ChapterPDF Available

Data Journalism in 2017: A Summary of Results from the Global Data Journalism Survey

Authors:
Bahareh Heravi at University of Surrey
Bahareh Heravi
Download full-text PDF
Read full-text
Download citation

Abstract

This paper is open access on Springer: https://link.springer.com/chapter/10.1007/978-3-319-78105-1_13
Content uploaded by Bahareh Heravi
Author content
All content in this area was uploaded by Bahareh Heravi on Nov 04, 2019
Content may be subject to copyright.
Data Journalism in 2017: A Summary
of Results from the Global Data Journalism
Survey
Bahareh R. Heravi
(&)
School of Information and Communication Studies, University College Dublin,
Dublin, Ireland
Bahareh.Heravi@ucd.ie
Abstract. Data journalism is an emerging discipline, which as a practice it is
rapidly becoming an integral part of many newsrooms. Despite this growth,
there is a lack of systematic research in this area to reveal the best practices,
knowledge sets, and skills required to develop the discipline. To address this
gap, this paper presents a brief overview of the results of the first Global Data
Journalism Survey, which includes the participation of journalists from 43
countries. Presented results shed light on a variety of aspects of data journalism
practice across the globe, including demographics, skills, education, and for-
mation of data teams, as well as the opportunities and values associated with
data journalism.
Keywords: Data journalism Data-driven journalism Journalism
Computer assisted reporting Precision journalism
Global Data Journalism Survey
1 Introduction
Data journalism is an emerging discipline, which –amongst other definitions [1,2]–is
defined as ‘finding stories in data –stories that are of interest to the public –and
presenting these stories in the most appropriate manner for public use and reuse’[3,4].
Similar to other journalistic practices, data journalism puts the tenets of journalism first:
the investigation, the story, and communication of that story to the public. In data
journalism, data is the source, and computational methods and applications are the tools
to aid journalists in their work [3,4].
Data journalism practice has been growing in the past 10 years. Despite this
growth, there is a lack of systematic research in this domain, and a divide between
academic and industry practices. Ausserhofer et al.’s[5] analysis of Data Journalism
literature suggests an increase of research publications on data journalism and related
fields since 2010. They note that although CAR (Computer Assisted Reporting) has
been practiced since the 1960s, the scientific investigation of it, also, has started only
recently.
©Springer International Publishing AG, part of Springer Nature 2018
G. Chowdhury et al. (Eds.): iConference 2018, LNCS 10766, pp. 107–113, 2018.
https://doi.org/10.1007/978-3-319-78105-1_13
To address this gap, the paper in hand presents a summary of the results of the first
Global Data Journalism Survey
1
, which studies the current state of data journalism in
newsrooms across the globe, with a focus on knowledge, education and journalistic
values when it comes to the practice of data journalism.
2 Method
This study was conducted through a survey, titled the Global Data Journalism Survey.
The survey questions were designed in a collaboration between academic and industry
partners, namely by the author and Mirko Lorenz, who is the Founder of Datawrapper
and Innovation Manager at Deutsche Welle Innovation, following a set of interviews
with industry experts. The survey consisted of 48 questions in 7 sections.
The survey was launched on the 3rd December 2016 and closed on the 10th May
2017. It was open to all data journalists and journalists globally. The survey was limited
to those who identify as having worked as a journalist or a data journalist in the past
year. It was carried out using the online Google Forms and was circulated and promoted
as broadly as possible through various platforms and channels. A link to the survey was
distributed widely through social media channels and relevant listservs, two Slack
groups - News Nerdy and DJA 2017 - and a number of articles about the survey featured
in the media [3,6,7]. This survey was conducted following an ethical approval from the
University College Dublin’s Research Ethics Committee.
3 Findings
Two hundred and six participants from 43 countries participated in this survey, with
181 respondents filling it out to completion. Given that the survey was circulated and
promoted online, a definitive understanding of the total population size in not possible.
However, as an indication of the size of the data journalism community, a data col-
lection from LinkedIn on the terms “data journalist”,“data journalism”and ‘“computer
assisted reporting”OR “CAR”’ on ‘current jobs’, at the time of the closing of the
survey, returned a total of 463 journalists listed in these positions. This figure provides
us with a crude estimate of the population size of the data journalism community.
Considering the small community of data journalists, the data collected in this survey is
considered to be a representative sample.
For the purpose of analysing the results, only responses completed to the end were
considered and the rest were discarded.
