Case Studies - Data Friendly Space

The Problem

Manual Entry Wasn’t Made For 21st Century Crises
Over the past 20 years, more than 7,300 natural disasters were recorded worldwide, affecting more than 4 billion people across the globe and generating $2.97 trillion in economic losses (UNDRR). The colossal effort to manually collect, track, translate, store, verify, and share critical data in the wake of these disasters has created overwhelming, and at times, insurmountable challenges for humanitarian responders— jeopardizing accurate decision making during a crisis and hindering global ability to prevent and abate future disasters. That’s where DEEP was born.

Secondary Data Review

Protection Monitoring

Participatory Assessments

Long-Term Storage

Open Source

Risk Analysis

The Solution

Remove Collaboration Barriers, Improve Response Time, Save More Lives
DEEP is a platform built with AI in mind to centralize, accelerate, and strengthen inter-agency response to humanitarian crises at national and field levels. The free, open source tool was developed by field responders in the wake of the devastating 2015 Nepal earthquakes, and has since become a go-to resource for leading global humanitarian organizations, including UNHCR, UNICEF, UN OCHA, and the IFRC. Today, DEEP hosts the largest analysis framework repository in the international humanitarian sector, hosting more than 85,000 carefully annotated response documents and connecting more than 3,000 expert users worldwide.

Since its inception, DEEP has been used to inform more than 1,800 international humanitarian projects whose scopes are estimated to impact more than 98 million people, including USAID’s response to COVID-19, ACAPS’s response to the Rohingya crisis, and UNHCR and IFRC’s response to the Venezuela migrations crisis. More than two-thirds of individuals in areas where DEEP is utilized earn less than $5 USD per day.

DEEP & COVID-19

Partners

“As more governmental measures are adopted to reduce pressure on health services and public health risks, the impact of the pandemic is being felt by all humanitarian organisations whose staff is mostly confined at home. Non-essential field movements have all been cancelled. Needs assessments are being cancelled and regular monitoring systems interrupted. For the months to come, access to structured information in humanitarian contexts will become the exception, and most decisions will be made on the basis of remote techniques, secondary data, social media, expert judgement or journalism. The impact of movement limitations will be felt at each step of the assessment and analysis cycle.”

iMMAP

June 2020

The COVID-19 pandemic has presented unprecedented challenges to the ability of humanitarian actors to collect and analyze data in humanitarian responses around the world. In addition to worldwide stay at home orders that have constrained traditional responses, humanitarian organizations have faced five concrete challenges:

1

Data Comprehensiveness

2

Consistency and Depth

3

Analytical Value

4

Analytical Value

5

Time and Focus

To date, DEEP is active in coordinating COVID-19 responses in 14 countries across Central and Eastern Africa, the Middle East, Southeast Asia and Latin America. In the case of iMMAP, DEEP is centralizing COVID-19 response data collection among 464 humanitarian organizations spread across 6 target countries and operating alongside broader global efforts.

Through this partnership, DEEP has directly strengthened assessment and analysis capacities that continue to inform response and resource allocation for more than 41.6 million people in targeted areas.

Conflict, violence, and disasters continue to uproot millions of people from their homes every year. Never in IDMC’s history have we recorded more people internally displaced than we do today.

Alexandra Bilak

Director, IDMC

The Problem

More than 50 million people around the world are internally displaced. Forced by natural disasters and violence to flee their homes and often living in refugee-like conditions within their own country’s borders, the UNHCR has called internally displaced people “among the most vulnerable in the world.”

Each year, thousands of internal displacement crises are tracked and analyzed by the Internal Displacement Monitoring Centre (IDMC)—the world’s most definitive source of data on internal displacement. Prior to partnering with Data Friendly Space (DFS), IDMC relied on a small IT team to collect and securely store reliable, timely, and longitudinal data on millions of displaced people from over 188 countries. This limited capacity held back the international community’s ability to respond to, report on, and ultimately, reduce the risk and impact of internal displacements across the globe.

