Data Journalism Practices Research Articles

The Development of Data Journalism in China: Influences, Motivations and Practice

Using semi-structured interviews with Chinese data journalists across party and commercial media, this article assesses the structure and practice of data journalism in China. In doing this, it responds to calls for further studies of data journalism in non-western contexts. It finds that Chinese data journalists face some of the same pressures and challenges that have been documented in other countries, including limited access to data and the constraints imposed by the screen-size of smartphones. However, these were often exacerbated through a combination of social and systemic factors - to the point that their impact is qualitatively and quantitatively different. Simultaneously, however, we find that in some cases Chinese data journalists, at least amongst party media, were protected from pressures such as audience demand, and encouraged to focus on state-of-the-art work. We conclude that what has emerged is a form of ‘data journalism with Chinese characteristics’, and that these characteristics emerge from the interactions between systemic, newsroom and social factors.

Preserving Data Journalism: A Systematic Literature Review

ABSTRACT 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.

La transparencia institucional y mediática del coronavirus. Un análisis de los portales de datos y de los medios de comunicación digitales en Iberoamérica

Introducción. La emergencia sanitaria producida por el virus COVID-19 ha tenido diversas consecuencias en el panorama institucional y en el mediático. Ante una situación de esta magnitud, las instituciones gubernamentales han tenido que introducir medidas de transparencia en sus rutinas diarias para ofrecer a la ciudadanía una información actualizada y de calidad sobre la pandemia. Esto ha afectado también a las prácticas periodísticas, ya que el volumen de información dedicada al coronavirus ha ido en aumento en los medios de comunicación. El periodismo de datos se presenta como una de las fórmulas más recurrentes de los medios de comunicación digitales, con el desarrollo de mapas y gráficos que utilizan los datos oficiales. Metodología. Este trabajo de investigación pretende conocer, por un lado, el grado de transparencia informativa de los gobiernos de Iberoamérica sobre la enfermedad, así como el desarrollo del periodismo abierto, el periodismo de datos y otras prácticas por parte de los medios de comunicación para informar sobre el coronavirus. Para ello, se ha elaborado una evaluación de los portales de información sobre el COVID-19 de 12 países iberoamericanos y de los dos medios digitales más relevantes de cada país. Conclusiones. A pesar del enorme esfuerzo realizado por las instituciones para informar a la ciudadanía de la emergencia sanitaria, los portales de transparencia presentan diversas deficiencias. Los medios de comunicación, por su parte, han desarrollado principalmente el periodismo de datos, pero no han fomentado la transparencia mediática ni la participación de la ciudadanía en la elaboración de contenidos.

Data Journalism Practices Globally: Skills, Education, Opportunities, and Values

Despite the growing interest in data journalism in newsrooms and its more recent emergence as an academic discipline, there is a need for systematic research on the state-of-the-art and current data journalism-related practices in newsrooms. The Global Data Journalism survey was an attempt to address this gap by studying the data journalism practices in newsrooms across the world. This study provides a descriptive view of the results of this study and discusses the findings on several aspects of data journalism practice, characteristics of data journalists and data teams, and their skills and educational requirements. We further provide insight into the values associated with journalistic work and analyse the ways in which the community believes data journalism has improved or undermined these values.

Mapping the territory of data journalism: A practical concept explication

The prevalence of data journalism in recent years has challenged traditional journalistic norms as well as the relationship between journalism and other subjects, affecting journalism both internally and externally. While the practice of data journalism has become increasingly pervasive around the world, systematic research on data journalism is only just starting to receive scholarly attention. The multi-aspects of data journalism cause difficulties in attempts to define it critically and clearly, and the limited number of previous studies suffer from a lack of coherent connections bridging the field’s academic and professional dimensions. Through a concept explication, this article generates theoretical and operational definitions of data journalism via empirical analysis and meaning analysis.