3.1 Demographics and Newsroom Practices
The majority of participants were from the young, but not so young, generation of
journalists with almost 75% being between 25 and 44 years old. Sixty-four per cent
(64%) of participating journalists were in full time employment, while 18% were
1
This survey was ran by Bahareh Heravi and Mirko Lorenz.
108 B. R. Heravi
freelancers, 12% in part time employment as journalists, and 4% were casual/retainer.
Thirty-two per cent (32%) of participants worked in large organisations of 500+
employees, 22% in organisations of size 10–49, 17% in organisations with 100–499
employees, 15% in small organisations of 2–9 employees and only 8% in mid-sized
organisations of 50–99 employees. Forty-two per cent (42%) of participants worked in
national organisations, 20% in local, 18% in international and the rest in a combination
of these types, or other types of organisations. In terms of gender, 57.5% of our
participants identified as male and 42.5% as female.
Tapping into experience, a majority of respondents (78%) were individuals with 1–
10 years experience as a journalist with breakdown of 2% having less than a year
experience, 41% having 1–4 years experience and 26% 5–9 years. Nineteen per cent
(19%) of participants had 10–19 years experience and only 11% had over 20 years
experience as a journalist.
In terms of content production, 43% of participating journalists produced content
for online platforms of broadcast or print media outlets and 34% produced content for
online-only publications. This makes a total 77% of all participants producing content
for online publications. This figure is followed by print newspaper (8%), radio (4%),
TV (4%), print magazines (3%), personal blog (2%) and producing content for news
agencies made only 1% of the total.
We asked our participants about the status of data journalism in their organisations.
Forty-six per cent (46%) claimed that they have a dedicated data desk/team/unit/blog/
section. This figure was followed by 29% who expressed that they do not have a
dedicated data desk/team/unit/blog/section, but publish data driven projects on a reg-
ular basis. Seven per cent (7%) of participants noted that they plan to work with data in
the next six months and another 7% expressed that they have no immediate plan to start
working with data. Of those who indicated they have a dedicated data
desk/team/unit/blog/section in their organisations, 40% had a data team consisting of
3–5 people and 30% had a team of 1–2 people. This means a vast majority (70%) of
organisations with data teams operate with small teams of 1–5. On the other side of the
spectrum 22% of participating organisations had data teams of 6–10 people, 3% had a
team of 11–15 people, and 5% had large data teams of more than 15 people.
When we asked journalists about the main hurdles in implementing data journalism
in their organisations (they could choose more than one), 52% identified ‘lack of
resources’as the main hurdle, followed by 44% indicating that ‘lack of adequate
knowledge’was the main hurdle. Furthermore 40% believed that lack of time con-
tributes to not being able to implement data journalism in their organisation.
3.2 Knowledge and Education
With an interest in education in this emerging area, we peeked into knowledge –which
was rated as the second biggest hurdle in implementing data journalism –and edu-
cation. Results show that while 86% of participants considered themselves as data
journalists, in terms of data journalism proficiency only 18% rated themselves as
experts in data journalism. Another 44% identified as having a better than average
knowledge in data journalism and 26% identified as having average knowledge in the
Data Journalism in 2017 109
field. Nearly 13% of participants identified as novice or below average level of
expertise in the field.
In terms of formal training, half of our participants (50%) had formal training in
data journalism and the other half did not. With regard to a wider understanding of
formal training in knowledge areas used in data journalism practices, most participants
demonstrated a high degree of formal training in journalism, with less formal training in
the more data oriented and technical aspects such as data analysis, statistics, coding,
data science, machine learning and data visualisation. Figure 1presents the breakdown
of formal training in related fields.
In terms of education level, 97% of respondents had a university degree, with a
breakdown of 40% university graduate (bachelor) level, 54% postgraduate level and
3% with a doctorate or above degrees. Looking into the degrees obtained by these
participants, a 62% majority were formally educated in Journalism at the university
level. This is followed by a combination of other degrees: Politics (15%),
Computer/Information/Data Science/Engineering (12%) and Communication and
Language/Literature each 10.5%, with 26% listing a combination of other degrees.
3.3 What Data Skills Are Journalists Interested to Learn?
To address the knowledge gap highlighted in the responses from participating jour-
nalists, we studied education needs in this sector. A remarkably high portion of par-
ticipants in the survey (98%), expressed that they were interested in acquiring further
skills to practice data journalism, with 81% being *very* interested. While nearly all
participating journalists were interested in acquiring further skills, merely 42%
expressed that they are interested in more formal higher education degrees in this area.
