What is data journalism?

Data journalism is a specialized field that involves filtering and analyzing large data sets to create or enhance news stories. It bridges traditional reporting with computer science, statistics, and data visualization to help the public understand complex patterns. Many data-driven stories originate from open data sources, public records requests, or leaked materials, while sharing overlapping goals with analytic journalism in explaining complex realities.

What we know

• Data journalism involves filtering and analyzing large data sets to build or elevate a news story. [1]
• The practice combines journalism with disciplines like data visualization, computer science, and statistics. [1]
• Many data-driven stories start from newly available resources such as open source software, open access publishing, open data, public records requests, or leaks. [1]
• Analytic journalism, much like data-driven approaches, seeks to make sense of complex reality and combines aspects of investigative and explanatory reporting to create public understanding. [3]

Where to go next

• whenHow does computer-assisted reporting relate to modern data analysis?
• how it workedWhat tools are used for open source data visualization?
• compared withHow does analytic journalism differ in its primary aims?
• the bigger pictureWhat is database journalism in information management?
• what caused itHow do open data initiatives supply raw materials for investigations?
• an unexpected connectionHow does social science research influence modern news reporting?Data journalism directly inherits techniques from social science research first advocated by Philipp Meyer in 1972 under the label precision journalism.

Sources

• [1]Data journalism · CC BY-SA 4.0
• [2]Database journalism · CC BY-SA 4.0
• [3]Analytic journalism · CC BY-SA 4.0
• [4]Data · CC BY-SA 4.0