indeed consider that in a number of scenarios (particular) big data applications may simply not be the appropriate approach. I feel that the paper to readily embraces the tacit assumption that big data must be good for understanding migration related social, economic and health phenomena. Looking at the references included to make this claim, it is clear that this assumption is very much directly adoped from reports driven and bound to by policy agendas (such as those set by the global compact for migration) that are not critically questioned. However, the paper itself clearly demonstrates that the assumption that bigger is better might not always hold given a gambit of unresolved questions about the quality of the data and how it is being analysed. I feel that the paper would benefit from more clearly highlighting that often times if the potential of big data is referred to that potential has for the most part not been met/demonstrated because of questions that remain open and concrete challenges that may or may not be overcome.

I feel that for that reason it might be useful to make a distinction between what we don’t know in technical terms eg. “How do we manage fragmented data sources across varied spatial and temporal scales?” and concrete challenges that may not be possible the overcome with technical solutions like: “How do power imbalances influence the use of big data?”. The latter making ethics not just a concern of public-private partnerships in this field but very much generally important as some methods can be highly invasive and lack regulatory oversight. In this vein – I think that the paper would benefit from explicitly recognising that - just as migration is shrouded in political narratives so is big data and its assumed beneficial role in making migration legible (with tools that always keep the researcher at least one, often multiple steps, removed from those who they are studying whose actions and practices the research aims to better understand: migrants). Many of the promises of big data migration analysis can be and are critically interrogated (Eg. Is it really less costly in the larger scheme of things if a market for big data migration analytics capitalises on framing migration as risk (Taylor and Meissner 2019) and is it acceptable that refugees and other vulnerable populations on the move become the testing population for new data technologies (see Molnar 2020)?). In this sense and in line with the aim set out in the paper’s introduction to assist migration experts in making a decision, I would welcome some reflection in the discussion part not only what big data migration research might be able to help with but also what kinds of questions it simply cannot address – and I here very much already welcome that the authors note that “A key output of the workshop was a consensus that researchers and decision makers must first ask why they require additional data and whether this  is what all parties, particularly migrants, would want.”

Relatedly and to move on to my third concern, critically reflecting on how a broad definition of big data chosen to frame the article is leaving room for glossing over issues or down playing them – this is particularly evident in the potential for health care interventions section of the paper that essentially point to a big survey (cohort studies) as a way to be better prepared for migrant health needs. As Pelizza and Milan (2020) point out in light of the Covid-19 pandemic there is a dilemma between obtaining the data needed and allowing migrants to remain invisible to often punitive regulatory regimes. The opportunity outlined in that section is thus one that also comes with various challenges and some challenges that might best be mitigated with more traditional methods but that would be exasperated through methods such as social media monitoring which does not meet European data protection standards. In this light I also feel that the section on understanding environmental drivers of migration is illuminating.  It sounds as though the section is making the argument that tech can help us avoid actually engaging with the very complicated decision-making processes involved in migration – there is now much research that alerts us that it cannot. Again given some of the more critical comments in the article I am not sure that message is the intended one so it would be good to sign-post more effectively. It seems to me that there is an important difference between using satellite data to identify environmental risks and using that data to monitor and predict migration. If the researchers concern is indeed with populations vulnerable to climate events would identifying the climate risk and then engaging with the at-risk populations not be a more effective way of combining our analytical tool kit? Overall I would welcome it if the authors tried to see if the opportunities sections cloud at least in part be informed by the challenges sections.

Having presented my concerns I hope it is clear that I think the paper makes an important contribution but that I also think it would benefit from more clearly signalling to the reader that these are ongoing debates, that those debates require attention to understanding why and what data is needed for and that big data also comes with big problems. It is also important to recognise that big data analytics bring many more stakeholders to the table that may have various different motivations for why they might push big data analytics as a supposed panacea for our patchy knowledge about an extremely complex and politically charged social process: migration.

Molnar, Petra (2020): Technological testing grounds. Migration management experiments and reflections from the ground up. Refugee Law Lab and EDRi.

Pelizza, Annalisa; Milan, Stefania (2020): The dilemma of making migrants visible to COVID-19 counting. In Processing Citizenship , 4/28/2020. Available online at https://processingcitizenship.eu/the-dilemma-of-making-migrants-visible-to-covid-19-counting/, checked on 6/16/2021.

Taylor, Linnet; Meissner, Fran (2020): A Crisis of Opportunity. Market-Making, Big Data, and the Consolidation of Migration as Risk. In Antipode 52 (1), pp. 270–290. DOI: 10.1111/anti.12583.