DEEP — through a time machine; from 2015 Nepal earthquake to 2021 Haiti earthquake

Data Friendly Space
3 min readSep 15, 2021


Six years ago, on April 25th 2015, at 11.56 am local time, an earthquake of magnitude 7.8 Mw hit Nepal. The news spread like a ripple around the world. The shocked humanitarian community lept into action without losing a minute.

Nearly 9,000 people were killed, many thousands more were injured, and more than 600,000 structures in Kathmandu and nearby towns were damaged or destroyed. Millions had become homeless.

Ewan Oglethorpe, then a data science engineer in Silicon Valley, arrived in Kathmandu to lend a hand as the post-quake humanitarian crisis was unfolding. The United Nations compound had countless tents set up and Ewan landed at the information management and assessment tent. One of the biggest challenges facing the humanitarian community was the creation of rapid needs assessments for immediate response. “I told them I knew how to code and analyze data, and pretty much right away, they put me to work,” Ewan recalls.

Ewan at the UN Assessment tent in Kathmandu during Nepal earthquake in 2015. (Pic. by Seth)

Soon after his arrival, Ewan met two fresh graduates from an engineering school in Kathmandu. He started a global IT operation in the kitchen of his rented apartment, and the project DEEP ( was born.

Six Years Later..

It’s been six years since the April 2015 Nepal Earthquake. Now DEEP, has become a go-to tool for leading global humanitarian organizations, including UNHCR, UNICEF, UN OCHA, and the IFRC.

DEEP has been instrumental in supporting the process of needs assessment and analysis, strategic response planning, resources mobilization, implementation and monitoring, operational peer review and evaluation throughout the humanitarian program cycle in several crises — from the Ebola outbreak to the Rohingya refugee crisis and now the ongoing Covid-19 pandemic.

The platform can support various field or headquarters-based institutional workstreams requiring solutions for managing unstructured data such as Secondary Data Review for informing specific research, context, sector or situational analysis or in support of needs assessments.

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.

Read more on DEEP: Using Machine Learning to Expedite Humanitarian Action

DEEP is a collaborative project governed by UN OCHA, UNHCR, UNICEF, ACAPS, IFRC, IDMC, OHCHR, IDMC, JIPS and iMMAP. Data Friendly Space (DFS) is currently the technical supervisor and host of DEEP.

Earthquake in Haiti

In 2021, eleven years after Haiti’s devastating 2010 earthquake, a 7.2 magnitude earthquake struck southwestern Haiti on 14 August at 8:30 am local time. As of 18 August, the latest tolls have risen to more than 2,100 dead and more than 9,900 people injured. (UN OCHA) According to Haitian Civil Protection, more than 37,300 homes have been destroyed and 46,000 have sustained damages. While less catastrophic than the 2010 earthquake, its impact is still devastating amid ongoing social and political upheaval. (UN OCHA)

DEEP in the context of the humanitarian response to the Haiti earthquake

H2H Network, a Geneva-based consortium providing technical support for better humanitarian action, has put together resources from its member organizations to respond to the #haitiearthquake.

Resources from H2H Network Organizations to respond to the Earthquake in Haiti.

In the context of the humanitarian response to the Haiti earthquake, DEEP could be useful to support protection monitoring, situation/risk analysis and participatory assessments. If you have any questions on how to use DEEP or would like a demo for your organization, please contact We are eager to partner with organizations who move quickly and have an outsized impact.

Data Friendly Space is the technical lead and host of DEEP and an active member of H2H Network.

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Written by: Rishi Jha — Communications & Partnerships — Data Friendly Space