The Solution

In the digital age, data is among the greatest tools to disaster management—when managed, secured, and utilized effectively. Overwhelmed by data inputs and the complexity of their data infrastructure, IDMC turned to DFS, a trusted partner to leading international humanitarian organizations across the globe.

Since 2019, DFS has introduced multiple data management tools backed by AI to better process, store, and analyze internal displacement trends and enable faster, more robust humanitarian responses in the field. Highlights include:

DFS Solution	Result
Efficient Media Monitoring	DFS helped to replace IDMC’s manual processing with IDETECT, a tool that analyzes thousands of global news sources daily through natural language processing. With IDETECT, IDMC now automates data collection on natural disaster and armed conflict displacements and can visually present the data to partners, funders, and decision makers worldwide.
Smart Reporting	DFS carried out a complete re-development of the main IDMC web application used to collect, analyze, and report on internal displacement data around the world. HELIX, a global information management system, is now pre-populated from the IDETECT natural language processing system, resulting in: 1. Reduced manual input and increased capacity for team members 2. More accurate and comprehensive data entry DFS’s data outputs are used to create reports like IDMC’s 2020 Global Report on Internal Displacement that are a primary resource to the United Nations and humanitarian leaders around the world.
21st Century Security	DFS redesigned and deployed an entirely new infrastructure to securely store IDMC’s data from 188 countries and thousands of annual displacement events. DFS continues to provide around the clock security monitoring for IDMC’s online resources.
Seamless Integration	DFS managed the migration of data from thousands of past internal displacement events to a centralized reporting system. Upgrades are designed to increase the organization’s interoperability and dramatically reduce human error and the need for manual input.

In the face of the global coronavirus pandemic (Covid-19), internally displaced people are especially at risk. Whether they were forced to flee their homes because of conflict, violence or disasters, millions of IDPs worldwide live in densely populated areas, are unable to self-isolate, and lack access to water, sanitation and basic healthcare.

IDMC

DFS’s data management tools, including Smart Reporting (Helix) and Efficient Media Monitoring (IDETECT), were utilized to produce multiple reports on the state of internal displacement during the COVID-19 pandemic, including Internal Displacement 2020: Mid-year update. The report analyzed 14.6 million new internal displacements across 127 countries in the first 6 months of 2020, giving the humanitarian community access to geolocalized data on the key priorities of people in need for a more accurate response on the ground.

DFS also built the data processing tools to enable detailed tracking and analysis of key variables impacting internally displaced people throughout COVID-19, including the virus’ impact to health, livelihoods, housing, education, and security. Learn more about IDMC’s response to COVID-19.


Crisis context/ scope of work	COVID-19
Geographical scope	Bangladesh, Burkina Faso, DRC, Syria, Colombia, Nigeria
Project period	August 5, 2020 – July 31, 2021
Donors/partners	iMMAP, USAID
Budget	USD 1,144,762
# Leads:	10,887
# Entries:	95,361
Analysis framework used:	IMMAP/DFS Situation Analysis Framework

Problem

DFS’ solution

Since March 2020, the COVID-19 pandemic has devastated lives causing tremendous economic disruption worldwide. Those facing existing crises have felt the impacts of the pandemic most acutely. Humanitarian responders faced multiple challenges: humanitarian access was constrained activities were disruptedaid workers were unable to conduct regular monitoring and assessments to meet the growing needs of crisis-affected people Countries found themselves overwhelmed by unstructured, overlapping, or missing data. There was an emerging need among country-level humanitarian responders for timely, comprehensive, and structured data on the transmission of the virus and the humanitarian impact of COVID-19 in affected countries on sectoral and intersectoral levels.