However, if the training offered is shorter-term or more flexible, a striking 74% of
participating journalists express interest in formal training in higher education, e.g. a
postgraduate certificate or higher education diplomas.
In terms of specific data skills journalists are interested to acquire (Fig. 2), data
analysis presented itself as the top skill, with 64% of individuals expressing interest in
learning about it. This was marginally followed by learning “how to programme/code”
at 63% and visualising data at 51%. These top three data skills were followed by
another three skills: “how to clean data”,“how to develop data-driven applications”
and to learn “how to check if data is reliable”, with over 48% of journalists expressing
interest in each.
Fig. 1. Level of formal training in related knowledge fields, N=181
110 B. R. Heravi
3.4 Values Associated with Journalism and Newsroom Production
The topic of using data as a source, and means, of reporting has struck various debates
around journalistic practices and associated values, e.g. [2,8–10]. To study how
journalists think about the values associated with journalism, and the inevitable
requirements of viable story production in newsrooms, we asked our participants a
series of questions covering a number of aspects associated, including topics of
quantity and quality of data journalism storied published.
Sixty-five per cent (65%) of the respondents ‘somehow agreed’or ‘strongly agreed’
that data journalism allows them or their organisation to produce more stories. On the
end of the spectrum 13% ‘somewhat disagreed’(10%) or ‘strongly disagreed’(3%)
with this statement.
Moving from quantity to quality, 90% of respondents ‘agreed somewhat’(21%) or
‘strongly agreed’(69%) that data driven journalism adds rigour to journalism, with
only 5% expressing the opposite. Similarly 91% ‘agreed’or ‘strongly agreed’that data
journalism improves the quality of journalistic work in their organisation, with only 4%
believing the opposite (Fig. 3).
Tapping into traditional journalistic values, while leaving the definition of these
values to the participants, 83% of participating journalists ‘disagreed somewhat’or
‘strongly disagreed’that data journalism undermines traditional journalistic values,
Fig. 2. Interest in acquiring skills listed skills (%), N=181
Fig. 3. Data Journalism, quantity, quality, rigour, opportunities and values (%),N=181
Data Journalism in 2017 111
while only 11% ‘agreed somewhat’or ‘strongly agreed’that data journalism is
undermining these values. On a final note, 70% of participants expressed that they will
not be able to carry out their work without data as a source.
4 Conclusion
Data journalism is an emerging discipline, which has evolved tremendously in the past
few years, and is rapidly becoming an integral practice in many newsrooms. Despite
this growth, there is little known about the best practices, knowledge sets, skills, and
more importantly opportunities, values and the ways to go forward in this discipline.
To address this gap, this paper presented a brief overview of the results of the first
Global Data Journalism Survey.
The results show that the data journalism community is a highly educated com-
munity, and it has its roots mostly in journalism and communication degrees, and less
so in data/information and computer related disciplines. Additionally journalists
engaged in data journalism form a younger cohort of journalists, with fewer than 10
years experience as a journalist. While technical, data analytics and statistical skills do
not appears to be the strength of participating journalists put next to their journalism
background, it appears that many newsrooms already have dedicated data team and/or
produce data driven stories on a regular basis. This study further reveals that despite
debates in the use of data for producing journalistic work, both in terms of quantity and
quality, a vast majority of journalists believe that data journalism allows them to create
more stories in terms of quantity, which are also more rigorous and of higher quality.
This paper presented a brief overview of the data collected in the Global Data
Journalism Survey. A further, more detailed, analysis of the results will take place in
the future.
References
1. Berret, C., Phillips, C.: Teaching Data and Computational Journalism. Knight Foundation,
New York (2016)
2. Howard, A.: The Art and Science of Data-Driven Journalism. Knight Foundation, New York
(2014)
3. SiliconRepublic: How is Data Journalism Changing the Newsroom? Q&A with Bahareh
Heravi (2016)
