Data journalism is the practice of using data to inform and enhance the process of journalism. It is a relatively new field, but one that has grown rapidly in recent years thanks to the explosion of digital data and the tools that have emerged to help journalists make sense of it all. In this essay, we will explore the history of data journalism, its current state, and where it might be headed in the future. This is a good field for an individual to venture into the world of data sets, analyze the data, and curate stories using statistics often termed storytelling from the data at hand.
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Last Updated: 2022-04-21
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History:
The origins of data journalism can be traced back to the early 20th century when journalists began using statistical data to inform their reporting. However, it wasn’t until the mid-20th century that data journalism really took off, with the advent of computer technology and the increasing availability of data in electronic form.
One of the pioneers of data journalism was Philip Meyer, a journalist and professor at the University of North Carolina at Chapel Hill. In the 1960s, Meyer began using statistical analysis to study the effectiveness of newspaper reporting, and in 1973 he published a book called “Precision Journalism,” which laid out a methodology for using data to improve the quality of reporting.
In the 1980s and 1990s, data journalism continued to evolve, with the development of computer-assisted reporting (CAR) techniques and the increasing availability of public data. CAR involves using computer programs to analyze large datasets, which can help journalists uncover patterns and trends that might otherwise be difficult to see.
Data Journalism in today’s world:
Today, data journalism is a thriving field, with many news organizations employing dedicated data journalists or teams of journalists who specialize in using data to inform their reporting. The proliferation of digital data, along with the development of tools such as data visualization software, has made it easier than ever for journalists to tell stories using data.
One of the most famous examples of data journalism in recent years is the work of The Guardian’s data team on the Edward Snowden leaks. The team used data visualization to help explain the complex workings of the NSA’s surveillance programs, and their reporting won numerous awards.
Another example of data journalism in action is ProPublica’s “Surgeon Scorecard,” which used data from Medicare to create a tool that allows patients to compare the performance of different surgeons. The tool has helped to uncover patterns of medical malpractice and has led to improvements in the quality of care provided by some surgeons.
Data Journalism in Future:
As technology continues to evolve, it is likely that data journalism will become an even more important part of the journalism landscape. Some experts predict that machine learning and artificial intelligence will play a greater role in data journalism, allowing journalists to analyze even larger datasets and uncover more complex patterns and trends.
However, there are also concerns about the future of data journalism. Some worry that the increasing use of algorithms to analyze data could lead to a “black box” problem, where it becomes difficult to understand how conclusions are reached. Others worry that the proliferation of fake news and disinformation could make it more difficult for journalists to use data effectively.
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