Q&A: How is data journalism changing the newsroom?

Q&A: How is data journalism changing the newsroom?

Q&A: How is data journalism changing the newsroom?

Big data and its analysis is impacting every industry, and the media is no exception. Dr Bahareh Heravi, who is conducting research on data journalism, wants to learn more.

Dr Bahareh Heravi is inviting all Irish journalists, editors and newsrooms to take part in the 2017 Global Data Journalism study.

Though data’s presence and purpose in newsrooms around the world has grown, there is a lack of systematic research in this domain, and a divide between academic and industry practices.

Heravi has lectured on data journalism in several Irish universities and institutions, including NUI Galway and Dublin City University. Currently an assistant professor in information and communication studies at University College Dublin, she answered our questions on data journalism, the study, and how newsrooms stand to benefit from the presence of data scientists.

You will probably find different definitions of data journalism if you look into different books and resources. But, to put it in simple terms, I would say data journalism is about 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.

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In data journalism data is your source, and computational methods and applications are the tools to aid you in journalistic work. I think it is important to mention that, like any other journalistic work, data journalism is about the investigation, the story, and communication of that story to the public.

Even though data journalism has been an emerging area in the past five to 10 years, it is not an entirely new phenomenon. We have had journalists using numbers and statistics for finding and telling stories for many years. They have also used data visualisation, mostly hand-drawn, as a means for communicating stories to the public since the 19th century.

Data journalism is essentially an evolution of what was called computer-assisted reporting in the 1960s. Computer-assisted reporting (CAR) was mostly about the use of computers – and, specifically, databases – in journalistic work. In the 1990s, a new term was coined for using statistics and social science methods in journalism, which was called precision journalism.

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The main force that has given rise to data journalism recently is the amount of data generated these days, accessibility to these data, and also the advancement, accessibility and ease of use of computing powers and computational tools in the past decade. Like many other disciplines that have been subject to change and many advancements as a result of access to this huge volume of data and computational power, journalism also is going through a change and needs to make the best out of these new available sources and tools.

Journalists are used to looking at the world around them, find interesting stories, or investigating areas of public interest, and telling stories about those in order to inform the public. A good journalist is often a journalist who knows her beat and her sources, and one who can make the best out of those.

Now that we have petabytes and zettabytes of data being generated on an hourly basis, our sources are altered – or, better say, are enhanced. We are now given access to a whole new and rather unlimited set of sources, and we have the opportunity to find interesting and unique stories in these new sources – the data sources.

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Here, it is perhaps worth noting that data is not equal to numbers. This seems to be a common misconception. All the textual data, images, videos and audio that we are generating every day are data too, and mining these data – and, particularly, mining and analysing textual data – can also result in interesting data stories.

Perhaps the main reason behind this misconception is that, historically, we have known how to analyse numbers and we have had access to powerful statistical analysis tools for years.


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