To address this urgent need in the humanitarian community, DFS partnered with iMMAP, a partner NGO that provides information management services to humanitarian and development organizations. Together we designed and implemented a large-scale secondary data review and COVID-19 situation analysis project in six countries: Bangladesh, Burkina Faso, DRC, Syria, Colombia, and Nigeria.
Monthly situational analyses were developed for each country, reporting on the evolution of ongoing situations such as quarantine effects, protection concerns, access to essential goods and services, market prices and more, to inform decision making. In addition to the reports, country-level aid responders were provided with weekly snapshots of available information at sub-national levels, summarized visually in country-specific dashboards.
Hundreds of weekly snapshots were developed throughout the project period with DFS playing a crucial role in developing the analytical frameworks for the project and ensuring that all data (academia, news articles, social media, humanitarian reports, phone surveys, etc.) would be screened, captured, tagged, and structured in DEEP. Between September 2020 and February 2021, 74 publicly available country reports were published on the COVID-19 dashboard.

Crisis context/scope of work	COVID-19
Geographical scope	Global/Local (14 countries)
Project period	Nov 2020 – May 2021
Donors/partners	Danish Refugee Council (DRC)
Budget	338,000 USD
# Leads:	761
# Entries:	26,317
Analysis framework used:	GIMAC analytical framework

Problem

DFS’ solution

Since the beginning of the COVID-19 global pandemic, restrictions have limited the ability of humanitarian workers to collect primary data in crises-affected communities. The global humanitarian sector has relied on secondary data to analyze the pandemic’s effects on systems, impact on populations, coping capacities, operational environments, humanitarian conditions, and top-line priorities. However, local actors often lack the capacity to collate, organize, and structure data at the sectoral and intersectoral levels. This has resulted in duplications and non-comprehensive outcomes.
Humanitarian country teams need support to improve their methodological approaches and strengthen analytical rigor to comply with the standards developed under the Grand Bargain Workstream 5 in preparation for the Humanitarian Needs Overviews (HNOs) and Humanitarian Response Planning (HRPs) 2021.

The Global Information Management, Assessment, and Analysis Cell (GIMAC) was created as a multi-stakeholder initiative to coordinate, structure, collate, manage, and analyze COVID-19 related information and provide technical support to prioritized countries’ global decision making based on request. DFS provided support to selected countries, in partnership with the Danish Refugee Council, by creating structured data repositories, data exploration modules, and an assessment registry in DEEP to support the humanitarian country teams’ strategic planning (Humanitarian Needs Overviews and Humanitarian Response Plans). DEEP has been integrated into the services provided by the GIMAC, granting selected countries access to centralized data across geographical areas, affected groups, and sectors/sub-sectors, improving the accountability and transparency of collective evidence.

Crisis context/scope of work	Humanitarian Response Plan processes
Geographical scope	Global/Local – Afghanistan, Somalia, South Sudan, Sudan
Project period	July – Dec 2021 (ongoing)
Donors/partners	Danish Refugee Council (DRC)
Budget	USD 473,431
# Leads:	1,087
# Entries:	39,675
Analysis framework used:	Joint Intersectoral Analytical Framework (JIAF), GIMAC analytical framework, IMMAP/DFS SDR framework

Problem

DFS’ solution

The humanitarian sector introduced the Joint Intersectoral Analytical Framework (JIAF) in 2020 to strengthen joint analysis across all sectors for the Humanitarian Needs Overview (HNO) and Humanitarian Response Plan (HRP).
While our Global Information Management, Assessment and Analysis Cell (GIMAC) project (Nov 2020 – Apr 2021) had provided secondary data analysis support to Inter-Cluster Coordination Groups across several countries, a review identified a deficiency at the end of the project. Countries lacked the capacity to undertake qualitative analysis of secondary data to inform the Humanitarian Programme Cycle (HPC), particularly the Humanitarian Needs Overview (HNO) process.