4. Heravi, B.: Teaching data journalism. In: Mair, J., Keeble, R., Lucero, M., Moore, M. (eds.)
Data Journalism: Past Present and Future. Abramis Academic Publishing, Bury St Edmunds
(2017)
5. Ausserhofer, J., Gutounig, R., Oppermann, M., Matiasek, S., Goldgruber, E.: The
datafication of data journalism scholarship: focal points, methods, and research propositions
for the investigation of data-intensive. Journalism (2017)
6. Lorenz, M.: What is the current status of data journalism? Participate in our global survey to
find out (2016)
7. Plaum, A.: Call for participation: global data journalism survey 2017 (2016). http://blogs.dw.
com/innovation/call-for-participation-global-data-journalism-survey-2017
112 B. R. Heravi
8. Diakopoulos, N.: Algorithmic accountability. Digit. J. 3, 398–415 (2015)
9. Satell, G.: This is why data journalism is failing (2014). https://www.forbes.com/sites/
gregsatell/2014/06/01/this-is-why-data-journalism-is-failing/
10. Houston, B.: Digging for truth with data: computer-assisted reporting. https://gijn.org/2015/
03/05/digging-for-truth-with-data-computer-assisted-reporting/
Data Journalism in 2017 113
... Many have covered large geographical areas: Fahmy and Attia (2020) in Arab Countries; Beiler, Irmer, and Breda (2020) and Appelgren and Salaverría (2018) in Europe; Gondwe and White (2021) in Africa; Zhang and Chen (2020) in Asia; Broussard and Boss (2018) in North America and the UK; Cunha (2020) and Arias-Robles and Carvajal (2022) in Latin America. The first global survey study was published by Heravi (2017). Another international study was conducted by Rogers, Schwabish, and Bowers (2017) at the Google News Lab. ...
... Together, these two findings suggest that the pandemic played an important role in expanding the workforce outside Western regions. Nonetheless, data journalists remain concentrated in wealthier nations, possibly due to better-funded newsrooms and more relevant educational pathways (Heravi 2017). ...
... Lack of training in more technical areas such as data analysis, statistics, and programming, as found in previous works (Faria Brandão 2019; Heravi 2017; Porlezza and Splendore 2019), could explain why so many respondents are self-taught in data journalism. This suggests a lack of options of formal education curricula in data journalism (Heravi 2017), or the unwillingness or inability of the workplace to offer specialised or technical training. One key aspect for the industry will be finding ways to train data journalists in the technical areas they feel they need to be upskilled in, as this can increase productivity and reduce workloads. ...
The Data Journalism Workforce: Demographics, Skills, Work Practices, and Challenges in the Aftermath of the COVID-19 Pandemic
Article
Full-text available
  • Mar 2023
In the last decade, data journalism has established itself as a thriving field. Recently, COVID-19 has boosted the demand for data-driven reporting to make sense of the pandemic, increasing the importance of studying the evolution of this rapidly evolving and technology-bounded practice. However, the number of efforts to map and systematically measure the data journalism industry are few. This paper analyses the findings of The State of the Data Journalism Survey 2021, currently the most extensive study on the characteristics surrounding the workforce producing and contributing to the data journalism industry. The outcome is an understanding of an expanding workforce with a geographically uneven distribution, which is still homogeneous in terms of tools and educational paths. Self-taught, resourceful, and multi-skilled, data journalists often work in isolation but share pressures of limited resources, time limitations, and access to quality data. The pandemic appears to have directly increased those struggles, although data journalists agree that the field’s reputation has ultimately benefited from it.
View
... realizado por el European Journalism Center, publicó en agosto de 2019 un artículo titulado "7 countries, 9 teachers: a dossier of data journalism teaching strategies. What are the most effective ways to introduce students to data?" (7 países, 9 profesores: un dossier de las estrategias docentes de periodismo de datos) en el que lamentablemente no se mencionaba el caso de España, pero sí que se apuntaban cuestiones comunes (Heravi, 2018). ...
... Por su parte, Bahareh Heravi, del University College Dublin (UCD) de Irlanda, comenta que pese al excepcional posicionamiento de su país en el sector de las tecnologías de la información y del conocimiento, como sede de muchas empresas tecnológicas de la región europea, no ha desarrollado tanto como Reino Unido o Alemania el periodismo de datos. Para elegir el tipo de formación a desarrollar realizó una encuesta durante cinco meses en colaboración con Mirko Lorenz de Datawrapper y otros medios en la que pregunta qué tipo de periodismo de datos se practica para ver qué tipo de estudio se necesita, la "Global Data Journalism Survey" (Heravi, 2018) donde reciben 181 respuestas de 43 países. Luego estudió alrededor de 220 cursos relacionados con periodismo de datos de todo el mundo para concluir que debía realizar un posgraduado en periodismo de datos que denominaron UCD Data Journalism ProfCert 3 en 2017 en el que combinaron periodismo de datos con análisis de datos cuantitativos, estadística y R 4 , para finalizar con un sitio web del proyecto desarrollado durante el curso 5 y que, en la medida de lo posible, fueran publicados por algunos medios, como el "Personal Injury Claims in Ireland" 6 o "Most dangerous cities for Gardai" 7 . ...
