As
technology becomes an increasingly important part of society, graphics and data
have become to play a significant role in journalism. In order to facilitate
readers’ perception of information and increase accuracy of their own
reporting, journalists are looking for more effective methods of data
presentation. Further data helps to drill down into charts and graphs for more
detail, interactively changing what data you see and how it’s processed. Data was used for maps and graphs in the 17th century, while the pie chart was
invented in the early 1800s. One of the first examples of statistical based
graphics occurred when Charles Minard in 1869 mapped Napoleon’s 1812 invasion
of Russia. The map depicted the size of the army as well as the path of
Napoleon’s retreat from Moscow, and it tied that information to temperature and
time scales for a more in-depth understanding of the event (Tufte, 1983).
It’s
the entire process of deriving meaning from data to develop a story - not only
the visual output. A written story that relies on data analysis and
interpretation is a better example of data journalism than an info graphic with
dozens of meaningless numbers. More than anything, data is about stories that
play a direct role in people’s lives. Many data stories have the ability to not
only tell individual stories but also contextualize a story by placing a person
in his or her neighborhood or country. Data journalists do more than just sift
through mountains of data and identify trends. They can often provide a
creative perspective to a story which allows them to engage with new audiences.
While it’s true that data-driven stories can benefit from people with technical
and design skills, most of the work stems from an editorial understanding of a
subject. As long as you have an eye for a story and are willing to collaborate
with others, you can become a good data journalist.
Data
journalism is often referred to by various terms, such as data driven
journalism, computational journalism or computer – assisted reporting. An info
graphic or chart without an underlying story is not data journalism. A data
journalism project should involve the uncovering of a story from a dataset.
Within Al Jazeera we’ve produced award-winning data journalism projects with a
mobile phone, camera and computer (as will be demonstrated in our case study
below). While, longer-term investigative projects may take time and resources
to develop, there are many daily stories that newsrooms are producing that
involve analyzing and presenting data.
The
main ingredient to a successful data story is creativity. Data by itself is not
a story. It requires you to think creatively about what’s relevant to your
audience and what is not. On the flip side, a great story idea without data is
also not a data-driven story. Often, finding the right balance between what stories
you want to tell us. What data you have requires some trial and error. A
mistake a lot of inexperienced data journalists make is thinking that they need
to analyses big datasets to tell a story. A better approach is to start off
with smaller datasets and develop them over time. This will help develop
data-fluency and ensure more effort is placed on extracting the story’s
meaning.
The
very first Data Journalism awards by the Global Editors Network in 2012 have
also emphasized the importance of the investigative reporting tradition in data
journalism. It is also worth mentioning that the average amount of time used to
compose a story was several months, the longest period was seven years
(Burn-Murdoch 2012).
Importance of Data Journalism
According
to journalists, they are saying to filter the flow of data, data journalism is
very important. When information was scarce, most of our efforts were devoted
to hunting and gathering. Now that information is abundant, processing is more
important. Information is being processed at two levels: (1) analysis to bring
sense and structure out of the never-ending flow of data and (2) presentation
to get what’s important and relevant into the consumer’s head. Like science,
data journalism discloses its methods and presents its findings in a way that
can be verified by replication. Further Data journalism brings new approaches
to storytelling which is an umbrella
term that, to everyone’s mind, encompasses an ever-growing set of tools,
techniques and approaches to storytelling. It can include everything from
traditional computer-assisted reporting (using data as a ‘source’) to the most
cutting edge data visualization and news applications. The unifying goal is a
journalistic one: providing information and analysis to help inform us all
about important issues of the day.[3]
‘Data
journalism’ only differs from ‘words journalism’ in that we use a different
kit. We all sniff out, report, and relate stories for a living. It’s like
‘photo journalism’; just swap the camera for a laptop. Data-driven journalism
is the future. Journalists need to be data-savvy. It used to be that you would
get stories by chatting to people in bars, and it still might be that you’ll do
it that way some times. But now it’s also going to be about poring over data
and equipping yourself with the tools to analyze 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. Data journalism
serves two important purposes for news organizations: finding unique stories
(not from news wires) and execute your watchdog function. Especially in times
of financial peril, these are important goals for newspapers to achieve. Data
journalism is another way to scrutinise the world and hold the powers that be
to account. With an increasing amount of data available, now more than ever it
is important that journalists are of aware of data journalism techniques. This
should be a tool in the toolkit of any journalist: whether learning how to work
with data directly, or collaborating with someone who can.