DFS launched an HNO Country Support Project with the Danish Refugee Council (DRC) to provide secondary data analysis to support the Humanitarian Programme Cycle (HPC), including the production of HNO and joint analysis processes. Afghanistan, Somalia, South Sudan and Sudan were provided humanitarian analysis support, despite the instability brought about by government transitions in Afghanistan and South Sudan. Country Expert Groups were engaged by DFS Senior Analysts and provided secondary data review and analysis in DEEP. DFS and DRC generated first level analysis reports using an analytical framework, aligned to the JIAF framework, allowing analysts to respond to the differing timelines and capacity needs of each country. DFS provided joint analysis workshops, capacity building on DEEP, and custom analysis as requested by the Country Expert Groups. DEEP provided value to the Humanitarian Programme Cycle process, supporting the Grand Bargain workstream 5 and the JIAF‘s current guidelines to ensure better evidence-based strategic humanitarian response planning.

Crisis context/scope of work	Humanitarian assistance in urban contexts
Geographical scope	Global
Project period	January 2021 – June 2021
Donors/partners	German Red Cross (GRC)
Budget	USD 28,000
# Leads:	254
# Entries:	11,449
Analysis framework used:	Urban Response Analytical Framework

Problem

DFS’ solution

Most refugees and internally displaced people gravitate to highly populated cities, creating unique threats and vulnerabilities. The result is that urban areas are increasingly the site of humanitarian crises exacerbated by natural hazards, violence, and armed conflict.
Response frameworks for rural challenges translate poorly into urban contexts and so the humanitarian community is now adapting their response mechanisms to create more contextual responses forsome of the world’s most pressing needs. Accordingly, the German Red Cross (GRC) needed to bolster their understanding of the complexities of urban crises and specific requirements for response including processes, socio-cultural considerations, legal requirements, and the structural frameworks needed to inform priorities of the GRC in an urban context. GRC was searching for a well-structured, comprehensive, and adequately categorized information repository.

DFS structured existing reports for GRC and provided secondary data tagging and analysis in its Urban Response Analytical Framework.
The partnership categorized information from multiple documents and sources, informing GRC’s implementation/testing of innovative approaches to urban knowledge management amid conflict and non-conflict urban situations. The project also tested the appropriateness and practicability of GRC’s urban framework for managing large amounts of data.
Training and reference materials grew out of the project in an effort to standardize definitions, instructions, and examples for each pillar and sub-pillar of the GRC urban framework. This will allow for smooth updates of the project in the future.

Crisis context	10th Ebola outbreak in the Democratic Republic of Congo
Geographical scope	Democratic Republic of Congo (DRC)
Project period	July – August 2019
Donors/partners	International Federation of Red Cross (IFRC)
Budget	USD 7,000
# Leads:	236
# Entries:	3,276
Analysis framework used:	IFRC’s Analytical Framework – EVD Review

Problem

DFS’ solution

Immediately after the end of the 9th Ebola virus disease in the Democratic Republic of Congo (DRC), the Ministry of Health declared the 10th epidemic of the Ebola virus disease (EVD) in North Kivu had begun. 2018 marked the biggest Ebola outbreak in the country’s history and the second-largest ever in recorded history. The impact of the disease was exacerbated by the fact that it was taking place in an active conflict zone.
By the time the outbreak ended in June 2020, there were 3470 cases, 2287 deaths, and 1171 survivors.
To evaluate its response measures and address ongoing activities, IFRC sought to analyze information from multiple sources to evaluate the decisions taken in the crisis. The Federation needed to know if the organization had scaled its response to the crisis effectively, and positioned itself to rapidly address humanitarian needs in key Ebola-response sectors (Safe and Dignified Burials, Infection Prevention and Control, Community Engagement and Accountability including Risk Communication).

DFS helped IFRC structure information from multiple secondary documents and sources based on a comparative analysis gathered from the previous Ebola outbreak.
The project included both of DRC’s affected areas – North Kivu and Equateur province.
Tagging and secondary data analysis of information from a variety of sources including appeals, operations updates, minutes of Joint Task Forces, field assessments and reports, minutes of coordination meetings enabled IFRC to document their findings and recommendations for future actions. The organization was able to evaluate timeliness, efficiency, effectiveness, and the coordination of its response in comparison to past events. This allowed the team to confirm if the decisions taken by the Federation positioned the organization effectively, providing the right process to scale up operations, and to rapidly address humanitarian needs in key Ebola-response sectors.

