After the Quake: Waiting for Relief

After the Quake: Waiting for Relief

Organisation: Centre for Investigative Jouranlism - Nepal (Nepal)

Publication Date: 04/10/2017

Size of team/newsroom:small

Description

Seven reporters rode motorbikes and four-wheel-drive Jeeps into Nepal’s mountains to find some of the 15,000 men, women and children struggling through a second winter in emergency tents or corrugated-metal shacks. Back in Kathmandu, our data wranglers analyzed more than 6,000 pages of government records to track rebuilding grants to earthquake victims. Our goal was to document and explain delays in Nepal’s reconstruction efforts after its devastating April 2015 earthquake. Nepalese people are our audience, but we also wanted to offer a resource for international organizations seeking earthquake recovery data. Our multimedia project, “After the Quake: Waiting for Relief,” went live on the Centre for Investigative Reporting-Nepal website in February. The project is a first in Nepal: seven young journalists from seven different media outlets collaborated on a deep data dive. Our very small team, brought together solely for this project, accomplished our goals at a much higher level than we thought possible. (By the way, all of the journalists had full-time jobs requiring them to file, at times daily, stories.) Our data chief Arun Karki analyzed records of reconstruction grants promised to 625,986 households. Using the results, he created an interactive map with granular detail of the slow pace of funds to earthquake-stricken areas. Collectively, stories showed that the Nepal government has so far spent only 3 percent of more than $900 million promised to residents to rebuild. While the seven journalists collaborated on data, each reporter produced and published an individual story. A BBC-Radio reporter revealed that international charities promised to build 22,000 houses, but have completed only 900, primarily because slow-moving Nepali authorities have not processed permits. Other reporters found that NGOs abandoned projects in mid-stream. Disorganized and fractionalized government reconstruction processes led to omission of thousands from relief rolls. A Republica reporter wrote that a distressing scarcity in manpower was delaying construction – even for those who had money and materials. Rudra Pangeni reported that a mere 150 masons trained in earthquake-resistant techniques were working in the hard-hit Sindhuli district – so few that the bricklayers would need 130 years to erect the district’s 34,256 demolished houses. A Fulbright Specialist award provided Washington, D.C.-based journalist Lucinda Fleeson the means to team up with CIJ-Nepal editors to coordinate the project. The Fund for Investigative Journalism, in Washington, D.C, provided funds for the reporters to take extra time to analyze data and travel to remote areas. Our stories contribute to the earthquake reconstruction story that will dominate Nepali news for many years. But we demonstrated that time-consuming data analysis can be shared collaboratively by multiple news outlets to document the human cost of Nepal’s heartbreakingly slow recovery.

What makes this project innovative? What was its impact?

This project is the first time that reporters from competing Nepali media outlets worked together on a common theme; also it is the first really deep data dive by media. While reporters published stories in their own news outlets, a Center for Investigative Journalism-Nepal website brought them together for a complex, nuanced report. The interactive maps show in astonishing detail grant distribution for each village in each of the 14 earthquake-hit districts. These figures are constantly updated. The maps alone have been heavily viewed, even in Nepal with its small Internet-penetration. Analytics show an average of 350 views per day. The interactive map for a Nepali Times article alone has received more than 1,000 views. In that report, Shreejana Shrestha revealed complaints and grievances against Village Development Committees where victims were omitted from grant lists. Collectively, the reporters’ stories reached tens of thousands of readers and viewers across Nepal as they were published in the four leading newspapers and websites. Importantly, stories about how international charities have built only a small fraction of promised houses were broadcast on the BBC-Nepali language service that reaches more than 6 million listeners. But the project isn’t just about the numbers. In-the-field reports and narratives of victims make the stories compelling. Rajneesh Bhandari begins: “It’s midnight. The rain pouring on the tin roofs makes a loud noise. Kanchaman Dong tried to ignore the rain and cold in the make-shift shelter that has been his home for two years.” As a result of the project, reporters developed more expert data skills. Rudra Pangeni of Republica just published another data story that shows how government officials spread money in voter districts to gain support in the upcoming elections. Phanindra Dahal of BBC Radio just reported that half the houses built since the earthquake are substandard and would not survive another quake.

Technologies used for this project:

As the reporters began to develop stories about the slow and disorganized distribution of promised grants to rebuild residents’ homes, we knew we could obtain government online data to document that grant process in precise numbers. Our data chief Arun Karki extracted more than 6,000 pages of online grant documents from the National Reconstruction Authority. For granular detail of each of the 14 earthquake-hit districts, he used personal sources to obtain information from the District Development Committees. The other six reporters analyzed additional data subsets. After group discussions, the data was cleaned, sort and analyzed for presentations in charts, maps and infograpahics. We used a variety of technologies. For collecting and analyzing data, we used Cometdocs.com, an online app (for pdf to Excel file conversion); Spreadsheet (for data cleaning and analysis); Open Refine (for data cleaning); and SQL (Sequential Query Language) for data analysis. For data visualizations, we used Excel, Highcharts, CartoDB, Infogram, vennage and other freely available software, in addition to Adobe Photoshop. For data mapping we used CARTO.com for multimedia video curation and Adobe Premiere.

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