Uncovering the 'truth' through data: The Power of Data Journalism

By Becky Mills and Megan Jones

What is data journalism?

Data, in journalism's context, is often numerical but is structured in a way to inform and educate. The data part of 'data journalism' is a small section of the final journalistic piece. It is often used to ignite and guide a story.

Paul Bradshaw said, "Some people think data journalism has to be especially technical, mathematical, or investigative. In reality, it doesn't have to be any of those things…Data journalism involves structured information."

Data journalism is gaining popularity due to its sense of reliability and relevant information.

What does data journalism include?

Data journalism includes factual and unbiased information stemming from reliable sources such as:

• FOI requests

• Official statistics and public databases

• Surveys and interviews.

It is easy to assume that graphs, tables, and general diagrammatic presentations represent data journalism. To an extent, this is true. However, for a story to become journalistic, you have to unpick the data and transform it into storytelling. 

These skills are where data journalism becomes unique. It requires a distinctive skill set as one analyses and picks apart data while turning it into an entertaining yet informative story for readers.

Who works as a data journalist?

Pamela Duncan- 'You don't have to be a mathematician: you just have to be a storyteller.'

Duncan specialises in analysing COVID-19 data that looks into excess deaths and misleading data. She works for The Guardian and admits she's a 'spreadsheet addict'.

The stigma and stereotypes in Data Journalism.

Catherine D'Ignazio noted that those who work with data are mostly male, white, from wealthier countries, and highly educated, which doesn't reflect the general population.

A Reuter job advert defined a data journalist as "a data ninja who can hunt and slay data" (Reuter's job advert, 2015)

These labels reinforce the stereotype that data journalism is a male-dominated field where only tech-savvy individuals can succeed.

Examples  

Murder Mysteries (Scripps Howard News Service)- Tom Hargrove analysed government data and public records from 1980-2008, based on 185,000 unsolved murders and designed an algorithm to search it for patterns suggesting the possible presence of serial killers. By doing this, he discovered multiple 'closed' cases that still needed to be solved. "My primary purpose was to use numbers to shock people." 

Hargrove engaged readers through the interactive presentation. He effectively used visuals like maps and graphs to provide a realistic experience for viewers.

Another example is Jacklin Kawn’s investigative work on homicide rates in Manchester. Jacklin analysed data obtained through a Freedom of Information Act request from Greater Manchester Police. Her work uncovered trends in crimes, such as homicides spiking during the pandemic. Additionally, Jacklin highlighted several issues with Greater Manchester Police not recording this information. 

‘Numbers can tell a significant story’ Interview with Jacklin Kawn.

Jacklin Kwan is a freelance journalist specialising in covering physical science and technology. She has also published data stories on topics such as health policy and crime, and her work in data journalism has won two awards.

In 2021, Jacklin earned the 'NCTJ Award for Excellence in Data Journalism' for contributing to The Mill's investigation into the increase in homicides in Manchester during the pandemic. She obtained the data through a Freedom of Information Act request.

Jacklin has worked in various newsrooms, such as The Straits Times in Singapore, The Mill in Manchester, and Science Magazine.

We had the pleasure of interviewing her about her experience in data journalism.

In our interview, Jacklin highlighted the importance of data journalism, stating, “Data journalism is essential. Data is not just numbers or a spreadsheet; it can be images you find on social media or how many tweets are posted on a topic. Data is very important to understand this complicated age that we have going on right now.”

Jacklin thinks all journalists should learn how to analyse data as it's easily accessible and essential for understanding current events.

She defined data journalism as "essentially creating a signal from the noise around us. How do we label and organise the raw information around us using a standard language, like numbers, and analyse that language to find patterns? When you break it down that way, data analysis is just a core skill set that all reporters need to have."

Jacklin spoke of the stigma attached to data journalism by saying, "I think being a woman or coming from an ethnic background can give so much richness or new potential avenues to interpret data already out there.”

She continued, “My advice is just to give it a try. There is a data lens on any topic or issue that is worth reporting on, like arts and culture or politics…”

We hope you have learned the importance of data journalism through this week's newsletter. Remember, anyone can be a data journalist! You don't have to be a 'data ninja who can hunt and slay data’ or a ‘tech-savvy mathematical genius’.