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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, is regularly 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 United Nations (UN), humanitarian non-governmental organisations (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 around the use of big data; and addressing political narratives. We advocate the need for careful consideration of the challenges faced by the use of big data, as well as increased cross-disciplinary collaborations to advance the use of big data in migration research whilst safeguarding vulnerable migrant communities.
displacement, Public relations, Sociology and Political Science, FOS: Political science, Social Sciences, Transportation, FOS: Law, Nursing, FOS: Health sciences, migration, Environmental technology. Sanitary engineering, Data science, Impact of Climate Change on Human Migration, Big data, humanitarian, Migrations, big data, Computer security, GE1-350, data security, Key (lock), Political science, TD1-1066, Politics, health, cross-disciplinary research, Computer science, 300, Environmental sciences, Safeguarding, Operating system, climate change, Health, Medicine, Impact of Social Factors on Health Outcomes, environment, Law, policy, Research Article, Understanding Human Mobility Patterns
displacement, Public relations, Sociology and Political Science, FOS: Political science, Social Sciences, Transportation, FOS: Law, Nursing, FOS: Health sciences, migration, Environmental technology. Sanitary engineering, Data science, Impact of Climate Change on Human Migration, Big data, humanitarian, Migrations, big data, Computer security, GE1-350, data security, Key (lock), Political science, TD1-1066, Politics, health, cross-disciplinary research, Computer science, 300, Environmental sciences, Safeguarding, Operating system, climate change, Health, Medicine, Impact of Social Factors on Health Outcomes, environment, Law, policy, Research Article, Understanding Human Mobility Patterns
| citations The total number of citations received by all articles of the researcher of interest. | 9 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
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