Crisis context	Syrian refugee crisis
Geographical scope	Turkey
Project period	From May 2021 – May 2022 (ongoing)
Donors/partners	International Federation of Red Cross (IFRC)
Budget	USD 76,000
# Leads:	3,232
# Entries:	38,708
Analysis framework used:	IFRC’s Analytical Framework

Problem

DFS’ solution

Turkey hosts more than 4 million refugees, many of whom are from Syria and fleeing a ten-year-long conflict. More than 1.5 million of the refugees qualify for the Emergency Social Safety Net (ESSN) program, led by the International Federation of Red Cross and Red Crescent Societies (IFRC) and the Turkish Red Crescent Society, which qualifies refugees for emergency cash assistance provided by the EU.
Project success requires an understanding of the refugees’ context, consistent sectoral and inter-sectoral country-level situation analysis, and near-constant data analysis. But data and information are generally scattered across different sources of information which existing data review tools are not capable of managing efficiently. This leads to data collection challenges across geographical areas, affected groups, or sub-sectors.

By creating a comprehensive multi-year repository of structured and coded data (qualitative and quantitative) from identified sources in DEEP, DFS provides project partners access to all sectoral and inter-sectoral information. This allows them to evaluate unmet needs and analyze underlying factors categorized in an IFRC-designed analysis framework.
The result is a comprehensive understanding of the needs of refugees allowing IFRC to develop systematic review of its programmes. DFS has provided a standard level of categorization and quality control for all captured information, in line with global standards and cluster taxonomies, in an effort to reduce the risk of miscategorization.
Project activities include assessing the depth and representativeness of available data, mapping the information landscape, and rating information gaps through an improved assessment registry to support decision making in terms of prioritizing and helping create targeted needs assessments.

Crisis context	Venezuela – mixed migration
Geographical scope	Argentina, Brazil, Chile, Colombia, Costa Rica, Dominican Republic, Ecuador, El Salvador, Guatemala, Honduras, México, Nicaragua, Panamá, Perú, Trinidad and Tobago, Venezuela
Project period	July 2019 – June 2022
Donors/partners	United Nations High Commissioner for Refugees (UNHCR)
Budget	USD 250,990
# Leads:	4,684
# Entries:	42,884
Analysis framework used:	Situational Analysis UNHCR Framework

Problem

DFS’ solution

Over 5 million Venezuelan refugees and migrants live abroad, having fled violence, threats, and lack of essential supplies and services. Latin America and the Caribbean have maintained a largely open-border policy. However, with more than 5,000 daily arrivals, national capacities in host communities are overstretched.
UNHCR has been coordinating a region-wide approach to cope with the scale of the influx.
Joint analysis and reinforced inter-agency tools are essential to assess the humanitarian conditions of affected populations and establish ‘country profiles’ to scale up operational impact. This requires information on mixed movements and unmet needs to be captured, categorized into a commonly agreed analysis framework, and made available to humanitarian actors. UNHCR needs very specific data to develop tailored assessment strategies at the national and regional levels to ensure humanitarian needs are identified and covered.

In collaboration with a mixed movement coordination platform, DFS has supported the development and adoption of UNHCR’s situational analysis framework to cover all information needs, ensuring compatibility with other ongoing initiatives in the Americas region.
DFS is focusing on identifying and extracting information on unmet humanitarian needs in the countries affected by the Venezuelan refugees and migrant crisis in DEEP.
Working with its teams of Spanish, English, and Portuguese-speaking taggers throughout the project, DFS ensures global standards and taxonomies are applied while identifying key priorities and tracking sources of information. The result is an ability to create vital snapshots, including situation analysis, for each affected country, informing country plans, interagency processes such as HNO/HRP, and the Regional Refugee and Migrant Response Plans (RMRP). To strengthen local capacities and facilitate the takeover of the secondary data review in DEEP, DFS has organized remote training and developed online tutorials for national focal points, supporting the project’s sustainability.

