How The Candy Crush Of Data Is Saving Lives In Nepal

The UN and Frog have teamed up on a platform that’s unifying data and first responders alike.


When Typhoon Haiyan struck the Philippines, it killed more than 10,000 people in a matter of hours. Dale Kunce, a senior geospatial engineer for the American Red Cross, was scrambling stateside to map the tragedy for first responders. The Philippine government had sent 40 pages of hastily scanned Excel tables. “It wasn’t even scanned by a machine scanner. So the pages would be turned slightly each time,” he says. The data, so crucial to planning recovery efforts, was useless in that form. Dozens of volunteers were tasked with retyping the information just for him to begin work.


Such a logistical hassle was commonplace until last year, when the UN Office for Coordination of Humanitarian Affairs (OCHA) and the global design firm Frog launched a new website called HDX–short for the Humanitarian Data Exchange. It has a clean user interface and meticulously coordinated data sets that, together, create a platform that helps disparate humanitarian organizations work together. The UN first deployed it during the Ebola pandemic in Africa, where it provided baseline information on clinics, deaths, and new outbreaks. And now, for its second major outing, it’s sharing dozens of key data sets coming in from Nepal.

“It’s like the Candy Crush of disaster information sharing,” Kunce says, alluding to its addictive front-end appeal. And it’s uniting information managers at some of the largest humanitarian organizations in the world under one easy-to-access data tongue to allow faster response coordination in Nepal.

Nepal Digital Model Elevation (DEM)OCHA Nepal

The HDX doesn’t look like much. The landing page for the Nepal earthquake is topped with a graphic of seismic activity in the region. Below that, you’ll see the confirmed injured and dead in large numbers. Below that, you have a simple list of files–things like population densities, climate data, river maps, and roads.

But with the click of a mouse, each of these pieces of information can be downloaded in standardized, editable file formats–think spreadsheets and CSVs, rather than stagnant PDFs. And with another click of the mouse, any approved organization can upload its data to share as part of that list. This combination of quick access and useful, predictable files is what HDX was designed for, and according to multiple NGOs we talked to, it’s unprecedented in the world of humanitarian data.


How It’s Used
Before HDX, humanitarian organizations wasted precious time on formatting. “We are feeding information to approximately six international organizations, and everyone had different files and formats. So for us, it was an absolute nightmare,” explains Justine Mackinnon, president of Standby Task Force. “Now, with HDX, everything goes into one format, gets put on the platform, and it’s accessed by everyone.”

Standby Task Force is a team of about 2,000 people from 80 countries who have been analyzing millions of Nepal-related tweets to build several databases, ranging from urgent needs and requests to which responders have reached the country to who has what sort of equipment where. By the time this story is published, 10 of these databases will be uploaded to HDX for public use.

“It’s really, really early on [in Nepal],” says Sarah Telford, program manager of HDX. “The type of data changes with the crisis. Right now, what’s important is geospatial data. Where are the roads? Where are the towns? Where are the hospitals? So they know what’s blocked and where the helicopters can land.”

The organization MapAction was able to hop on HDX shortly after the earthquake and download five key shapefiles of the region–basic templates showing geographical features like mountains and rivers. With these, they produce “quick-and-dirty” maps that can be used in PowerPoint presentations to coordinate efforts by the government, the UN, and NGOs. And they’ll print maps on the ground for volunteers who operate largely without electricity.

At the Red Cross, Kunce immediately downloaded the data on Nepal’s poverty statistics to use in the organization’s planning efforts. Impoverished areas tend to suffer the most in a natural disaster, and with the HDX data, the Red Cross could deploy its resources based upon this census-level information.


The Common Tongue
But what is HDX’s true “common tongue”? Is it just having files in something other than PDFs?

It ends up that the achievement here is a bit more complicated than that. HDX has a clean, streamlined front end–a mix of sheer utilitarianism and generally pleasing aesthetics–that has caused what Telford calls a “zeitgeist” in her field. Due to HDX’s design, formerly insular multinational organizations are more actively and openly sharing their data.

“Nerds like me really like something that’s shiny,” Kunce explains. “And HDX is really shiny. So all of us were like, let’s go use the HDX.”


Importantly, HDX is hosting one piece of data that unites all the big players like a Rosetta Stone. It’s the UN’s list for Place Codes (or P-Codes for short). P-Codes are numerical identifiers that are assigned to locations like towns, neighborhoods, or hospitals in big data sets. However, P-Codes aren’t standardized–they’re not simply based upon recognizable coding like GPS coordinates. Instead, each organization might have different P-Codes for the same place, built upon entirely different logic. On top of that, these P-Codes might even change over time. So P-Codes used in the aftermath of Nepal’s 2015 earthquake might not be used in a disaster occurring in 2017.

Why isn’t there some universal list of P-Codes? Actually, there has been. Since 1999, the UN has released a P-Code standard. It was online for anyone to download, and still exists online outside of HDX. But as Kunce explains, nobody was using it, so raw data he’d be mining to create Red Cross maps from various sources wouldn’t match up. Yet within a year of HDX’s launch, he has seen the P-Code standard tighten up across the world. Why? He believes that HDX proved so appealing for information managers to use that they wanted to get in line with the more collaborative nature of the UN’s P-Code system.

“Basically, it wasn’t a technical problem. It was a political problem,” Kunce says. “From my perspective, sitting outside HDX and watching it grow, it solved a technical problem in that it was a better overall platform to share data, and it solved the political problem [of people using the same standard], because it was a better technical platform.”

Nepal: IDP camps siteOCHA Nepal

Some Politics Remain
As bullish as Kunce is on the openness of HDX data-sharing, he admits that his own organization, the Red Cross, has yet to upload data into it. “We hope to be. We’re working hard to be able to do that,” he says. “[But] HDX is a relatively new thing. It’s only been around for a year. I like to think that the Red Cross moves really fast, but we’re a big organization. We do try to share our data as much as possible, but we haven’t figured out the mechanics of putting our own data on there yet.”

But what “mechanics” could be in the way, given that the Red Cross is already mining HDX data, and therefore, already adhering to many of HDX’s file standards?


“You have to remember, ultimately, all these organizations are businesses, so building the trust to share is changing complete behaviors and the way organizations work,” Mackinnon says. “It’s a bit unnerving for some companies because they used to work in silos. We’re now saying to them, ‘We want you to share.’ They’re thinking, ‘Why do we want to share our customer base?’–that’s putting it in very raw terms.”

Ultimately, Mackinnon believes that HDX will not just prove a convenient platform for groups like the Red Cross to mine, but an economically sound one for everyone to take part in.

“Organizations are seeing the benefits,” she says. “They’re finding some of the work they’re doing has already been done … the whole collaborative in turn saves time, money, effort, everything.”

About the author

Mark Wilson is a senior writer at Fast Company who has written about design, technology, and culture for almost 15 years. His work has appeared at Gizmodo, Kotaku, PopMech, PopSci, Esquire, American Photo and Lucky Peach