Challenges and Opportunities
Challenges to producing more
Building on Heravi and Lorenz’s data journalism survey1, as well as the Google News Lab report2, we investigated the main hurdles in generating more data journalism. Our extensive answer selection was a combination of the options offered by the two reports. This was done to give a comprehensive list of possibilities to our respondents, and our findings reflect, where applicable, the results of the two studies.
The survey findings showed that the top three barriers for data journalists were access to quality data (56%), followed by time pressure (49%) and lack of final resources (47%). In fourth place we found a lack of adequate knowledge in data analysis (44%), suggesting that data journalists could do a better job with more training. Similarly, the fifth and sixth most common hurdles were ensuring data reliability (39%), followed by a lack of data visualisation knowledge (36%).
Generally, a lack of knowledge in a specific area is seen as a bigger struggle than a lack of adequate software. On another note, not many data journalists see a lack of interest from consumers, or a poor return on investment in terms of audience benefit as a challenge, showcasing data journalists’ belief in the value of their work.
Data access and quality
How data journalists rate the quality and access to local and national data varies substantially around the world. The table below offers a breakdown by variable type for all the countries with a minimum of 10 respondents, countries ordered by the number of respondents.
Generally, local data is overall poorer both in terms of quality and access. The Scandinavian countries stand out by ranking the highest for local and national data. However, countries in other regions, such as Asia and the Middle East, paint a less promising picture for data quality and access (e.g. Egypt, Turkey, and Pakistan).
Having a clear source and provider was considered the most important feature (80%) in determining the usefulness of a dataset. Meanwhile, the number of citations and status of those using the data, or in other words, how popular a dataset is and who else has used it, was the least useful criteria (32% rated it as important). The findings signal that data journalists want to use objective parameters to determine a dataset’s quality rather than external cues.
What do data journalists see as the most promising technologies for data journalism? The top choice is software that facilitates data analysis and data visualisation (65%), which shows how central these tasks are to data journalism. Over half of data journalists selected machine learning, followed by programming languages (47%) and Natural Language Processing (NLP) (40%).
Barriers to learning
We asked educators specifically to tell us what they viewed as the greatest hurdles for learning data journalism. Lack of time was the most common selection (65%), followed by a lack of expert educators (52%) and the struggle to enter the industry (51%). Altogether, nearly half of educators saw a barrier in each of the listed options, revealing how many factors hinder learning data journalism.
Value of data journalism
What does data journalism bring to the field at large and to the audiences that consume it? About 7 out of 10 data journalists who responded to the survey said data journalism offers reliability and contextualisation of a story. However, data journalism also facilitates finding (68%) relevant or unique (63%) stories. Less than half indicated the need for data journalism to operate due to much information existing in data format (44%), and even less saw data journalism as a way to increase impartiality (40%).
- Heravi, Bahareh R., and Mirko Lorenz. “Data Journalism Practices Globally: Skills, Education, Opportunities, and Values.” Journalism and Media 1, no. 1 (2020): 26-40.
- Rogers, Simon, J. Schwabish, and D. Bowers. “Data journalism in 2017.” Google News Lab (2017).