Crisis context/scope of work	Community-based disaster preparedness programmes
Geographical scope	Global
Project period	February – June 2019
Donors/partners	International Federation of Red Cross (IFRC)
Budget	USD 20,000
# Leads:	89
# Entries:	1,551
Analysis framework used:	IFRC VCA analytical framework in DEEP

Problem

DFS’ solution

The Vulnerability and Capacity Assessment (VCA) is a participatory investigative process developed by the International Federation of Red Cross and Red Crescent Societies (IFRC) to enable communities to become more resilient to natural hazards by assessing and analyzing the risks faced and allowing them to identify actions. VCA allows Red Cross Red Crescent (RCRC) National Societies to explore the source of risks, identify the most affected communities and strengthen capacities.
RCRC National Societies upload and access reports via the EVCA repository, providing vulnerability and capacity assessments at community levels across countries. Because the VCA tool benefits from near-constant development to manage its growing number of reports, IFRC sought a more-automated process to quickly scan VCA/EVCA reports to extract and visualize the required data to identify trends and gaps.

DFS provided support to IFRC to manually curate and structure existing RCRC reports into an analytical framework in DEEP allowing IFRC to further develop their assessment tools.
Today, DFS supports IFRC to develop a system of extracting and visualizing the necessary information in VCA/EVCA reports in the EVCA repository to get snapshots of key data regarding main hazards, exposures, vulnerability, capacity and risks for communities concerned.
After piloting the project in the Philippines, DFS partnered with IFRC on a global roll out by finalizing the list of relevant criteria, generating a representative sample of documents to tag, and coordinating the tagging of the reports leading to more effective disaster risk management.

Crisis context/scope of work	Connecting information on global emergency needs with the right response
Geographical scope	Global
Project period	Jan 2019 – ongoing
Donors/partners	International Federation of Red Cross (IFRC)
Budget	USD 300,000 till Jan 2022
Technologies used:	Django, Postgres, PostGIS, React, Mapbox, D3.js

Problem

DFS’ solution

The GO platform was launched in 2018 as part of IFRC‘s modernization and digitization of disaster information. The system supports Red Cross Red Crescent Societies worldwide allowing IFRC to make disaster information universally accessible and helpful to all IFRC responders.
In 2019, IFRC needed additional features on the GO platform such as information about which national societies were doing what interventions and where.
An initial ‘Who does What, Where’ or the ‘3w’ tool had been developed but IFRC needed a more centralized platform that supported more information in multiple languages. The COVID-19 pandemic exacerbated IFRC’s needs to provide program progress and support decision-making. IFRC needed technical support to structure and visualize data in a user-friendly way.

DFS has been providing technical support for IFRC’s GO platform since 2019. In partnership with IFRC’s Information Management team, DFS worked as a developer to optimize the 3w module of the GO platform to allow synchronized data input and data visualization using business intelligence software including Tableau or PowerBI.
To improve access to COVID-19 emergency information, DFS supported the development of COVID-19 dashboards. The resulting visualizations created a more visually engaging landing page, organizing critical data in a more usable format that supports the automatic translation of content from English into Spanish, French, and Arabic (IFRC’s official languages). DFS rolled out digital wayfinding across multiple languages including specific navigational features, key figure references, and crisis summaries.

After deciding the overall architecture and direction for developing our new CRM system to manage casework and related data, we needed a technical partner. DFS led technical development of the platform, piloted it in three countries, and led the roll-out to 27 countries (covering all regions). We relied heavily on DFS not only for the technical side of developing the platform, but also for preparing the training materials and leading the training with our in-country partners adopting the platform.

