Data Journalism Practices Globally: Skills, Education, Opportunities, and Values

Bahareh R Heravi,Mirko Lorenz

doi:10.3390/journalmedia1010003

Abstract

Despite the growing interest in data journalism in newsrooms and its more recent emergence as an academic discipline, there is a need for systematic research on the state-of-the-art and current data journalism-related practices in newsrooms. The Global Data Journalism survey was an attempt to address this gap by studying the data journalism practices in newsrooms across the world. This study provides a descriptive view of the results of this study and discusses the findings on several aspects of data journalism practice, characteristics of data journalists and data teams, and their skills and educational requirements. We further provide insight into the values associated with journalistic work and analyse the ways in which the community believes data journalism has improved or undermined these values.

Highlights

Data journalism, known as data-driven journalism, is an emerging discipline that brings together knowledge from several disciplines, including journalism, social sciences, information science, data and computer sciences, data analytics, information design, and storytelling.Various definitions have been provided for data journalism in recent years. Berret and Phillips (2016, p. 15) define data journalism as a “field [that] encompasses a suite of practices for collecting, analyzing, visualizing, and publishing data for journalistic purposes”
These two countries present the highest quality of data journalism work, likely the highest number of active data journalists, and the most willingness to participate in data journalism-related studies
France and Argentina, were both the third contenders in terms of winning Data Journalism Awards between 2013 and 2016, but their rate of participation in the study did not match the rate of their winning cases, as it did for the United States and the United Kingdom

Summary

Introduction

Known as data-driven journalism, is an emerging discipline that brings together knowledge from several disciplines, including journalism, social sciences, information science, data and computer sciences, data analytics, information design, and storytelling.Various definitions have been provided for data journalism in recent years. Berret and Phillips (2016, p. 15) define data journalism as a “field [that] encompasses a suite of practices for collecting, analyzing, visualizing, and publishing data for journalistic purposes”. Known as data-driven journalism, is an emerging discipline that brings together knowledge from several disciplines, including journalism, social sciences, information science, data and computer sciences, data analytics, information design, and storytelling. Various definitions have been provided for data journalism in recent years. 15) define data journalism as a “field [that] encompasses a suite of practices for collecting, analyzing, visualizing, and publishing data for journalistic purposes”. Howard (2014) defines data journalism as the “application of data science to journalism, where data science is defined as the study of the extraction of knowledge from data” Howard further suggests that data journalism encompasses “gathering, cleaning, organizing, analyzing, visualizing, and publishing data to support the creation of acts of journalism” (ibid.)

Methods

Results

Conclusion