Operationalizing Data Collaboratives for Migration

Abstract

While the information challenges associated with migration are real, and limit the ability of policymakers and civil society to make effective, targeted responses, recent years have seen growing efforts on the part of governments, aid agencies and others to collect and make better use of data. It is, however, when combined with other sources of data – often collected by the private sector – that these efforts become most effective. We call such partnerships data collaboratives.

We use the term “data collaboratives” to refer to an emergent form of public–private partnership that allows for collaboration and access to data for reuse across sectors and actors. This model has now been used in a variety of sectors and geographies, ranging from accessing environment related data to accelerate disease treatments (The GovLab, n.d.a) to leveraging private bus data to improve urban planning (The GovLab, n.d.b). When designed responsibly, data collaboratives have the potential to help overcome the problem of data fragmentation and fill gaps in existing information architectures for migration, allowing policymakers and civil society organizations to drive more targeted support and policies and generate new knowledge on migrant populations across the globe.

The public value of cross-sector data collaboration in the realm of migration is starting to become apparent in diverse and ongoing cross-sector data-sharing experiments. Needless to say, much remains to be done to make these efforts more systematic. As it stands, decision makers on both the supply and demand sides of data collaboratives often lack a clear and actionable understanding of whether to establish data collaboratives, when and how – and, importantly, how to do so in a responsible manner that does not create privacy and other risks. Without a clear understanding of both the risks and rewards of accessing data across sectors, data holders are likely to remain risk averse and restrict the flow of data, thus minimizing the positive secondary usage and societal impacts of data.

To help practitioners operationalize data collaboratives to improve outcomes in the field of migration, we suggest four necessary steps to transition from a series of innovative yet ad hoc projects to a more systematic framework of action. Together, these steps provide the foundations that could allow all stakeholders – in government, civil society and the private sector – to design effective, more targeted policy interventions.

Keywords: Data, Data Collaboratives, Migration, Policy Making