Data journalism
Journalistic process / From Wikipedia, the free encyclopedia
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Data journalism or data-driven journalism (DDJ) is a journalistic process based on analyzing and filtering large data sets for the purpose of creating or elevating a news story.
Data journalism is a type of journalism 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. From the point of view of journalists, it represents "an overlapping set of competencies drawn from disparate fields".[1]
Data journalism has been widely used to unite several concepts and link them to journalism. Some see these as levels or stages leading from the simpler to the more complex uses of new technologies in the journalistic process.[2]
Many data-driven stories begin with newly available resources such as open source software, open access publishing and open data, while others are products of public records requests or leaked materials. This approach to journalism builds on older practices, most notably on computer-assisted reporting (CAR) a label used mainly in the US for decades. Other labels for partially similar approaches are "precision journalism", based on a book by Philipp Meyer,[3] published in 1972, where he advocated the use of techniques from social sciences in researching stories. Data-driven journalism has a wider approach. At the core the process builds on the growing availability of open data that is freely available online and analyzed with open source tools.[4] Data-driven journalism strives to reach new levels of service for the public, helping the general public or specific groups or individuals to understand patterns and make decisions based on the findings. As such, data driven journalism might help to put journalists into a role relevant for society in a new way.
Telling stories based on the data is the primary goal. The findings from data can be transformed into any form of journalistic writing. Visualizations can be used to create a clear understanding of a complex situation. Furthermore, elements of storytelling can be used to illustrate what the findings actually mean, from the perspective of someone who is affected by a development. This connection between data and story can be viewed as a "new arc" trying to span the gap between developments that are relevant, but poorly understood, to a story that is verifiable, trustworthy, relevant and easy to remember.