“We need to find a revenue model”: Data journalists’ perceptions on the challenges of practicing data journalism in India

Data journalism is emerging as a new subspecialty in Indian journalism. Indian data journalism practice is in nascent stage and newsrooms have lately started recognizing it as a new practice. There were specific issues and challenges faced by journalists in western news rooms as they adopted the practice. To generate a comparative perspective, the study carried out semi-structured interviews with Indian data journalists about their perceptions on the challenges of practicing data journalism. The results show that there are external and internal bottlenecks in practicing data journalism in India. While irregular data releases, use of unfriendly formats by governmental authorities is a major concern; reluctance of media organizations to invest in data teams is identified as an internal challenge. Indian data journalists are skeptical about the audience’s participatory potential, which has restricted them from relying on practices like crowd-sourcing.

Teaching Data Journalism: Insights for Indian Journalism Education

With emergent subspecialties like data journalism bringing new skillsets and job roles, professionals and journalism educators find it difficult to imbibe the fast-changing industry demands. Such challenges in some countries and media industries put journalism educators in an advantageous position, offering them an agency to actively shape the contours of industry practice than getting shaped by it. From this perspective, the present study tries to understand data journalism practices in India and suggests certain insights to integrate data journalism training in programmes offered by Indian journalism education. By probing insights from the literature on data journalism education and by examining existing data journalism practices in India, the study calls for intervention with a pedagogic strategy to impart better data-sourcing practices, coding skills and critical data literacy among the students as an antidote to the prevalent DIY culture and overdependence on data aggregates. The pedagogic strategy should convey the importance of audience centrality and ethics in data journalism practice. It argues that such an approach can, in effect, improve industry practices as well as the quality of journalism education in India.

A Field Study of Arab Data Journalism Practices in the Digital Era

ABSTRACT This research paper presents an analysis of the state of data journalism practice in the Arab world through the use of the field theory approach. It is based on the analyzed results from a survey of Arab journalists conducted by the Arab Data Journalists Network (ADJN) in 2017. This paper discusses the factors affecting the practice and development of Arab data journalism. It sheds light on the potentials and challenges of practicing data journalism in the Arab world, especially in terms of required resources as well as the cultural, socioeconomic, and institutional context in the Arab journalism ecosystem. As an indication of a clear interest in this field, a significant amount of Arab journalists are interested in applying for data journalism training and fellowships. However, the business model of most Arab media organizations, which struggle from certain financial or political agendas, makes these organizations less interested in upgrading the quality of their content provided to their audience. Accordingly, they do not care about adopting new methods in presenting in-depth and data-driven content. This study concludes with a theoretical model regarding the state of data journalism in Arab countries and suggests several applicable ways to develop data journalism practices and education.

Evolving data teams: Tensions between organisational structure and professional subculture

This study explores the integration of data journalism within three European legacy news organisations through the lens of organisational structure and professional culture. Interviews with data journalists and editors suggest that professional routines resonate with established data journalism epistemologies, values, and norms that appear to be constitutional for an inter-organisational data journalism subculture. At the same time, organisational structure either integrates the journalistic subculture by increasing levels of complexity, formalisation, and centralisation or rejects it by not accommodating it structurally or culturally. The three data teams work along epistemologies of computer-assisted reporting, investigative journalism, and data journalism but differentiate themselves through nuanced understandings of data journalism practice, driven by individual journalists. After a structureless episode, one team sets itself apart as it diverges from data-driven routines and orients itself towards technological and interdisciplinary interactive journalism. The findings show an interdependence of individual efforts, varying conceptualisations of data journalism practice, and interplay between organisational structure and professional culture.

