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+++++++++++ an open-access postprint of this paper is available on UCD's institutional repository here: https://researchrepository.ucd.ie/rest/bitstreams/29628/retrieve +++++++++++ This paper explores data journalism education, with a particular focus on formal training in the higher education sector globally. The study draws on data from: (1) the 2017 Global Data Journalism Survey, to study the state of data journalism education and the requirements in terms of training and (2) a dataset of 219 unique modules or programmes on data journalism or related fields that were curated and examined in order to understand the nature of data journalism education in universities across the world. The results show that while journalists interested in data are highly educated in journalism or closely related fields, they do not have a strong level of education in the more technical areas of data journalism, such as data analysis, coding and data visualisation. The study further reveals that a high proportion of data journalism courses are concentrated in the United States, with a growing number of courses developing across the world, and particularly in Europe. Despite this, education in the field does not have a strong academic underpinning, and while many courses are emerging in this area, there are not enough academically trained instructors to lead and/or teach such interdisciplinary programmes in the higher education sector.
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... It was not inevitable that this would be seen as exciting, significant journalism worthy of its own awards (Ojo and Heravi, 2018). Nor was it inevitable that universities would dedicate courses to it (Heravi, 2019). Instead, this paper understands data journalism as a rationalised and contingent category of knowledge shaped by discourse. ...
... Its generalised acceptance of the stability and homogeneity of the industry (Deuze and Witschge, 2018) has led to a narrow focus on socialising students to the routinised practices of the newsroom model (Mensing, 2010) rather than a more critical engagement with how normative ideas of journalism are channelled into university education and whose voices are amplified or marginalised in this process. The scholarship of data journalism education is inevitably even more limited but there are useful reports on the extent of data journalism education globally (Berret and Phillips, 2016 in the USA; Davies and Cullen, 2016 in Australia;Heravi, 2019 globally;Splendore et al., 2016 in 6 European countries;Yang and Du, 2016 in Hong Kong) and the challenges it poses to educators (Berret and Phillips, 2016;Green, 2018;Heravi, 2019). Beyond this, the literature is mainly confined to descriptions of model curricula and 'innovative' pedagogy (Bradshaw, 2018;Green, 2018;Hewett, 2015;Treadwell et al., 2016). ...
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Becoming a data literate, technologically competent journalist is represented as a desirable goal that will benefit the individual, the industry and society as a whole. Data journalism skills are increasingly being taught in journalism programmes around the world. This article applies Foucault’s distinctive conceptualisation of discourse to critically examine data journalism as constructed in the ‘talk’ of its most visible pioneers. The analysis is driven by three distinctive aspects of Foucault’s theory of discourse – power, knowledge and materiality. Using these tools, I investigate how data journalism knowledge is produced, the practices that reinforce it and the strategic power relations it conceals. I argue that data journalism draws on four discourses – journalism, technology, enterprise and citizenship – and wraps itself in the power relations embedded in these prestigious discourses. I argue that there is a political imperative for journalism educators to examine these power relations because material injustices along race, gender, class lines are built into them and have consequences for our students and society.
... Data journalism is a specialization that integrates several disciplines such as journalism, computer science, social science, and design, and promotes data and fact-driven journalism (Heravi 2019). This specialization incorporates a wide range of styles, such as visualizations or text-based stories, which both tell a story using numbers and statistics (Rogers 2017). ...
... As demonstrated by the number and variety of research topics over the last decade, data journalism can be considered a consolidated and mature field of study (Beiler, Irmer, and Breda 2020) Some studies, for example, have focused on the origins of data journalism and their epistemological aspect (Hammond 2017 Bhaskaran 2020) or some of the Arab states 1 (Fahmy and Attia 2020), and others in the educational aspects of this discipline (Heravi 2019;Splendore et al. 2016;Chaparro-Domínguez 2014). ...
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Data journalism is a consolidated specialization in the newsrooms of many of the world's media outlets. Despite this, little research has been conducted on the ethical principles followed in this field of journalism. Data journalism uses different types of software to find its stories by statistically analyzing large datasets. Our research examines the winning projects of the Data Journalism Awards, Sigma Awards, and Online Journalism Awards, the last in the data journalism category, between 2012 and 2020. Using qualitative content analysis, we analyzed these projects from a three-fold ethical perspective: verification and data analysis, transparency, and privacy. Our main findings show that the winning projects complied with verification and data analysis, which is a standard practice to cross-check data from various sources and contextualize them adequately. In contrast, transparency and privacy principles were followed to a lesser extent. In light of these results, we propose that future research should focus on the perceptions of data journalists and users regarding the ethical standards that these projects meet.
... (4) Analysis and research on data journalism education. For example, Bahareh R. Heravi's (3WS of Data Journalism Education: What, Where and Who) pays particular attention to the education of data journalism in the global higher education sector (Heravi 2018). Bradshaw, Paul's (Data Journalism Teaching, Fast and Slow) draws on the experience of teaching data journalism in various backgrounds over the past ten years, and analyzes the experience and lessons of different teaching techniques and data journalism teaching choices (Bradshaw 2018). ...