... Tal como ocurría con los resultados de la encuesta global de periodismo de datos (Heravi, 2018) la mayoría de las apuestas coinciden en apartados del periodismo multimedia, redes sociales o producción web y poco en los conocimientos más técnicos como la programación, estadística, ciencia de datos o aprendizaje automático. Si se abordan, lo hacen a través de aplicaciones informáticas determinadas sin una visión global de conjunto. ...
Innovación en la docencia del periodismo a través de la ciencia de datos
Article
Full-text available
  • Jul 2021
El periodismo de datos moderno nace en 2008 con la confluencia de tres factores fundamentales: los renovados formatos de la Web, con HTML5 y CSS3 a la cabeza, la abundancia de software libre disponible para cada una de las etapas del proceso de investigación con datos y la apertura de portales de datos abiertos de los gobiernos. Para los periodistas uno de los retos fundamentales de este cambio tecnológico ha sido encontrar la formación adecuada. Existen diversas experiencias y enfoques en la educación periodística con datos; en este artículo se examina la docencia del periodismo de datos en España a través del análisis de las propuestas docentes en siete másteres impartidos por universidades españolas.
View
... El énfasis en el perfil y las rutinas profesionales del periodista, por lo tanto, también se ha extendido en la investigación académica sobre el periodismo de datos. El trabajo más ambicioso hasta la fecha probablemente sea la encuesta realizada por Heravi (2018) a 206 profesionales de 43 países, que refleja la necesidad de una mayor formación reglada en aspectos técnicos como el análisis de datos, la estadística, la programación, el machine learning o la visualización. Otro de los proyectos más destacados en este ámbito fue el liderado por Appelgren y Salaverría (2018), que encuestaron a 144 periodistas de datos (96 españoles y 84 suecos) en un estudio que resalta las grandes diferencias en transparencia pública entre ambos países. ...
... Con el de(Appelgren & Salaverría, 2017), dado que se centra principalmente en la visión de los profesionales sobre la transparencia informativa, la principal coincidencia radica en el uso de Twitter como una de las herramientas de contacto y confección de la muestra. El cotejo con los resultados mostrados por(Heravi, 2018) sí arroja más coincidencias, especialmente la juventud de muchos de los profesionales de esta especialidad, la mayor presencia en redacciones de medios de tamaño medio y la ubicación en cabeceras de tirada nacional y, por tanto, ubicadas principalmente en las capitales. ...
Periodistas de datos. Análisis del perfil sociodemográfico del profesional en España y Latinoamérica
Article
Full-text available
  • Feb 2022
El periodismo de datos se ha convertido en una de las especialidades profesionales más relevantes en la industria. Cada vez se publican más trabajos que abordan la disciplina desde múltiples puntos de vista, pero pocos han indagado en el perfil de los profesionales implicados, especialmente en el ámbito hispanohablante. Por eso este trabajo explora las características sociodemográficas de una muestra de profesionales en España y Latinoamérica mediante una metodología cuantitativa basada en una encuesta (n = 208), recogida en una base de datos abierta y publicada como directorio web (n = 296). Los primeros resultados reflejan que esta especialidad ocupa a más mujeres que hombres y, sobre todo, a más jóvenes que veteranos. Los datos obtenidos también muestran un mayor número de profesionales especializados en España y la concentración de estos puestos de trabajo en las principales urbes y capitales. Finalmente, se observa que los periodistas de datos suelen trabajar preferentemente en equipos pequeños, casi siempre de una o dos personas, y con frecuencia de manera freelance.
View
... The group 'coordination' counts 36 women and 25 men. Other groups traditionally considered more masculine, such as data journalism (Heravi, 2018), indicate that, in collaborative projects, women are at the front line in projects that deal with data. In groups 'data collection', 'data visualisation', and 'multimedia production', women outnumber men. ...
Collaborative Journalism and Normative Journalism: Intersections and implications of normative roles in the collaborative action of journalists, media practitioners and news organisations in Latin America
Thesis
Full-text available
  • Apr 2022
Declaration I hereby certify that this material, which I now submit for assessment on the programme of study leading to the award of PhD is entirely my own work, and that I have exercised reasonable care to ensure that the work is original, and does not to the best of my knowledge breach any law of copyright, and has not been taken from the work of others save and to the extent that such work has been cited and acknowledged within the text of my work. Signed:
View
... To make news reliable, realistic, scientific, and more credible, the news industry has started adopting digital data as a key resource for developing news stories. "Data journalism" is fairly a new term where a journalist finds stories in data that may be interesting to the public and present these stories most appropriately for public use and reuse (Heravi, 2017;2018). ...
“Making” the contemporary and next-generation journalist, through data journalism: The need for emerging curriculum in journalism education in India - A primary proposal
Article
Full-text available
  • Jan 2022
Like any other profession, the media and communication domains are also majorly robust with the advent of computers and information communication technologies. In the recent past, the concept of data journalism struck the chords of major news media houses across the globe. Data journalism is an evolving form of storytelling, where journalist works with data, data analytics software, and visualize data to narrate their news stories. In India, over the years, many academic institutions started offering certificate, diploma, undergraduate, postgraduate, and research programmes in journalism and communication-related fields. Currently, academic curricula and journalism education are strengthened with conventional journalism theories and practices. Due to the arrival of data journalism, modern tools, and techniques, journalism pedagogy faces a relatively large knowledge gap. This research article is an outcome of exploratory research that examined 155 academic institutions by scrutinizing the communication curriculum offered across India and suggests the need-based syllabi in consultation with academic and industrial experts, which entails data journalism as an empowering element for the current and next-generation journalists.
View
View
Data Journalism and Ethics: Best Practices in the Winning Projects (DJA, OJA and Sigma Awards)
Article
  • Sep 2021
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.
View
Exploring Data Visualisations: An Analytical Framework Based on Dimensional Components of Data Artefacts in Journalism
Article
Full-text available
  • Aug 2021
This study introduces a synthesised framework for the analysis of data visualisations in the news. Through a close examination of seminal content analyses, their methodologies and findings, this article proposes a framework that consolidates dimensional components of data visualisations previously scattered across this body of research. To transition from incidental and essentialist examinations of visual data artefacts towards a systematic and theory-informed exploration, we consider the diagrammatic dimensions of data visualisations. The offered synthesized framework can serve as a starting point for both theory-infused descriptive purposes as well as more theory-guided explorations. The framework is put to the test by analysing 185 visualisations drawn from award-winning data stories. Findings generated through the application of the framework highlight the varied composition of components of data visualisations, though certain combinations of components are prevalent, leading to static categorical comparisons or interactive spatial localization. After all, data artefacts can be understood as problem-posing elements that are the outcome of diagrammatic thinking that journalists employ to communicate claims.
View
View
Data Journalism Practices Globally: Skills, Education, Opportunities, and Values
Article
Full-text available
  • Oct 2020
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.
View
The Datafication of Data Journalism Scholarship: Focal Points, Methods and Research Propositions for the Investigation of Data-intensive Newswork
Article
Full-text available
  • Jul 2020
This paper 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. The article closes with proposals for future research in the field of data-intensive newswork.
View
Computer-assisted reporting tools
Article
Full-text available
  • Jan 1996
View
View
View
Call for participation: global data journalism survey
  • A Plaum
Plaum, A.: Call for participation: global data journalism survey 2017 (2016). http://blogs.dw. com/innovation/call-for-participation-global-data-journalism-survey-2017
This is why data journalism is failing
  • G Satell
Satell, G.: This is why data journalism is failing (2014). https://www.forbes.com/sites/ gregsatell/2014/06/01/this-is-why-data-journalism-is-failing/
What is the current status of data journalism? Participate in our global survey to find out
  • M Lorenz
Lorenz, M.: What is the current status of data journalism? Participate in our global survey to find out (2016)
Teaching Data and Computational Journalism. Knight Foundation
  • Jan 2016
  • C Berret
  • C Phillips
Berret, C., Phillips, C.: Teaching Data and Computational Journalism. Knight Foundation, New York (2016)
The Art and Science of Data-Driven Journalism. Knight Foundation
  • Jan 2014
  • A Howard
Howard, A.: The Art and Science of Data-Driven Journalism. Knight Foundation, New York (2014)
Teaching data journalism
  • Jan 2017
  • B Heravi
  • J Mair
  • R Keeble
  • M Lucero
Heravi, B.: Teaching data journalism. In: Mair, J., Keeble, R., Lucero, M., Moore, M. (eds.) Data Journalism: Past Present and Future. Abramis Academic Publishing, Bury St Edmunds (2017)