Note 2nd October 2023: This Special Collection in the Data & Policy Journal is now also running as a Special Track at the Data for Policy Conference 2024. The Conference takes place at Imperial College London on 9-11 July 2024 (see details of the track here). We encourage authors to consider submitting their paper to the Conference but it is not a requirement to do so. The submission deadline has been extended to 27th November 2024. See the timetable section below.
Introduction
Migration is a complex and diverse phenomenon, brought about and influenced by various different factors. Across the world, it has become an increasingly important issue that could yield significant opportunities and challenges for countries of origin, transit, and destination. Migration can benefit the actors involved and anticipatory methods provide a new and promising way of addressing the field’s uncertainty. Anticipatory methods include techniques such as early warning systems, nowcasting, forecasting, horizon scanning, Delphi methods, backcasting, and others. Increasingly, they prove promising for researchers, policymakers, and practitioners to address the challenges of migration and inform forward-looking policy actions.
For instance, environmental and political crises spurring human mobility, improved mobility driven by ‘smart’ cities, and a new (remote) future of work are some of the new opportunities to collect novel and innovative data on human mobility. Anticipatory tools across forecasting and foresight categories could leverage this data to better anticipate trends in migration and give momentum for including data-driven insight in the decision-making processes in the field.
To explore and consolidate the state-of-the-art potential of such anticipatory methods, the Data & Policy journal is calling for contributions for a special collection of papers edited by the Big Data for Migration Alliance centered on the theme of ‘Anticipating Migration for Policymaking: Forecasting, Foresight, and Other Forward-Looking Methods To Inform Migration Policy'.
This special collection seeks to understand the ways in which new data sources, technologies, and anticipatory techniques can help signal emerging migration trends. We aim to understand the ways in which anticipatory techniques can be leveraged by decision-makers and to implement necessary legal and regulatory considerations to protect the human and data rights of migrants on the way.
The papers will provide a comprehensive, multidisciplinary, and application-focused approach to the use and re-use of data and anticipatory methods for migration research and policymaking. They will offer insights, practical tools, and recommendations for policymakers, practitioners, and researchers working in this field to improve their knowledge and application of data-driven techniques to migration policy.
Policy Significance of this Collection
Migrants are a diverse and continuously changing pool of people. Meeting their needs requires a greater understanding of who they are, where they come from, where they are going, and why they are on the move. A better understanding of how anticipatory methods can utilize data, data tools, and modeling can help answer these questions and proactively improve the evaluation, monitoring, and governance frameworks around migration.
Key Themes
This special collection is soliciting papers around the following topics:
- Advances in the use of forecasting models to anticipate different types of migration, specifically labor migration and mixed migration, with a focus on both traditional statistical methods, as well as machine learning and artificial intelligence ones.
- Role of foresight techniques to develop possible migration scenarios and public policies.
- Integration of quantitative and qualitative information in formulating forecasts for labor and mixed migration.
- Use of non-traditional data to assess migration patterns between countries of origin and countries of destination.
- Case studies on the development, deployment, and use of anticipatory methods, and their results
- Ethical and human rights-respecting collection, analysis, and use of data by anticipatory methods
- Resource, capacity, and organizational needs for effectively using anticipatory methods for migration policy
- Linking results from anticipatory methods to policy actions
- Integration of anticipatory methodologies across the migration policy cycle
Timeline
The submission deadline for full papers is:
- 27 November 2023
Authors should submit using the Data & Policy ScholarOne site and use the ‘Anticipatory Methods in Migration’ special collection option when prompted in their submission.
Data for Policy Conference
The Data for Policy Conference is the premier Conference for the data science - governance interface. The 2024 Data for Policy Conference takes place at Imperial College London, 9-11 July 2024. This Special Collection is also running as a Special Track at the Conference Authors have the option of submitting their paper for the Conference but are not required to do so.
The Conference and Journal have an integrated review process. If you wish to submit for both you should do so by the deadline (27th Nov) via the Data & Policy ScholarOne site. Use the Data for Policy Proceedings category and indicate the submission is for Data for Policy 2024 as well as the ‘Anticipatory Methods in Migration’ special collection, when prompted.
