Last updated
Last updated
Although it has many definitions, we can define data journalism as journalism with its simplest expression. Data journalism is the use of data and number crunching in journalism to uncover, better explain and/or provide context to a news story. According to the Data Journalism Handbook, data can be either the tool used to tell a story, the source upon which a story is based, or both. Data journalism involves the use of statistics, design, charts, graphs or infographics. Plus, as a mentioned above data journalism is follow-up of Computer-Assisted-Reporting (CAR) and Precision Journalism as defined by Philip Meyer in the early 70ies. It means finding stories by processing large datasets. Free online tools, open data now make it easy to manipulate, interpret and present numerical information.
For more specific definition is data journalism is a journalism specialty reflecting the increased role that numerical data is used in the production and distribution of information in the digital era. It reflects the increased interaction between content producers (journalist) and several other fields such as design, computer science and statistics.In other words data journalism is gathering, cleaning, organizing, analyzing, visualizing, and publishing data to support the creation of acts of journalism. So it simply uses data as a source in addition to humans. So today news are flowing from many sources and what has happened is filtered through network of social connections, commented and more. This is why data journalism so important for gathering, filtering, visualizing is what is happening beyond what our eye can see has a growing value. Therefore in today's practices to make sense of the data deluge, journalists need to be more numerate, technically literate and logical while producing news. Because of using data in journalism allow us to create deeper insight into what happening around us. Data analysis can reveal “a story’s shape” (Sarah Cohen), or provides us with a “new camera” (David McCandless). So ssing data the job of journalists shifts its main focus from being the first ones to report to being the ones telling us what a certain development might actually mean. The range of topics can be far and wide. The next financial crisis that is in the making. The economics behind the products we use. The misuse of funds or political blunders, presented in a compelling data visualization that leaves little room to argue with it. This is why journalists should see data as an opportunity. For example, reveal how some abstract threat such as unemployment affects people based on their age, gender, education and region. Using data transforms something abstract into something everyone can understand and relate to. Additionally, getting into data journalism offers a future perspective. Today, when newsrooms cut down, most journalists hope to switch to public relations. Data journalists or data scientists though are already a sought-after group of employees, not only in the media. There is a promise in data and this is what excites newsrooms, making them look for a new type of reporter. Processes that facilitate data journalism
Process of data journalism The process to transform raw data into stories is akin to a refinement and transformation. The main goal is to extract information recipients can act upon. The task of a data journalist is to extract what is hidden. This approach can be applied to almost any context, such as finances, health, environment or other areas of public interest. Inverted pyramid of data journalism
In 2011, Paul Bradshaw introduced a model, he called "The Inverted Pyramid of Data Journalism".
Steps of the process In order to achieve this, the process should be split up into several steps. While the steps leading to results can differ, a basic distinction can be made by looking at six phases:
