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Data journalism and the ethics of open source: Transparency and participation as a prerequisite for serving the public good


Porlezza, Colin (2019). Data journalism and the ethics of open source: Transparency and participation as a prerequisite for serving the public good. In: Daly, Angela; Devitt, S Kate; Mann, Monique. Good Data. Amsterdam: Institute of Network Cultures, 189-201.

Abstract

Data journalism has enjoyed an increasing amount of attention and success both in media practice and in journalism research. Unlike traditional journalism, which only recently adopted concepts such as openness and accountability, data journalism seems to be deeply rooted in a culture of open source that comes with increased transparency, shareability and participation. This chapter analyzes the question whether and to what extent data journalists effectively reflect the ethical notions of the open source culture in their everyday work routines and what kind of best practices are in place in order to minimize the ethical challenges they are confronted with while accessing, analyzing and publishing data. The proposed chapter offers therefore a structured insight into whether and how data journalists implement the four normative principles - transparency, participation, tinkering, and iteration - that the concept of open source implies. The chapter also highlights and discusses key ethical standards such as sharing source-codes or granting third parties with complete access to raw datasets.

Abstract

Data journalism has enjoyed an increasing amount of attention and success both in media practice and in journalism research. Unlike traditional journalism, which only recently adopted concepts such as openness and accountability, data journalism seems to be deeply rooted in a culture of open source that comes with increased transparency, shareability and participation. This chapter analyzes the question whether and to what extent data journalists effectively reflect the ethical notions of the open source culture in their everyday work routines and what kind of best practices are in place in order to minimize the ethical challenges they are confronted with while accessing, analyzing and publishing data. The proposed chapter offers therefore a structured insight into whether and how data journalists implement the four normative principles - transparency, participation, tinkering, and iteration - that the concept of open source implies. The chapter also highlights and discusses key ethical standards such as sharing source-codes or granting third parties with complete access to raw datasets.

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Additional indexing

Item Type:Book Section, refereed, original work
Communities & Collections:06 Faculty of Arts > Department of Communication and Media Research
Dewey Decimal Classification:700 Arts
Language:English
Date:2019
Deposited On:19 Feb 2019 11:18
Last Modified:07 Apr 2020 07:19
Publisher:Institute of Network Cultures
Series Name:Theory on Demand
Number:29
ISBN:978-94-92302-27-4
OA Status:Green
Official URL:http://networkcultures.org/blog/publication/tod-29-good-data/

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