Open Data: Call to Journalists

By Rhoda Omenya
iHub Research
  Published 05 Sep 2012
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By Rhoda Omenya
Code 4 Kenya is a pilot experiment being carried out as part of the Open Data Pre Incubator, where four fellows and four developers have been embedded in three media organizations and one civil society organization. One of the objectives of this project is to motivate media houses and civil society to embrace open data in their reporting, particularly through Data-driven journalism.
Data journalism can be defined as a journalistic process based on analyzing and filtering large data sets for the purpose of creating a new story or enhancing an existing story.
The above image answers the who, what, why, when and where of journalism. . . Putting the above into intelligible speak is an excerpt drawn from "The Handbook of Independent Journalism:"

New technologies have made it possible for anyone with a computer to disseminate information as widely as the largest news organizations. But a well-designed Internet site, no matter how well it's written or how often it's updated, is not necessarily a reliable source of news. The truth is that in a complex world where information is no longer a scarce commodity, the role of the journalist has become more important than ever...

Unlike a propagandist or a gossip, the journalist sorts through the information available and determines how much of it is valuable and reliable before passing it on to the public. News stories, whether hard news or features, must be accurate. Journalists not only collect the information they need to tell the story, they have to verify the information before they can use it. Journalists rely on first-hand observation whenever possible and consult multiple sources to make sure the information they receive is reliable. And, except on rare occasions, they identify the sources of their information so the audience can evaluate its credibility.

Data Driven Journalism
It is an inherent nature of journalists to dig deeper, to “find the truth behind the truth”, and data-driven journalism is  one style of journalism that precisely does this. Given the free access to data through the open data initiative and the large numbers of datasets media organizations possess, it is an opportune time for both concerned citizens and journalists to join the Open Data bandwagon as data journalists. A paradigm shift in journalism has seen established media houses worldwide such as the Guardian embrace this new style of reporting. Data journalism essentially means churning out well analyzed stories that go up and beyond basic reporting, by referring to historical data and facts and relating them to present day occurrences, making a reader pose more questions while at the same time giving deeper insight into what would otherwise be a lacklustre story. Data journalism unearths fundamental realities about humanity by digging deeper than what journalists thought was possible before. Furthermore, this analysis can be done with open source tools and it strives to reach new levels of service for the public, helping consumers, managers, politicians to understand patterns and make decisions based on the findings. As such, data driven journalism might help to put journalists into an even more relevant role in society.
Data Journalism in the Kenyan Context
Using the below workflow by Mirko Lorenz, an information architect, journalist and trainer the basic data journalism process can be grafted into a Kenyan context:  
1. Data

A journalist has to find large amounts of data to be able to tell a story. This data can from his/her media organization, web searches, data that the journalist has collected himself or herself through surveys, etc and this data can also be from the Kenya Open Data portal. This data is then cleaned and structured (Cleaning can done by tools such as Google Refine or Google Spreadsheets - that allow uploading, extracting and formatting of data).

2. Filter

The searching of specific information from the cleaned data in the form of big variances or subtle nuances. The journalist has to interrogate to understand the terminology used, codes, all in context e.g. history and objectives of the study.

3. Visualize

The filter can then be mashed up to create new data which would create news stories for the journalist and finally put visualized as a map, in a chart, infographic, etc. One can use Many Eyes or Tableau Pulique as visualization tools.

4. Stories

The journalist now brings to light what he or she has discovered in the visualization thus telling the untold stories, discovering new angles to stories, telling a specific story or telling the story based on the bigger picture. Not just to tell stories for the sake, otherwise emphasis on data journalism would be irrelevant. The main goal of data journalism is to extract information, visualize, narrate, humanize and personalize the story so that recipients utilise it by acting on it and thereby influence matters related to policy and development.

The beginning word pictorial on journalism has so many words but yet lacks one so vital to journalism, DATA. The government has created the data portal, an experiment for data use is in progress, the onus is now on citizens and journalists to pick up the baton to bring data into the journalism picture, sustain its use and scale it in telling stories for change. The Code 4 Kenya team is also working towards creating sustainable and easy to use platforms and applications to further enhance citizen and data journalism while at the same time creating Open Data ecosystems. Suffice to say;


The mic is in your court . . .
FYI: Data journalism isn’t a new concept is you factor in the fact that Florence Nightingale used it to visualize mortality in the British army. Here’s the proof! To the occupation nurse, add applied statistician, data journalist. . .
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