The Inapplicability of Objectivity: Understanding the Work of Data Journalism

ABSTRACT Data journalism is an emerging form of journalism, entailing the discovery of stories in data with the assistance of data algorithms. The burgeoning literature has largely interpreted the work of data journalism through the lens of objectivity. This paper, however, rejects the applicability of objectivity to data journalism. This inapplicability is the product of five factors: the extensive use of data and data algorithms in journalism; the difficulty in verifying data; the imbalance in data and data access; the uncertainty about if and to what extent data journalists can obtain sufficient knowledge of data contexts and algorithms; and their “design subjectivity” in the data processing process. Data reporting becomes a process of knowledge construction under the influence of these factors. The article argues that because of the social constructionist nature of data journalism, serving the public interest and democracy is a more appropriate principle than objectivity for data journalism. It suggests shifting academic attention from celebrating objectivity in data journalism to examining the epistemology of data journalists, the factors influencing data journalists’ formation of knowledge in reporting, their defence of cultural authority, and the democratic meanings of data reports in future research. Such understanding also has implications for data journalism pedagogy and practice.

Increasing Accountability Using Data Journalism: Challenges for the Pakistani Journalists

ABSTRACT A distinct era of data-driven reporting is on rise – a period when software, algorithms, programming, and data-processing techniques are being used by media organizations, especially in many developed countries of the world. Amid the increased practice of data journalism, it is imperative to analyse how journalists can use it for holding the power holders accountable, particularly in authoritarian and competitive authoritarian regimes where democratic norms are often abused and access to information is constrained. Drawing on the new institutionalism theory, thus this study aims to analyse the ability of Pakistan’s journalists to practice data journalism and to explore challenges that they face in the practice of data-driven reporting. To address this aim, this study uses the qualitative methods of document review and in-depth interviews (face-to-face). This study uses thematic analysis to offer insights into the gathered data.

Dadificação e Transdisciplinaridade nos Estudos do Letramento: O Jornalismo de Dados como Contexto de Pesquisa

Aborda-se o conceito e a prática do letramento de dados, visando caracterizá-lo como instanciação da transdisciplinaridade do(s) letramento(s) em sentido mais geral, apresentando-se, a partir dessa caracterização, perguntas e hipóteses de uma proposta de pesquisa focada no jornalismo de dados. Situamos a discussão no contexto da dadificação digitalizada da atividade social, argumentando que ela afeta a formulação de opiniões e argumentos baseados em textos jornalísticos que caracteriza o exercício da cidadania na esfera pública. Nossa pesquisa bibliográfica evidenciou que, embora predominem concepções de letramento de dados de natureza funcional e/ou baseada em habilidades (disciplinares), há também propostas baseadas no modelo ideológico/sociocultural do letramento. Concluímos apresentando a hipótese de que, nas práticas de jornalismo de dados, haveria uma tendência à subordinação das interpretações qualitativas aos saberes quantitativos, mas que se podem criar situações em que as lacunas disciplinares evidenciam o caráter transdisciplinar dos textos e dos eventos para os próprios produtores e leitores.

Data Journalism Sustainability

During its period of rapid growth, data journalism was poised to position journalism as society’s watchdog once again. But despite eager predictions, its rate of adoption outside large news organisations remains low, limiting the consolidation of data journalism to a normative practice. Through Scenario Network Mapping, this article seeks to outline the possible futures of data journalism practice by determining its sustainability in the current climate of journalism austerity. Results suggest three possible scenarios: (1) As a skillset, data journalism will soon be regarded as essential for every professional journalist. (2) As a genre, data journalism will remain a niche storytelling format but will ultimately find its way into smaller newsrooms due to decreasing limitations. (3) Due to financial and personnel limitations, data journalism will be abandoned by the mainstream media, who will outsource data analysis to non-legacy actors. Within this context, it remains to be seen whether data journalism can continue innovating in order to remain competitive in the constantly evolving ecosystem of today’s news production.