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In big data era, data has become an important part of human lives and work. At the same time, data plays an important role in information acquisition and dissemination. At present, the influence of data journalism is gradually increasing. However, unlike other countries, China data journalism started late. To study the problems of data journalism and the trend of future development, we use the method of combining data and news to explore the status quo and dig out the existing problems. This article first summarizes the research status, research methods, and theoretical basis of data journalism's propagation path. Next, it uses Lasswell's 5W model: a new model to analyze data news from five aspects, namely, disseminator, disseminating channel, dissemination content, audience, and dissemination effect. Finally, based on content analysis, searching, and data mining, an indicator system is constructed for the current new media’s news dissemination effect evaluation, and the Delphi method is used to assign weights to various indicators and make decisions based on them. By analyzing the results, this paper identify the problems in the process of combining data journalism and new media platforms, and provide help for the future communication strategy of data journalism.
... In the last ten years, the rise of data journalism in the Western news media presents a counter-point to this narrative (Coddington 2015). A new generation of quantitativelyadept journalists utilise increasingly open data to generate slick data visualisations, engaging data interactives and quantitatively-based investigative journalism (Splendore 2016, 345;McAdams 2019, 1;Heravi 2019;Scott 2017). All too often, however, this research overstates the significance of the data journalist within the news media. ...
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Numbers have long been central to the practice of journalism. But most journalists use numbers with relatively little critical engagement. This practice presents journalists with a dilemma: how can they, and their stories, maintain their credibility when such key pieces of information are not verified? This article takes a mixed-method approach to journalists’ use of numbers in their coverage of seven humanitarian crises in 2017. This includes a content analysis of news articles (n = 978) and semi-structured reconstruction interviews with journalists (n = 16). The findings highlight how journalists rarely verify the numbers they use. In place of verification, they engage in two processes. First, the constant construction of a hierarchy of trustworthy sources. Second, the discursive twinning of data with certainty – elevating databases above the most trustworthy institutional source. These two practices are aimed at ensuring the credibility of the numbers they use and maintaining the credibility of their profession by hiding behind trusted sources. These findings provide a rationale for why journalists trust certain sources over others, a detail lacking in the existing literature. It also puts forward a numbers-specific take on “strategic rituals” in the idea of “quantification as strategic ritual”.
... Finally, digital preservation topics are to a great degree absent from data journalism courses (Heravi 2017(Heravi , 2019 and should be added urgently. ...
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News organisations have longstanding practices for archiving and preserving their content. The emerging practice of data journalism has led to the creation of complex new outputs, including dynamic data visualisations that rely on distributed digital infrastructures. Traditional news archiving does not yet have systems in place for preserving these outputs, which means that we risk losing this crucial part of reporting and news history. Following a systematic approach to studying the literature in this area, this paper provides a set of recommendations to address lacunae in the literature. This paper contributes to the field by (1) providing a systematic study of the literature in the fields, (2) providing a set of recommendations for the adoption of long-term preservation of dynamic data visualisations as part of the news publication workflow, and (3) identifying concrete actions that data journalists can take immediately to ensure that these visualisations are not lost.
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Data Journalism has attracted considerable academic attention as an innovative journalism practice in the recent past. It has resulted in a steady increase in academic research on data journalism. A subset of these studies deals with imparting training in data journalism. This study attempts to systematically review the peer-reviewed academic literature on data journalism training in order to ascertain the present status of academic research on the subject. By examining the studies, it brings together insights about the prevalent methods used in data journalism training, the challenges faced by the instructors, the recommended best practices and the students’ perception about data journalism training. The study finds that accommodating a new programme in the existing tight schedule of journalism curricula, alleviating the math-fear in students and adequately addressing the interdisciplinary nature of the practice through consistent up-skilling are some of the challenges faced by data journalism educators. It also finds that the academic literature on data journalism training is less concerned about imparting ethical awareness related to the practice.
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This article argues that the logic of data journalism has been a driving force in journalism since its beginnings, particularly in the case of economic journalism. Economic journalism has historically integrated five central aspects of data journalism: working with data and databases; the development of a conceptual infrastructure for data analysis and storytelling; the regular use of visualization tools; the application of new technologies to the peculiarities of economic data; and the integration of different professional profiles in the newsrooms. By analyzing economic journalism - the first among equals of data journalism - the article argues that data journalism can extract some lessons from economic news in order to improve the extension of data stories to every news beat. Four recommendations are drawn: the importance of a balanced management of data exuberance, their newsworthiness, and the analytical and conceptual tools used to interpret them; the aim of visualization should be more conceptual than descriptive, in order to simplify and clarify complex issues, and relationships between data, to make the explanation of current affairs more relevant and understandable; data journalism needs a harmonious integration of investigative projects with day-to-day coverage; and data journalism should avoid the perils of technological determinism.
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+++++++++++ An open-access preprint of this paper is available on UCD repository here: https://researchrepository.ucd.ie/rest/bitstreams/44566/retrieve +++++++++++ Data storytelling is rapidly gaining prominence as a characteristic activity of digital journalism with significant adoption by small and large media houses. While a handful of previous studies have examined what characterises aspects of data storytelling like narratives and visualisation or analysis based on single cases, we are yet to see a systematic effort to harness these available resources to gain better insight into what characterises good data stories and how these are created. This study analysed 44 cases of outstanding data storytelling practices comprising winning entries of the Global Editors Network’s Data Journalism Award from 2013 to 2016 to bridge this knowledge gap. Based on a conceptual model we developed, we uniformly characterised each of the 44 cases and then proceeded to determine types of these stories and the nature of technologies employed in creating them. Our findings refine the traditional typology of data stories from the journalistic perspective and also identify core technologies and tools that appear central to good data journalism practice. We also discuss our findings in relations to the recently published 2017 winning entries. Our results have significant implications for the required competencies for data journalists in contemporary and future newsrooms.
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