Journalists have a long tradition of using programming and data analysis to hunt down and tell stories.
Some of the earliest efforts stretch back to the 1950s and 1960s, when news organizations used computers to tally election results and analyze government data.
In 1969, Philip Meyer made the case in Precision Journalism for reporters to adopt social science research methods, including the use of computers and statistical analysis.
Thirty years later, in the fourth edition of his book, Meyer said that "a dedication to truth" and "some talent for writing" are no longer sufficient. The modern journalist must also be "a database manager, a data processor, and a data analyst."
By the time he wrote those words, "computer-assisted reporting" -- or CAR, as it came to be known -- was a well-established niche in the news industry. The increasing availability of personal computers and the rise of the Internet contributed to the number of journalists unearthing stories with the help of spreadsheets, databases, and mapping and statistical software.
Industry groups such as the National Institute for Computer-Assisted Reporting nurtured the trend, providing conferences and online forums for practitioners to share tools and knowledge.
Code and data suffuse the news industry today.
Newsrooms are scraping and analyzing data from government websites and social media, and building data-driven web applications and interactive graphics. They're using code to enlist the public in the news-gathering process and creating storybots to speed up the responsiveness of news.
Journalists are branching out into interactive games and AR/VR to provide new story experiences; tapping into satellite imagery and ocean tide sensors -- or even building their own sensors -- to uncover the news; and applying computational techniques to find hidden spy planes.
Programmer journalists are building tools and platforms to support the news gathering and publication process.
The news has even helped spawn technologies that have gained traction outside the industry.
These include the csvkit command-line tool for data wrangling and Django, a web framework for "perfectionists with deadlines".
Some fairly popular web technologies also grew up adjacent to the news. They include Backbone.js, CoffeeScript and Underscore.js -- the creations of Jeremy Ashkenas, a former member of The New York Times graphics desk and original developer of DocumentCloud.
Mike Bostock, a Stanford alumnus and former New York Times graphics developer, created D3.js, a tool used in newsrooms and beyond to create rich, interactive data visualizations on the web.
These days, computer-assisted reporters are more commonly known as "data journalists". Such reporters still specialize in obtaining, analyzing, and communicating the findings of data through stories. But we also have a growing number of generalists and specialists in a diverse range of skills such as computational techniques, sensors and satellites, web design and development.
The cross-pollination between journalism and the software and data science communities has expanded our ability to tell stories. Equally important, it's helped increase transparency in journalism. For years, investigative and CAR reporters have published detailed explanations alongside stories, describing the source materials and methodology that led to their findings.
These days, data journalists are building on this tradition by publishing the raw data and code used in analysis, tools and applications. Here are just a few noteworthy examples:
The combination of code, data and journalism positions us to tell engaging, creative stories. It arms us with the ability to search for patterns and outliers in an increasingly data-driven world. It allows us to increase trust in our practices by inviting the public into our process, and empowering others to build on our work.