Archive for July 2022

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[Commlist] New book: Data for Journalism Between Transparency and Accountability

Fri Jul 29 12:01:52 GMT 2022






*Data for Journalism Between Transparency and Accountability * <https://www.routledge.com/Data-for-Journalism-Between-Transparency-and-Accountability/Tong/p/book/9780367466343>
By Jingrong Tong

*Book Description*


Considering the interactions between developments in open data and data journalism, /Data for Journalism: //Between Transparency and Accountability /offers an interdisciplinary account of this complex and uncertain relationship in a context of tightening the control over data and weighing transparency against privacy.

As data has brought both promise and disruptive changes to societies, the relationship between transparency and accountability has become complicated, and data journalism is practised alongside the contradictory needs of opening up and protecting data. In addition to exploring the benefits of data for journalism, this book addresses the uncertain nature of data and the obstacles preventing data from being fluently accessed and properly used for data reporting. Because of these obstacles, it argues individual data journalists play a decisive role in using data for journalism and facilitating the circulation of data. Frictions in data access, newsrooms’ resources and cultures and data journalists’ skill and data literacy levels determine the degree to which journalism can benefit from data, and these factors potentially exacerbate digital inequalities between newsrooms in different countries and with different resources. As such, the author takes an international perspective, drawing on empirical research and cases from around the world, including countries such as the UK, the US, Germany, Sweden, Australia, India, China and Japan.

Introducing a new dimension to the study of developments in journalism and the role of journalism in society, /Data for Journalism /will be of interest to academics and researchers in the fields of journalism and the sociology of (big and open) data.

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