Journalists' responsibilities have been redefined by data journalism.

A thriving buzzword in the academy, “data journalism” is regarded as an important trend for the development of journalism in the digital age. On July 18, the Knight Center at the University of Texas at Austin opened registration for a new MOOC, “Data-Driven Journalism: The Basics”, an event which marks the significance of data journalism to today’s news development.

David Cuillier, associate professor of the School of Journalism at the University Arizona, said that data journalism evolved out of computer-assisted reporting and already has a 50-year long history in the U.S. By this definition, data journalism refers to a news writing style that involves using computers to gather and analyze data, Cuillier explained, noting that the wide-spread use of computers and the internet have helped to promote the popularity of data journalism. Cuillier also remarked that compared to twenty years ago, when reporters had to invest considerable time and effort to learn how to use professional software to draw data graphs, today’s reporters have mastered techniques of data analysis and can whip up data graphs in seconds. 

Today’s reporters have gradually realized that news not only originates from a source’s speech, but also from statistical data and information, concluded Jean Folkerts, former dean of the School of Journalism and Mass Communication at the University of North Carolina at Chapel Hill. 

Justin Arenstein, the chief strategist and Knight International Fellow at the International Center for Journalists in South Africa, commented that although new tools like data journalism do not replace traditional journalism, data journalism is no longer just catering to entertainment and voyeurism but creating decisive tools based on news reporting. He still believes that journalists should not lose the skill of storytelling, a tradition he says they should integrate with the new tools at the disposal, becoming good storytellers with the help of data analysis.

Data journalism requires independent judgment on the part of reporters, as well as a commitment to seeking for news sources rather than chasing trends. Justin Arenstein said that reporters should strive to satisfy readers’ demands and understand readers’ concern that reporters extract credible and actionable intelligence from the firehose of available information.

 

 

The Chinese version appeared in Chinese Social Sciences Today, No. 478, July 22, 2013

                                                                                                                           Edited by Zhang Mengying

                                                                                                                           Revised by Charles Horne

The Chinese link:

http://www.csstoday.net/xueshuzixun/guoneixinwen/82816.html