Introduction

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Hi, and welcome to our blog! We hope you all enjoy our documentation of this exciting process and journey during our Dialouge in Leuven, Belguim. Our team consists of three members:

• Carson Hunter
• Ivy Jordan
• Dylan Sacks

Without further ado, here’s our project!

Our Project Description

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Migration is a natural byproduct of any human society and thus has remained and will continue to be a highly important topic for governments, politicians, and citizens alike. This often contentious topic can be very polarizing, and thus produces a wide range of emotions when discussed. Using more quantitative approaches to grasp this topic could help to reduce the contention and subjectivity behind migration. Recent years have specifically called to attention the incidence of refugee crises across the globe. As conflicts arise and citizens flee their countries, with often varying motivations, countries must now grapple with managing this influx of refugee populations. To do this, they must be given adequate time to prepare for, and thus react to changes in refugee populations or patterns. This project aims to create a software based tool to visualize and predict refugee and migration patterns. Using various datasets, our group hopes to both report on past immigration patterns and predict future trends using machine learning models. We hope that by providing an easy to use tool, we can allow important stakeholders to have a better understanding of the trends surrounding refugees and immigration. With this greater insight, our hope is that stakeholders will be able to use this quantifiable information to determine the best courses of action, ensuring the safety and wellbeing of both refugees and their populaces alike. This tool could additionally provide evidence based information to a very controversial topic, helping to create adequate justifications for the decisions that these shareholders choose to make.

Data Sources

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http://data.un.org/Data.aspx?d=UNHCR&f=indID%3aType-Ref - Table of refugees

https://data.un.org/Data.aspx?d=POP&f=tableCode:128&c=2,3,6,8,10,12,14,16,17,18&s=_countryEnglishNameOrderBy:asc,refYear:desc,areaCode:asc&v=1 - Foreign population (non-citizens) 15 years of age or over by country of citizenship, educational attainment and sex

https://www.unhcr.org/refugee-statistics/download/?url=g09Osq - refugee data finder

https://data.un.org/Data.aspx?d=POP&f=tableCode:405&c=2,3,6,8,10,12,14,15,16&s=_countryEnglishNameOrderBy:asc,refYear:desc,areaCode:asc&v=1 - Number of incoming foreign migrants by country of citizenship and sex

http://data.un.org/Data.aspx?d=POP&f=tableCode%3a403 - Outflows by purpose of going abroad and sex

https://api.unhcr.org/docs/refugee-statistics.html#api-Default-solutions - Refugee statistics API

https://icr.ethz.ch/data/epr/er/ - Ethnicity of Refugees 2021 Database

User Persona and Stories

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Immigration Focused Entities: Jackson Davies is a field officer with USCIS who has experience facing sudden surges in immigration applications, leading to delays and inefficient processing.

a) Davies will be able to allocate resources needed populations within a targeted area of the United states that faces more migration than others.

b) Davies will be able to efficinetly manage immigration applications and anticipate where an influx of groups may arise from during a time of crisis based on historical context.

c) Davies will be able to coordinate with other immigartion enities to be able to write policies and regulations on immigration based on the attributes and qualities of migration from certain countries.

Relief Groups: Kyle Medina is a data scientist for the UNHCR based in Geneva, Switzerland, who is tasked with overseeing NGO / Red Cross locations which are facing a shortage of supplies in developing countries in the Southern Hemisphere.

a) He will be able to predict migration patterns to nearby asylum seeking countries, so they can account for the amount of necessary supplies needed for a duration of time.

b) He will be able to know which regions that will be prone to an influx of refugees and know the amount of employees/volunteers needed per 1,000 refugees.

c) He will be able to enhance the efficiency of distribution flow for certain products needed by a certain group of refugees such as women vs men, and children vs elderly groups.

Urban Development Planners: Tanya Bracker is a city council member from Utica, New York, a city with a large refugee population, based on the last few years population increase, there will be budget cuts and allocations for more city resources.

a) She will be able to identify the common age demographic levels of refugees so she can know if primary and secondary schools budget allocations will be most effective.

b) She will be able to anticipate and manage the housing needs for incoming refugees by predicting which regions are likely to send more refugees, thus preventing housing shortages.

c) She will be able to plan for and improve public transportation routes and schedules to better serve areas with high refugee populations.

Major Questions

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Question 1: Where are populations likely to move during major conflicts/crises?

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This question is interesting and important to our project because it allows the critical process of immigration from countries in crisis to more stable ones to be more reliable/efficient. Answering this question would allow the stable countries that are likely to experience a sudden surge of migrants with nowhere else to go to be more prepared, allowing the process of immigration to be expedited, thus saving the lives of more immigrants.

Question 2: How many refugees are moving (and are predicted to move) to a given country?

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This question further prepares countries to be ready for immigrants, expanding from question 1. A general quantitative idea of how many people may need relocation would allow stable countries to work together to ensure that one country does not have too many refugees to handle. In other words, if the number of refugees trying to immigrate to country A is too great for country A to allow all of them, country A could communicate/agree with country B before they are overwhelmed with refugees, sending some of them there. Not only would this allow more refugees to be safely relocated, but it would likely improve the way people view migration due to the improvement in efficiency.

Question 3: How can we optimize resource allocation and strategic planning for stakeholders based on predicted refugee and migration patterns?

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This question is interesting because this data can help enhance the timeliness and effectiveness of humanitarian responses, ensuring that aid reaches those in need more quickly and efficiently during crises such as the situation arising in Gaza.

Affirmation of data collection

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From: https://icr.ethz.ch/data/epr/er/ - Ethnicity of Refugees 2021 Database

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