Data Journalism: redefining community awareness and decision making in Sudan
By: Ahmed El-Affendi
Tags: Journalism, Writing, Data Journalism, Sudan, Data Science

The concept of data journalism is allowing data to pave context and build in credibility to the story. Datasets can be found ready made in the internet, or created by extracting it from multimedia files (pdf, videos, audio) or from people through a series of interviews, analysis, research and any other means of discovery which will result in a wholesome set of information to be used as a point of reference for readers, communities, governments, etc.

Its process has a series of steps that anyone can learn and master.[ It has unlimited uses and benefits, and has a huge positive impact on the communities and readers. There are some essential tools for data journalism.

This field isn’t new, it’s just trendy. There’re a number of professionals in this field that you should follow where they could provide further insight on data journalism.

Alex Howard defined it as: “gathering, cleaning, organizing, analyzing, visualizing and publishing data to support the creation of acts of journalism.”

The Data

I’m not going to define what data is in this section , but I’ll be giving you brief case studies and demonstrate data in a more digestible light.

Not all official data sources are reliable, accurate, or correct. This can be solved by getting the officials’ people’s attention to this matter, so that they can fix it. You can do this by writing an article about it by the way!

As it will require a huge effort, a master plan, and a budge. However, institutions with a capability to satisfy these factors can change and improve data sources for a better and wider use.

To bring this to light on an individual level, one can use whatever at his/her disposal to resolve the facts such as blogging or social media.

The best way that you acquire data is to create your own datasets from scratch. Only then you’ll be sure that you got what want. You can create big datasets about the smallest things around the world.

Moreover, the most important thing is how will you visualize the data because it might be the most important aspect of all. The colors, the graph type, the scales and etc. It should be readable, understandable and digestible for your readers.

When discovering data, you should look at it from a wider angle and provide alternative stories to it. Be sceptic, but not cynic about the data. Do not interpret the data, but rather let it speak by itself. Uncertainty is good because you might not have the answer, or the best answer, and you get to ask more questions and discover more. The investigation in itself is a story.

“Data is not the whole story because the people are the main source. Interviews are still crucial . A clear example that emphasizes this claim is when there was a story about real estate deals made by investors in family houses. It was noticed that there was this one particular house in the dataset that was exchanged multiple times, and the people involved in these multiple transactions of this one house were interviewed, the story became richer and more amusing! Data helps journalists to verify claims, tackle bigger stories, find new stories, illuminate murky issues, report more efficiently.” Ben Casselman from the New York Times

What data isn’t:

According to the Guardian, data is not: a force unto itself, speak for itself, power by itself, a perfect reflection of the world, or easy to interpret .

R-Programming Language, Python Programming Language, Tableau Software, Power Bi Software, and Web Scrapping Tools are all useful software tools that you’ll need to learn in order to becomes a data journalist.

“I ask myself whether the numbers I’m looking at will start a new conversation that people aren’t having yet, or if they will add to an existing conversation in a valuable way. If the answer to both of those questions is no, then I don’t bother to write the piece.” Mona Chalabi

Data journalism process is 80% perspiration, 10% great ideas, and 10% output. It can be either a long investigative process, or a short one that covers only key data.[1]

History of Data Journalism

Data journalism is very old. You can take a look at Florence Nightingale (1858), and at John Snow’s Cholera Visualization.