Reporting based on the computer analysis of solid data could bring greater transparency and accountability
The ceremony of the 2016 Data Journalism Awards (DJA) took place at the Vienna town hall on Friday 17th June. It was held during the 2016 GEN Summit, the annual meeting of Global editors network (GEN) which gathers editors for online media.
Data journalism is about adopting an evidence-based approach to help critically analyse the data pertaining to issues affecting our lives. This branch of journalism combines the use of various forms of data analysis, design and visualisation leading to greater accuracy in reporting. This approach was pioneered by Philip Meyer, who was one of the first to adopt an approach grounded in the method of science, including data analysis, to the practice of journalism. Specifically, he used survey research and data analysis to demonstrate that college students were as likely to have attended the 1967 Detroit riot as high school dropouts.
EuroScientist interviewed some of the awardees on how they believe data journalism can improve accountability in our society. Specifically, we talked about data journalism projects questioning issues which are at the interface between the applications of science and society.
Greater accuracy in journalism
“The thing with data journalism is you can’t say ‘no, what you are saying is not true’,” explains Eva Belmonte, the managing editor of Civio Foundation, a Spanish non-profit investigative journalism organisation focused on political and health issues.
She won a DJA in the category ‘Investigation of the year (small newsroom)’ with her data journalism project Medicamentalia. The project’s objective was to explain the huge discrepancies in the price of medicines sold around the world, which, she believes, are not always justified by the different standards of living between countries.
“When we are talking about this kind of data, about science data, you need to be more accurate.” Belmonte also explains the value of adhering to a strict methodology to ascertain the credibility of her investigative work. She notes: “and the most important, you publish that methodology.”
Unveiling environmental and social issues
The role of data journalism is even more important in countries where transparency is still lacking. In Peru, for example, “the oil industry and mining are big companies, they represent a big economic power,” explains Milagros Salazar, director of Convoca, a data and investigative journalism organisation based in Lima.
She won a DJA in the category ‘News data app of the year (small newsroom)’ with a project, called Excesos sin Castigo–meaning Unpunished Excesses–about the impact of oil and mining industries on the environment and on the lives of the Peruvians living in the Peruvian Highlands and in the Amazon. Her work was based on the analysis of 3,000 documents, including data provided by the Peruvian state. The findings were published in La Republica, the second most important newspaper in Peru.
She notes that the government has difficulty in protecting its citizens and the environment from the economic power of large companies exploiting natural resources. For that reason, I think it’s very important that data journalism shows this problem to the world.” The documentary forced the authorities to be more transparent and to break the silence around these issues. Her work has led other investigative teams to pursue this issue.
Performing a watchdog role
Data journalism cannot be separated from journalism. “I don’t see data journalism and other forms of journalism being separate. I see them being totally intertwined,” says Peter Aldhous, who is a science reporter at BuzzFeed News. He trained as a scientist before becoming a science journalist and editor, previously working at New Scientist and at Nature.
Together with his colleague Charles Seife, science journalist and professor of science journalism at New York University, they won a DJA in the category ‘Data visualisation of the year (large newsroom)’ for a project called Spies in the Sky about government surveillance planes in the United States. They analysed four months of data of all of the planes over the USA, via a web site called flightradar24. They were thus able to narrow down all planes operated by the FBI and the US Department of Homeland Security. They relied on a software and programming language, called R, for data analysis and for statistics data visualisation. They also animated the planes over a map, using a geographic database tool called CartoDB, to tangibly demonstrate how extensive the flights were.
Aldhous’ scientific background has helped him investigate issues he finds interesting, such as criminal justice, mental health, surveillance and mining of personal data by large corporations. He believes that, ironically, science journalists—who are often trained in science and quantitative methods—have not embraced the use of data in journalism. Today, most of the data journalists are people with a background in social sciences.
Data journalism could help make science more accountable. “I do think there’s an enormous amount of potential,” suggesting that examining misconducts—such as manipulation of images or text plagiarism—are essentially data problems. In the same vein, he also quotes the work of Uri Simmonsohn, at the University of Pennsylvania, in the USA, who has developed tools to detect so-called p-hacking, such as selective reporting of significant results and bias in statistical analysis. He concludes: “I think that science journalists could do a great deal to perform a watchdog role in and around science by applying quantitative methods to the analysis of the published literature.”
Interview and text Sabine Louët, Editor EuroScientist
Podcast editing and text Charline Pierre
Featured image credit: BuzzFeed News
Latest posts by Sabine Louët (see all)
- All good things come to an end - 30 March, 2018
- Ivo Verbeek: cutting the middle man in language editing - 21 March, 2018
- Podcast: How open science could benefit from blockchain - 31 January, 2018