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Public Observatory for Integrated Population Migration Data and Modeling


OBJECTIVE: Create a data repository for population migration data and modeling for public use consisting of data that can be integrated from diverse open sources, codebooks, computational models with source code, and a tool suite to enable researchers to develop new analytic models as well as upload new data, codebooks, and computational models to support predictive and causal modeling of global population migration patterns alongside causes and consequences of population migration, as well as mitigating factors that determine those patterns. DESCRIPTION: There are no existing comprehensive tools to predictively model the impact of the increasing incidence of population migration due to environmental change and human-caused crises, which poses challenges for global security. Large-scale environmental changes such as floods, earthquakes, and droughts, can drive population migration; so to can war and regime change. Both types of events can precipitate impacts on health, crime, and sociopolitical instability as humans relocate to access critical resources. Migration impacts both in- and out-migration regions. Receiving regions for migrants experience stresses on social institutions and infrastructure (e.g., economic, healthcare, education, political systems), and can exacerbate already-present sociocultural conflicts as new cultures come into contact with the receiving culture. Out-migration regions suffer from the loss of human and social capital leading to a crippling of their social institutions and infrastructure, which are precursors to a fragile state. The net outcome is a potential for geopolitical and social conflict that poses a risk to global stability. At the same time, there are opportunities to catalyze new markets that can jump-start economic growth, generate increased cooperation across diverse cultural groups, and introduce new forms of human and social capital to a region receiving migrants. If impacts of naturally occurring environmental change and human-caused crises on migration patterns can be predicted, potential out-migration regions can mitigate the likelihood of mass exoduses of their population through proactive planning, and in-migration regions can prepare for the impact of the new migrants on their culture and infrastructure. To address this issue, scientists across academia and the private sector have begun to create new datasets and mine existing open source data to develop models to predict patterns of population migration and the causes and consequences of these patterns. These scientific efforts, however, require intensive searching for and assessment of diverse data (e.g., meterological, event, demographic, ethnographic, geospatial data) from different sources, that are structured in different ways (e.g., qualitative vs. quantitative data). Moreover, modeling the dynamic relationships between natural and human-induced change and population dynamics is challenging due to both temporal and spatial parameters, alongside human and collective decision-making that determine if/how populations will move in the face of crises. What is needed is a tool to house or link to relevant data sets and computational models to capture interdependencies between human social systems and environmental and human-induced events. Such a tool will facilitate development, validation, and replicability of predictive models of population migration under duress and improve the capacity of policymakers and decision leaders to identify potential hot-spots in advance, develop strategic plans to mitigate adverse consequences such as stress on the social infrastructure and cross-cultural conflict, and turn the population dynamics into opportunities for economic growth and cultural enrichment. The aim of this topic is to create a public open-source sustainable platform to integrate diverse data sources and predictive models of population migration resulting from crises; encourage a community of scientists, policymakers, and decision leaders to share data and models; and motivate cross-disciplinary collaboration to generate basic and applied advances to better predict, address the adverse impacts of, and optimize opportunities related to crises-induced population migration. PHASE I: Develop a prototype of a tool to integrate data, models, and analytics depicting patterns of population migration due to human-induced or environmental events, including a data preparation protocol for ingestion of time series environment or climate data and human-caused crises event data, as well as data from at least two other open sources of population, migration, demographic, or ethnographic data for proof of concept (i.e., test data pool), with at least one source of structured data and one source of unstructured data; develop the protocol for importing computational models that can be applied to an integrated subset of the test data as defined by the data preparation protocol. The data and model formats must be compatible with Department of Defense (DoD) standards to ensure interoperability with other DoD datasets. Phase 1 should also include the development of a prototype tool interface that includes computational output of analyses of data sets included in the tool as well as visualization of those analytic results. A usability test of the prototype tool with a sample of researchers should be conducted and a report issued detailing the analysis of the test. PHASE II: Expand the data pool to include at least a dozen open sources of data (both structured and unstructured) uploaded by researchers outside the performer’s team as well as data sources linked to the tool from existing open source data (e.g., census data, general social survey data, human research area files) to demonstrate the versatility of the ingestion protocol and efficiency of the modeling/analytics component of the tool. Refine the user interface to address improvements discovered in the Phase 1 usability test. Test the refined and expanded tool on a large sample of researchers, to include government scientists and analysts, as well academic and private sector researchers. (1) Develop a continuity plan to enable ongoing viability of the tool subsequent to the STTR award; the continuity plan must describe how/where the tool would reside for broad accessibility (i.e., identify a durable plan and host for the tool capable of sustaining it without additional government funding) and how it will be maintained and refreshed beyond the scope of the STTR award; (2) Generate commercialization plan to ensure continued public access to open-source databases within the tool, while providing a for-profit pathway and/or licensing plan to leverage market demand for proprietary elements of the observatory including computational models, visualization and analytic algorithms, and consulting services. PHASE III DUAL USE APPLICATIONS: Additional data capabilities and models can be added to the tool, including health data, crime/deviance data, event data (e.g., from news reports), climate and disaster data, utility data (e.g., energy use trends, transportation routes, communication networks), epidemiological models, network models, and survival models to enhance the broad applicability of the tool across sectors interested in population dynamics to increase commercialization potential. REFERENCES: An, Li (2012). Modeling human decisions in coupled human-natural system: Review of agent-based models. Ecological Modelling, 229(24), 25-36. Berhin, II, I Blasi Valduga, J Garcia, & J. Bltazzar Salgueirrinho, O de Andrade Guerra (2017). Climate change and forced migrations: An effort toward recognizing climate refugees. Geoforum, 84, 147-150. Cattaneo, C, M Bein, CJ Frolich, D Kniveton, I Martinez-Zarzoso, M Mastrorillo, K. Millock, E, Piguet, and B. Schraven (2019). Human Migration in the Era of Climate Change. Rev. of Env Econ & Policy, 13,(2), 189-206 Gopalakrishnan, S., C. E. Landry, & M. D. Smith. (2018). Climate change adaptation in coastal environments: modeling challenges for resource and environmental economists. Rev of Env Econ & Policy, 12, 48–68. Muneepeerakul, R. J Anderies (2017). Strategic behaviors and governance challenges in social-ecological systems. Earth’s Future, 865-876. Thalheimer, L., & Heslin, A. (2020). The picture from above: Using satellite imagery to overcome methodological challenges in studying environmental displacement. Oxford Monitor of Forced Migration, 8(2). Wouter Botzen, WJ, O Descheens, & M Sanders (2018). The economic impacts of natural disasters: A review of models and empirical Studies, Rev. of Env Econ & Impacts, 13(2), 167-188. KEYWORDS: environment; analysis; conflict; data archive
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