The Promise of the Transparency Culture

In 2013, with the introduction of the Transparency Law in Spain, a number of Spanish newsrooms started working with data journalism methods. In Sweden, which has one of the oldest Freedom of Information acts in the world, newsrooms invested in the skill development of data journalism at approximately the same time. Because previous research suggests that access to public data has been one of the key driving forces for the development of data journalism worldwide, it is important to understand how legislation is actually shaping the practice of data journalism. Based on a survey of 66 key informants in Spain and Sweden and ten in-depth interviews with data journalists from five media companies in each country, we conducted a comparative study, building on the frameworks of media systems to explore data journalism practices in these two countries. The differences found indicate that the national and EU legislation in both nations shape journalistic strategies for accessing data, turning journalists at times into activists fighting for the right to access public data. Beyond the law, data journalists advocate for a transparency culture among the civil servants, in order to secure public accountability.

Data Journalism Teaching, Fast and Slow

This commentary draws on a decade’s experience of teaching data journalism within a variety of contexts to describe the lessons learned regarding different pedagogical techniques and choices about the aspects of data journalism to teach. What emerges is a difference between classes aimed at a general audience, who might be sceptical and/or ignorant of the diversity of data journalism practice and those aimed at a more specialist audience aiming to go into the increasing numbers of roles dedicated to data-driven techniques.

Representation of data journalism practices in the South Korean and US television news

Few studies have investigated how television news is represented through data journalism. To fill this gap, this study compared data news content from South Korean and that from US television networks using the grounded theory method. The following differences were found: South Korean television networks ( KBS, SBS, MBC, and JTBC) highlight social issues, politics, and lifestyle; while American television networks ( ABC, CBS, NBC, CNN) cover the economy, social issues, and politics. Both television networks rely on government sources and seldom provide raw data. The South Korean networks use a static graph and an infographic most frequently, while the US networks favor a number pull quote and a static graphic. The South Korean networks prefer complex, visually appealing elements (e.g., an infographic), while the American networks prefer less complex and less visually appealing elements (e.g., a number pull quote). The South Korean networks prefer the news forms of ‘visualization,’ ‘condensity,’ and ‘typification,’ and the US networks prefer ‘visualization,’ ‘typification,’ ‘condensity,’ and ‘completeness.’ The degree of user participation is extremely low in both countries’ networks.

Does Data Journalism Matter for Social Media Users? : Users’ Perspectives on Digital Data-Based News

News organizations apply data journalism practices to producing quantified digital content (e.g., text in an interactive map). However, it is unclear how social media users understand this trend. The study examines how need for quantified news, credibility of digital data-based news, and information seeking through social media influence the usage of digital data. Findings indicate that the need for quantified news and the perceived credibility influence the news tweeting through intention to utilize digital data in news. Information seeking affects the intention to utilize digital data, and it directly influences the news tweeting. These relationships are consistent across two samples.

Patterns in Award Winning Data Storytelling

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.

Data Journalism: The Type of Communication, Features and Significance in Mobile News Client

Data journalism is an important direction of the current breakthrough in journalism. In the specific journalism practice, there are more front-line reporters and the media began to use the data journalism to explore the news events, so that news reports obtained re-energized. However, with the continuous development of technology and the growing popularity of smart phones, mobile media on the development of data journalism practice cannot be ignored. This paper attempts to sort out the development of data movement practice on the mobile side, so as to explore the innovation path of the development of data journalism communication under the background of big data age.

The datafication of data journalism scholarship: Focal points, methods, and research propositions for the investigation of data-intensive newswork

This article explores the existing research literature on data journalism. Over the past years, this emerging journalistic practice has attracted significant attention from researchers in different fields and produced an increasing number of publications across a variety of channels. To better understand its current state, we surveyed the published academic literature between 1996 and 2015 and selected a corpus of 40 scholarly works that studied data journalism and related practices empirically. Analyzing this corpus with both quantitative and qualitative techniques allowed us to clarify the development of the literature, influential publications, and possible gaps in the research caused by the recurring use of particular theoretical frameworks and research designs. This article closes with proposals for future research in the field of data-intensive newswork.