Prior to submission, authors should familiarize themselves with the Instructions for Authors. For submissions, feel free to use either the LaTeX or Word templates. Note also that we have a template in Overleaf, a cloud-based, which has collaborative features and enables authors to submit directly into the Data & Policy system without having to re-upload files.
Note also that Data & Policy publishes the following types of articles, which authors will be prompted to select from on submission:
- Research articles that use rigorous methods that demonstrate how data science can inform or impact policy by, for example, improving situation analysis, predictions, public service design, and/or the legitimacy and/or effectiveness of policy making. Published research articles are typically reviewed by three peer reviewers: two assessing the academic or methodological rigor of the paper; and one providing an interdisciplinary or policy-specific perspective.
- Commentaries are shorter articles that discuss and/or problematize an issue relevant to the Data & Policy scope. Commentaries are typically reviewed by two peer reviewers.
- Translational papers are contributions that show how data science principles, techniques, and technologies are being used in practice in organizational settings to improve policy outcomes. They may present original findings but are less embedded in the scholarly literature as research articles. They are typically reviewed by two peer reviewers, who assess the rigor and policy significance of the paper.
- Data papers that provide a structured description of an openly available dataset with the aim of encouraging its re-use for further research.
Data & Policy strongly encourages authors to make replication data and code available in an open repository, where this is possible (see the research transparency policy). All authors must provide a Data Availability Statement in their article that explains where the replication material resides, if it is available, and if not, the reason why it cannot be made accessible. Authors who link to replication materials will be awarded Open Data and/or Open Materials badges that display on the published article.
About the Editors
This special collection is edited by members of the Big Data for Migration Alliance, an initiative led by the IOM’s Global Migration Data Analysis Centre (IOM-GMDAC), the European Commission’s Knowledge Centre on Migration and Demography (KCMD), and The GovLab at New York University. As the first-ever dedicated network of stakeholders seeking to facilitate responsible data innovation and collaboration to improve the evidence base on migration and human mobility, the BD4M looks to accelerate the responsible and ethical use of novel data sources and methodologies—such as social media, mobile phone data, satellite imagery, and artificial intelligence—to support migration-related programming and policy on the global, national, and local levels.
The BD4M members editing this special collection include:
- Martina Belmonte, Policy Analyst at the Joint Research Centre of the European Commission, Knowledge Centre on Migration and Demography (KCMD) Unit.
- Matteo Fontana, Department of Computer Science, Royal Holloway, University of London
- Damien Jusselme, Head of the Data Science and Analytics Unit at the International Organization for Migration (IOM), Global Migration Data Analysis Center (GMDAC).
- Sara Marcucci, Research Fellow at TheGovLab
- Alina Menocal Peters, Project Analyst at the International Organization for Migration Global Migration Data Analysis Center (GMDAC).
- Umberto Minora, Data Scientist at the Joint Research Centre of the European Commission, in the Knowledge Centre on Migration and Demography (KCMD) Unit
- Anna Rosinska, Policy Analyst at the Joint Research Centre of the European Commission, in the Knowledge Centre on Migration and Demography (KCMD) Unit
- Stefaan Verhulst, Co-Founder and Chief Research and Development Officer of The GovLab, Professor at the NYU Center for Urban Science and also Data & Policy Editor-in-Chief.
About Data & Policy
Data & Policy is a peer-reviewed open access journal from Cambridge University Press that explores the interface of data science and governance. The journal aims to promote a new theory of policy-data interactions by publishing work that considers systems of policy and data and how they relate to each other. This Medium page is the blog for the journal.
About the BD4M
The Big Data for Migration Alliance (BD4M) is a multisectoral initiative led by the IOM’s Global Migration Data Analysis Centre (IOM-GMDAC), the European Commission’s Knowledge Centre on Migration and Demography (KCMD), and The GovLab at New York University. Since 2019, the BD4M has investigated how data, data tools, and data theories play a role in internal and cross-border human mobility. This includes a 100 Questions domain to identify the most pressing migration questions that data can help answer, a studio series on how data collaboratives can improve understanding and policy action for migration flows in West Africa, and a studio series investigating the parameters of a new concept of digital self-determination for migrants, as well as a plethora of cutting-edge research on the intersection of data innovation and migration issues.
Learn more about the BD4M at https://data4migration.org.