What Types Of Journalism Have Emerged From The Continuous Publishing Of Increasing Data? How Do These Digital Assemblages Function?
Much like news develops and is disseminated continuously on a 24-hour cycle through multiplatform journalism, data is continuously produced, collected, and disseminated via invisible flows made visible by various platforms such as traditional graphs or dynamic visualisations. In a contemporary media scape where web platforms such as Twitter and media forms such as iPhones and ‘Smart Phones’ afford producers and consumers with instantaneous sharing of information, to say that the relationship between data and media is “an unrequited love” is a misconception.
Data and media have always had close-knit relationship. In fact, news media is data. While modern tools such as Twitter have heavily exemplified how flows of data are integral to contemporary journalism, data gathering and publishing has always been an intergral to the practice. The journalist conducts interviews and researches through different pools of data in order to provide a balanced, truthful and factual report. Feature writing involves a more ethnographical experience as the journalist obtains more experiential data through ethnographic research. Investigative journalism combines both ethnographic and statisitcal data research in which journalists sift through lots of data to expose misconduct.
Yet, what we are seeing in the contemporary mediascape is that new-media platforms are accentuating this relationship and making it more transparent and prominent in different ways because data availability has risen exponentially since the beginning of the digital age .
According to Tim Berner-Lee, the founder of the internet, analysing data is the future of journalism:
“Journalists need to be data-savvy… [it’s] going to be about poring over data and equipping yourself with the tools to analyse it and picking out what’s interesting. And keeping it in perspective, helping people out by really seeing where it all fits together, and what’s going on in the country” (Arthur, 2010).
Data-driven Journalism is based on analysing and filtering large sets of data in order to find a story. It deals with freely available, open data and is analysed using open source tools. The primary goal is to transform the data into journalistic news stories (Lorenz 2010; Wikimedia 2012).
Coincidently, the process of data-driven journalism can be described through an ‘inverted pyramid’ understanding, similar to how the structure of a news report is described as being an inverted pyramid structure. Bradshaw’s (2011) model is summarised as follows:
- Find: Searching for data on the web
- Clean: Process to filter and transform data, preparation for visualization
- Visualize: Displaying the pattern, either as a static or animated visual
- Publish: Integrating the visuals, attaching data to stories
- Distribute: Enabling access on a variety of devices, such as the web, tablets and mobile
- Measure: Tracking usage of data stories over time and across the spectrum of uses (Wikimedia, 2012)
Simon Rogers of The Guardian provides a 10-point guide to data-journalism in the blog ‘Data journalism at the Guardian: what is it and how do we do it?‘:
- Data is “Trendy, but not new”: essentially, data has always been published, but now it can be published in various digital and online platforms.
- Open-data means Open-data journalism: data is available for anyone to take and make a story out of. There is a diversity of sources.
- Curation: Data is sometimes curated as journalists have to sift through large amounts of data, which is a lengthy process.
- Bigger Datasets, Smaller Things: large amounts of data available about small things.
Data journalism is 80% perspiration, 10% great idea, 10% output
Long and Short-Form: new short-form data journalism emerging where only the key points are extrapolated from research and readers are guided by it while it is still in the news.
Anyone Can Do It: there is a wide range of data collecting and publishing tools available across the internet for people to search and present findings of research.
Looks Can Be Everything: the way data is visualised and presented is important. Clarity and good design makes data more appealing and easy to understand
You Don’t Have To Be A Programmer: Think about data like a journalist, not an analyst.
It’s All About The Story/Stories: Data-journalism is not about graphics and visualisations, but the storytelling, and how the story is told. (Rogers 2011)
In my previous posts I’ve spoken about the premise of open journalism, and The Guardian’s Open Journalism initiative. Essential to the concept of open journalism is the of encouraging an active audience who get out there and obtain primary data and raw footage from events in order to convey the most accurate, factual and rich news reports, and to encourage public debate.
The practice of journalism allows journalists the opportunity to decrease their data searching and sifting workload by letting the public get involved. Furthermore, with the advent of Twitter and use of multimedia, various perspectives on events can be conveyed, which can be then used to find out what is spin and what is truth.
Not only does data increase, but the avenues from which we obtain data expand. This actants in this assemblage are the news organisations, the journalists, the public, and the various media used in order to collect, analyse, distribute, and visualise data (just to highlight a few). This ecology reflects both notions of technological determinism and cultural imperialism, as technology affords the people the ability to convey information and data in a certain way, and at the same time, it is the way in which we use these media that determines how data is produced and consumed.
Arthur, C 2010, ‘Analsying data is the future for journalists, says Tim Berners-Lee’, The Guardian, 22 November, <http://www.guardian.co.uk/media/2010/nov/22/data-analysis-tim-berners-lee>
Bradshaw, P 2011, ‘The Inverted Pyramid of Data Journalism’, Online Journalism Blog, posted 11 July, <http://onlinejournalismblog.com/2011/07/07/the-inverted-pyramid-of-data-journalism/>
Charalambous, L. 2011, ‘Assembling Publishing Publics: What is the Relationship Between Different Publishing Tools & Techniques & The Social In “Publishing Assemblages”?’, Transitioning Publics & Publishing – ARTS2090, March 20, <http://publishingintransition.wordpress.com/tag/actor-network-theory/>
The Guardian 2012, ‘Guardian Open Journalism – Three Little Pigs Advert’, Youtube, published 29 Feb 2012, <http://youtu.be/vDGrfhJH1P4>
Hughes, N. 2011, ‘Data Journalism: The Story So Far’, Data Mining UK, Blog, May 3, <https://datamineruk.wordpress.com/2011/05/03/data-journalism-the-story-so-far/>
Rogers, S. 2011, ‘Data journalism at the Guardian: what is it and how do we do it?’, The Guardian, Datablog, July 28, <http://www.guardian.co.uk/news/datablog/2011/jul/28/data-journalism>
Quilty-Harper, C. 2010, ’10 ways data is changing how we live’, The Telegraph, August 25, <http://www.telegraph.co.uk/technology/7963311/10-ways-data-is-changing-how-we-live.html>
Wikimedia 2012, ‘Data-Driven Journalism’,Wikipedia, last updated 29 March 2012, <http://en.wikipedia.org/wiki/Data_driven_journalism#Inverted_pyramid_of_data_journalism>
- Lorenz, Mirko (2010) Data driven journalism: What is there to learn? Edited conference documentation, based on presentations of participants, 24 August 2010, Amsterdam, The Netherlands
- Lorenz, Mirko. (2010). Data driven journalism: What is there to learn? Presented at IJ-7 Innovation Journalism Conference, 7–9 June 2010, Stanford, CA