Alison Matthews

Programme Lead, Advocacy and Legal Advice Centers (ALACs) Transparency International

Crisis context/scope of work	Fight against corruption globally
Geographical scope	27 countries across the globe
Project period	August 2019 – September 2021
Donors/partners	Transparency International
Budget	USD 187,000
Technologies used:	Salesforce, Salesforce Apex, Python

Problem

DFS’ solution

Transparency International (TI) works to end global corruption in partnership with government, business, and civil society.
In early 2009, the TI Secretariat in Berlin (TI-S) began utilizing a database to provide its national chapters with a case management system to manage corruption information securely and efficiently. Today, TI’s successful program requires an updated data platform and the support of a more secure CRM (Customer Relationship Management) solution. As with most growing organizations, TI’s technologies need regular updating to allow for better digital records management and client communications.

DFS led TI through a detailed consultative process, including interviewing national chapters, to gather business intelligence on the technical requirements needed for a more suitable database.
Ultimately, TI and DFS selected a new environment for the information management system. DFS developed the roll-out roadmap, designed the prototype, and provided testing and training.
The new information management system now serves twenty national chapters of TI, allowing offices to process data, information, and documentation faster and more securely and to create analysis and manage client complaints and cases.

Crisis context/scope of work	Accountability for crisis affected population
Geographical scope	Global
Project period	May – June 2021
Donors/partners	International Federation of Red Cross (IFRC)
Budget	USD 18,000

Problem

DFS’ solution

The International Federation of the Red Cross Red Crescent Societies (IFRC) is the world’s largest humanitarian network with over 160,000 branches and millions of volunteers.
To highlight stories from national communities, IFRC initiated the Local Data Stories Project in 2019, allowing local communities to inform programming. The project extracts information from social media, local news articles, and strategic documents from a Federation-wide database.
After prototyping the project in selected countries, IFRC needed a technical partner to conduct a technical review of existing functions and systems before the global rollout.

DFS evaluated the potential of expanding the Local Data Stories Project to include all 192 National Societies by conducting a desktop review with members, evaluating the site’s code/algorithm settings, and ensuring stakeholder feedback reviews from all relevant parties.
DFS provided IFRC with strategic advice to support the next stage of its beta project including recommendation on how open source code could be integrated with other internal and external tools for IFRC. DFS suggested a series of higher-level organizational recommendations on how to best integrate and use data across IFRC while helping to facilitate the global roll-out of the project.

After piloting a small-scale study to explore the potential for machine learning and Al to help us gather more information on the activities of local branches around the world, we needed a technical partner. That’s when we heard about DFS. We really enjoyed working with them. They confirmed our assumptions about potential data gaps on the digital transformation journey and provided a code review, in-depth research, and recommendations that were used to inform our next steps.

Heather Leson

Data Literacy Lead, International Federation of Red Cross Red Crescent Societies

Read about some of our projects.

Data Entry and Exploration Platform (DEEP)

How AI is Bettering Response To Internal Displacement

COVID-19 Situation Analysis

Secondary Data Review – GIMAC

2020 Humanitarian Needs Overview

Humanitarian Response in Urban Contexts – GRC

Equipping IFRC to Respond to the DRC Ebola Outbreak

Cash Assistance for Refugees – IFRC

Venezuelan Refugee and Migrant Crisis – UNHCR

Vulnerability and Capacity Assessments – IFRC

Training and Secondary Data Analysis Capacity Building – IFRC

Media Monitoring Through IOM’s Missing Migrant Project

GO Platform and COVID-19 Dashboards – IFRC

Environmental Assessment Tool (NEAT+) – UNEP

Media Monitoring Platform – IDMC

Tracking Gender-Based Violence – UNFPA

Women’s Participation Project (WPP) Website – IOM

Information Management System – Transparency International

Tracking Internally Displaced Persons Using AI – IDMC

Data Visualization System – DIFD Nepal

Recovery Reporting after Earthquake in Nepal – CRS

Open Government Web Application – Congo Research Group (GEC) / NYU

Global Internal Displacement Database (GIDD) – IDMC

Informing Humanitarian Decisions through DEEP

Emergency Response Questionnaire Builder – IFRC

Improving Emergency Needs Assessments – UNHCR

Hosting and Maintenance of theDEEP.io

DEEP Feature Development – OHCHR

Local Data Stories Project – IFRC

Crisis context/area of work	Building assessment capacities of humanitarian responders
Geographical scope	Global
Project period	March 2020
Donors/partners	International Federation of Red Cross (IFRC)
Budget	USD 15,000
Analysis framework used:	IFRC VCA analytical framework in DEEP

