Snurb — Thursday 10 October 2019 15:32

ANZCA 2019

Out-of-the-Box vs. In-House Tools: How Are They Affecting Data Journalism in Australia?

Mathias Felipe de Lima-Santos, Aljosha Karim Schapals, and Axel Bruns

5 July 2019 – Australia New Zealand Communication Association conference, Canberra

Out-of-the-Box vs In-House Tools: How Are They Affecting Data Journalism in Australia? from Axel Bruns

Abstract

Although the field of computer-assisted reporting (CAR) dates back as far as the 1960s (McGregor 2013), it was not until the late 2000s that data journalism began to establish itself as a credible field, with The Guardian’s ‘Datablog’, launched in 2009, a prominent example. In it, The Guardian broke the then widely publicised expenses scandal by Members of Parliament in the United Kingdom. In a thus far unprecedented move, it published 460,000 pages of expense reports, asking members of the public to sift through them and to flag questionable claims (Flew et al. 2010; Coddington 2015). However, the attention given to the Datablog also demonstrates that scholarly attention to data journalism is frequently centred on media initiatives and professionals across early-adopter nations such as the United Kingdom, the United States, and the Nordic countries (Parasie & Dagiral, 2013; Young & Hermida, 2015; Borges-Rey, 2016; Appelgren & Nygren, 2014).

In this paper, we argue that such an approach is no longer appropriate at a time in which data journalism has not only established itself as an important discursive order but has permeated contemporary news production processes across a wide range of journalistic forms and formats around the world. Therefore, this paper deliberately steps outside this somewhat narrow area of study and instead aims at a better understanding of how, specifically, the technological limitations, possibilities, and business models of out-of-the-box solutions commonly deployed in data journalism practice, including Infogram, Carto, Datawrapper, and Tableau, affect the production and archiving mechanisms of major data-intensive stories (Broussard & Boss, 2018) in the still under-researched case of Australia, and how such solutions compare to those developed in-house.

This article relies on a mixed-methods approach to study the status quo and future challenges in the adoption of out-of-the-box vs. in-house tools to shed light on how they, respectively, impact the practice of data journalism in Australia. First, all major data-intensive stories produced by established Australian news organisations (such as ABC News, SBS, Fairfax, and The Guardian Australia) between January 2017 to May 2018 were reviewed to establish an at-a-glance view of how many were still freely accessible, despite the challenges of archiving major data sets. Second, the study presents n = 18 semi-structured, in-depth interviews conducted with Australian media practitioners in early 2018, all of whom have played major roles in the reporting, design, and presentation of these data journalism stories. Finally, an additional questionnaire circulated to data journalists in Australia informs our understanding of both the benefits and disadvantages of the usage of out-of-the-box and in-house tools, respectively. Finally, the paper concludes with an agenda for future research.

References

Appelgren, E., & Nygren, G. (2014). Data Journalism in Sweden: Introducing new methods and genres of journalism into “old” organisations. Digital Journalism, 2(3), 394-405.

Borges-Rey, E. (2016). Unravelling Data Journalism: A study of data journalism practice in British newsrooms. Journalism Practice, 10(7), 833-843.

Broussard, M., & Boss, K. (2018). Saving Data Journalism. Digital Journalism, 6(9), 1206–1221.

Coddington, M. (2015). Clarifying Journalism’s Quantitative Turn: A typology for evaluating data journalism, computational journalism, and computer-assisted reporting. Digital Journalism. doi: 10.1080/21670811.2014.976400.

Flew, T., Spurgeon, S., Daniels, A., & Swift, A. (2012). The Promise of Computational Journalism. Journalism Practice, 6(2), 157-171.

McGregor, Susan E. (2013) A Brief History of Computer-Assisted Reporting. https://towcenter.org/a-brief-history-of-computer-assisted-reporting/

Parasie, S., & Dagiral, E. (2013). Data-driven journalism and the public good: “Computer-assisted-reporters” and “programmer-journalists” in Chicago. New Media & Society, 15(6), 853-871.

Young, M.L., & Hermida, A. (2015). From Mr. and Mrs. outlier to central tendencies: Computational journalism and crime reporting at the Los Angeles Times. Digital Journalism, 3(3), 381-397.