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State of Data Journalism 2023 results

Work Practices

Type of data journalism

In 2017, Simon Rogers, Jonathan Schwabish, and Danielle Bowers published a report on the state of the field of data journalism. The findings showed data journalism outputs generally fell into three categories: investigative journalism, stories that explain data, and stories that are enriched by data.

As in 2021 and 2022, data journalism is predominantly focused on stories supported by data (61%), followed by investigative reporting (41%). This preference for narrative enrichment could be reflective of the broader audience's interest or the journalists' skill sets, or a combination of both. It is notable that with more experience in the field, journalists tend to diversify and conduct more investigative data journalism, which may require more time, experience and expertise.

The gap between types of data journalism is wider for part-timers, who are more prone to use data to enrich the story and less prone to create data explainers than their full-time counterparts.

As years of experience in data journalism increase, so does carrying out any of the typologies listed, until this trend reaches a plateau around 3-5 years of experience. Such increase is particularly steep for data investigations, suggesting that versatility grows with time in the field.

Work tasks

Data analysis is the most commonly performed task, carried out by nearly three out of four data journalists, highlighting the core importance of interpreting data for storytelling. In comparison, coding (19%), developing (9%), and web design (15%) are much more uncommon tasks. While three out of four analyse data, only just over half of respondents are also responsible for producing visualisations. We still find, like in 2022, that regardless of work tasks, as income increases so does the share of people who perform that work task.

Over time the distribution pattern of responses has remained constant. However, the share of respondents selecting each choice has generally decreased. This could be indicative of specialisation in one particular area, which is indeed suggested by the increase in fewer selections in this multiple choice question. The trend towards specialisation may be due to the increasing complexity and depth of skills required for each task, and it is particularly strong among women, who, like in the 2022 survey, chose fewer options in this multiple choice question.


In terms of geographic scope, the largest group works at national media organisations (48%), where their work also addresses stories of national value or scale (50%). These figures are consistent with the results from the 2022 survey and indicate that national scale remains a significant focus for data journalism, or that many local newsrooms are yet to invest in data journalism. Only 22% work at local news organisations and only one in four produces local data journalism.


Just over half of respondents cover Government and Politics in their data journalism, making it once again the top beat for the field. Environment and Weather / Climate reporting are steadily increasing since our first survey in 2021, with the former gaining six percentage points over the course of two years, and the latter eight. Weather / Climate is witnessing a sharp increase in coverage over time, as it was selected by 27% of respondents in 2021, 30% in 2022, and 35% in 2023. The Environment, which also has its highest increase in 2023, going from 44% in 2021, to 46% in 2022, and 50% in 2023, is the second most common beat, and it is now nearly on par with Government and Politics, reflecting the growing global concern over these issues and the strong relationship between data and climate reporting. The surge in climate and environment reporting highlights the role of data journalism in analysing and visualising complex datasets to shed light on environmental phenomena and the impacts of climate change. The Climate Journalism Awards and the 2023 News Impact Summit, organised by the EJC, responded to these shifts by incentivising journalists to adopt innovative techniques, driving greater awareness and action on environmental issues through data-driven journalism.

The share of journalists being specialised in more than one beat is on the rise. The median number of selections is five (standard deviation 3.75). One in four works on three and four different beats.


Over half of data journalists work for an online-only digital outlet, making it the most common medium for data journalism and emphasising the digital shift in news consumption and the potential for interactive storytelling online. This is followed by print or broadcast media outlets with a digital site (38%). Data reporters working for TV or radio are just over one in ten, respectively.

Like in 2022, over three quarters of respondents work for one medium in particular, or two. Oftentimes, combinations of different media types include social media alongside a primary legacy media format.

When it comes to the distribution of medium types by country, patterns remain overall consistent with the global distribution, in that online-only outlets and outlets with both a print or broadcast medium and additionally a digital site are the most common ones. Italy has distinctively low shares of respondents working for TV or radio.

Data journalists working in the TV media sector enjoy the highest salaries, followed by online media outlets. Print-only outlets are found at the opposite end of the spectrum earning the least amount in salaries. Since salaries are unadjusted by country, surely the distribution of medium types by country influences to a certain extent the patterns seen here.

Data Used

In 2023, public official governmental data remained the most common data type used, adopted by three out of four respondents. At the bottom of the distribution we find FOI-obtained data, used by one in five respondents globally. The widespread use of official governmental data signifies trust in and the necessity for authoritative sources, while the use of FOI-obtained data points to investigative journalism's need for transparency and uncovering information that is not readily available. By country, FOI-obtained data is more commonly used in the UK (43%) and the US (40%). Census data is also most commonly used in the US, where 68% of respondents have reported having used it in 2023. Similarly, scraped data is most commonly used in the US (58%). On the other hand, social media data is most common in Russia (62%).

By profession, educators, followed by editors, and then by employees, work on average with the largest number of data types. Contracted reporters tend to work more with census data, governmental data, and FOI-obtained data than freelancers. Social media data and crowd-sourced data are instead evenly distributed across professions in data journalism.

Dedicated data unit

One in four people surveyed works in a dedicated data unit. Dedicated data units are most commonly found in medium to large organisations, where around one in three of data journalists work in one. The presence of dedicated data units in larger organisations, but not as a norm, suggests that while there is a recognition of the importance of specialised data teams, many organisations may not have the resources to support them or may integrate data tasks across different teams. Regardless of company size, most dedicated data units (61%) have less than five members, however larger teams of 6-15 individuals are on the rise compared to 2022.


As the 2022 and 2023 survey results showed, most data journalism projects are completed within several weeks or months (51%), reflecting the time-intensive nature of this field. Projects completed in a day are very rare (9%), while one in five projects are completed in a week. Projects tend to be the fruit of collaboration with a small team of 2-5 individuals (45%), followed by solo work (32%).


Collaboration projects between different organisations are relatively rare (29%) and temporally the pattern is stable with previous survey editions. 38% of collaborations are one-time occurrences leading to separate content production. In fact, one-time collaborations are more common than ongoing ones, and separate content production is much more frequent than sharing resources or production.

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