Crisis context/scope of work	Missing migrants, refugees and asylum seekers worldwide
Geographical scope	Global
Project period	Jan – March 2021
Donors/partners	International Organization for Migration (IOM)
Budget	USD 36,000
Technologies used:	Django, Postgres, PostGIS, React, Mapbox, D3.js

Crisis context/area of work	Environmental sustainability in humanitarian programme planning
Geographical scope	Global
Project period	Apr 2019 – ongoing
Donors/partners	United Nations Environment Programme (UNEP)
Budget	USD 250,000
Technologies used:	Django, Postgres, PostGIS, React, Mapbox, D3.js, Kobo

Crisis context/area of work	Global internal displacement
Geographical scope	Global
Project period	May 2021
Donors/partners	Internal Displacement Monitoring Centre (IDMC)
Budget	USD 10,800
Technologies used:	Django, Postgres, PostGIS, React, Mapbox, D3.js, Kobo

Crisis context/area of work	Gender-Based Violence
Geographical scope	Global
Project period	Jan 2019 – ongoing
Donors/partners	United Nations Population Fund (UNFPA)
Budget	USD 38,385
Technologies used:	Drupal

Crisis context/scope of work	Displaced women’s participation in humanitarian programming
Geographical scope	Global
Project period	July – September 2020
Donors/partners	International Organization for Migration (IOM)
Budget	USD 29,239
Technologies used:	Drupal, D3, jQuery, MariaDB

Crisis context/scope of work	Internal displacement globally
Geographical scope	Global
Project period	November 2019 – December 2020
Donors/partners	Internal Displacement Monitoring Centre (IDMC)
Budget	USD 327,000
Technologies used:	Django, Postgres, PostGIS, React, Mapbox, D3.js

Crisis context/scope of work:	Evidence for Development (E4D), Nepal
Geographical scope	Nepal
Project period	July 2018
Donors/partners	DFID Nepal
Budget	USD 1,200
Technologies used:	Mapbox

Crisis context/scope of work	2015 Nepal Earthquake
Geographical scope	Nepal
Project period	July 2018 – Feb 2019
Donors/partners	The Catholic Relief Services (CRS) Nepal
Budget	USD 7,500
Technologies used:	Python, django

Crisis context/scope of work	Government accountability
Geographical scope	Democratic Republic of Congo
Project period	September 2020 – January 2022
Donors/partners	Congo Study Group (GEC)
Budget	USD 29,111
Technologies used:	Django, Postgres, PostGIS, React

Crisis context/scope of work	Internal displacement
Geographical scope	Global
Project period	May 2021
Donors/partners	Internal Displacement Monitoring Centre (IDMC)
Budget	USD 10,800
Technologies used:	Django, Postgres, PostGIS, React, Mapbox, D3.js

Crisis context/scope of work	Grand Bargain workstream 5/ Joint and impartial needs assessments
Geographical scope	Global
Project period	Oct 2020 — Sept 2022
Donors/partners	Danish Refugee Council (DRC)
Budget	USD 628,645

Crisis context/scope of work	Humanitarian needs assessment processes
Geographical scope	Global
Project period	August – December 2019
Donors/partners	International Federation of Red Cross (IFRC)
Budget	USD 21,540

Crisis context/scope of work	Humanitarian data review and analysis through DEEP
Geographical scope	Global
Project period	April – December 2020
Donors/partners	International Federation of Red Cross (IFRC)
Budget	USD 20,000