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Data Visualizations

Data visualizations are central to data journalism and help to distinguish it from overlapping journalism forms, such as investigative journalism, precision journalism, computer-assisted reporting, computational journalism, quantitative journalism, and database journalism. Data journalism projects usually involve enormous amounts of complicated information and data. Visualizations play a key role in turning numbers into easier-to-understand information content.

The increased availability of certain forms of data and the use of data visualizations has had an impact on the news media landscape. To make effective use of visualizations, a data journalism team should consist of reporters, developers, data analysts, and designers. Interdisciplinary collaboration among people with different trainings is highly valued and may be required in news production, as data-driven storytelling becomes mainstream. Since data-processing tasks are now major components of the newsroom’s environment, computational literacy has become a fundamental requirement for journalism practitioners. A lack of computing knowledge and skills may constrain journalism professionals in news production, particularly in smaller news organizations.

This entry discusses the significance and evolution of data visualizations and their applications to journalism practice. Data-driven storytelling draws on a wide variety of skills—from simple data collection to statistical analysis to graphic design to coding and programming, among which data visualizations are core to the process of news production with data.

Data Visualizations in News

Data journalism, that is, using numerical elements in the production and distribution of news with computer-assisted tools, is an emerging area in the field of information and mass media. According to a 2017 research report by Google News Lab, one of the first comprehensive multinational studies of data journalism, 42% of the journalists surveyed use data regularly to tell stories, and 51% of news organizations have a dedicated data journalist on staff.

Journalism stories involving big databases and statistics have won several Pulitzer Prizes for general news or investigative reporting since the 1980s. Examples include the Montgomery Advertiser’s use of financial analysis to investigate the state’s high infant mortality rate in 1988 and a series of investigative articles published by The Wall Street Journal on the admission preferences for white privileged students in elite American universities by Daniel Golden in 2004. In addition, the staff of The Washington Post won the 2020 Pulitzer Prize (in the Explanatory Reporting category) for its climate change series that analyzed global temperature records and showed “with scientific clarity the dire effects of extreme temperatures on the planet” (The Pulitzer Prizes, 2020).

Tables, charts, maps, timelines, infographics, animations, and interactive graphs are common visual elements utilized to present data in data-driven storytelling. The basic ideas behind data visualization are not new. Diagrams, maps, and sketches have been used to depict events since ancient times. Maps were drawn to assist in exploration, navigation, and the identification of the locations of the stars in the universe. In ancient Egypt, for example, mapping of stars was used to locate the appropriate positions to construct towns and habitats. By the 18th century, new techniques were being used to present data in fields such as cartography, with theme-based maps based on medical, geological, or economic data instead of only showing geographical locations.

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