Data journalism and information visualization is a burgeoning field. Every week, Between the Spreadsheets will analyze, interrogate, and explore emerging work in this area. Between the Spreadsheets is brought to you by CJR and Columbia’s Tow Center for Digital Journalism.

The Tow Center’s Post-Industrial Journalism report* is dense with observations and recommendations for journalists and newsrooms adapting to the “tectonic shifts” within the media. One of recurring themes discussed in the report, co-authored by Emily Bell, Clay Shirky, and CW Anderson, is data. How it’s changed and influenced journalism; how individual reporters should handle it; and what institutions—news organizations and journalism schools alike—should be doing with it. There are some crucial takeaways about data journalism highlighted in the report that call for further attention.

The first of the report’s three chapters—“Journalists”— talks about data most extensively, an indicator that data journalism is still very much reliant on the enterprise and enthusiasm of the individual journalist rather than a prescriptive, institutional-level concern. The chapter distinguishes between the elements of the journalistic process that are better carried out by machines and those that will continue to require the touch of the reporter’s hand.

Algorithmic journalism comes up straightaway in the report. In the section of the first chapter, titled “What machines do better,” the authors state the obvious:

One thing machines do better is create value from large amounts of data at high speed. Automation of process and content is the most under-explored territory for reducing costs of journalism and improving editorial output.

The authors used Narrative Science as an example of how data-driven narratives can be automated with computer technology. They point out that the technology that artificially creates stories shouldn’t be feared by reporters, but rather incorporated into their working process. Not having to report little league scores isn’t a threat to the sports reporter’s job; it’s an opportunity to use that time to write an in-depth piece about doping within high school football teams.

The report also says that reporters need at least a basic understanding of data and statistics. This point is worth emphasizing and really teasing out. A reporter doesn’t need an economics degree but should be able to look at spreadsheet without breaking out in hives. As the report says:

Journalists should be able to analyze the data and metrics that accompany their own work, have a familiarity with the idea that metrics represent human activity.

For the financial reporter, that means a certain specialist knowledge in the percentage change, the price elasticity of demand, and what have you. But the same principle is equally important to, let’s say, a music journalist. At the simplest level, he might work with data to analyze CD sales for a run-of-the-mill story about the music business. A foundational knowledge of statistics, however, can push that story a lot further—think a Freakanomics-type of analysis into why Tiesto topped Forbes’s list of the world’s highest-paid DJs.

The report says as the role of the journalist evolves, understanding how to work with data will become increasingly more pervasive:

The presence of metrics and data, relating to both the outside world and their own work, will become a daily reality.

The music journalist who knows diddly-squat about statistics should at the very least know when to call upon a statistician to help with analysis or an interactive editor to help him produce a map.

Another key recommendation is the need for more journalistic partnerships. The report talks about inter-institutional partnerships, citing WNYC and The New York Times’s SchoolBook project as an example of how the individual skills of both organizations have been used to produce efficient and in-depth coverage. Encouraging partnerships will also hopefully have the trickle down effect of encouraging more internal collaboration, such as between reporters and programmers in a given news organization.

The report gets to the heart of the issue of how the skill is taught both in journalism schools and in the newsroom. On j-school’s approach to teaching data journalism:

[T]here is a need for basic numeracy among journalists, something we’ve taken to calling the “Final Cut vs. Excel” problem, where journalism schools are more likely to teach tools related to basic video production than to basic data exploration.

Even j-schools that have data journalism classes often emphasize the tools used for presentation over those used for investigation. If there’s one thing journalists should take away from this report, it’s that taking a basic Excel course should be a necessity. Even simple spreadsheets can be a valuable reporting tool. Every journalist should be getting between them.


*Anna Codrea-Rado was, in a small part, involved in the production of the report.

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Anna Codrea-Rado is a digital media associate at the Tow Center for Digital Journalism at the Columbia University Graduate School of Journalism. Follow her on Twitter @annacod.