The Guardian’s data journalism is cool, but it takes three months to make

Gigaom

Once he finds a suitable topic, Feilding Cage, a New York-based developer and journalist for The Guardian, can easily spend three months generating the source information and designing a visualization for what’s become known as data journalism. The results bring understanding and reader engagement to topics that are otherwise discussed with a lot of words or static numbers. Readers can and do play around with the information, share it widely and discuss it for long periods after it appears online.

The Guardian’s interactive guide to gay rights in the United States

Cage is one of a handful of Guardian journalists who generate reports that say new things about topics that pop up in the news or are just plain old interesting. Cage and his boss, Simon Rogers, editor of The Guardian Datablog and Data Store, spoke about their work at the Strata conference at Santa Clara, Calif., on Tuesday.

Along with The Guardian, a few other news organizations have been putting an emphasis on data-driven reporting and visualizations, apps and even games in the past few years, such as the Chicago Tribune, the Los Angeles Times and ProPublica (Check out the Data Journalism Handbook for more information on this sort of work.)

Data journalism and visualization stand out for the verification and occasional gray-area explanations that journalists provide. Cage, for example, accompanied his interactive visualization of gay rights in the United States with a blog post explaining his methodology and disclosing his assumptions.

Screenshot from the Zoomdata’s big data analytics iPad app

It’s certainly one way to say something fresh with data, but it’s time-consuming when you consider big data analytics apps that provide users with real-time information users can compare against Hadoop-processed historical data, such as Zoomdata. (That company, which my colleague Derrick Harris covered last year, released the beta version of its iPad app on Tuesday.)

It would be neat to find a happy medium for enterprises that want original insights that every employee can see and use and act on but doesn’t take three months to generate. That’s especially true because the return on investment for work like Cage’s is hard to identify, although it’s possible the content could indirectly generate revenue by driving users to content they have to pay for.

Bridging the gap might be a matter of finding the perfect data scientist for the company. Or it might be a matter of time before the kind of work Cage does is automated. A computer already can write an earnings story, although it might be a few years before computers put wordsmiths out of business.

Maybe it just doesn’t make sense to cross data journalism visualizations with big data analytics apps. But I, for one, would like to play with such a tool.

Entrepreneurs from companies that work with and make visualizations from big data, such as Quid, will speak at the GigaOM Structure:Data conference on March 20-21 in New York.

Disclosure: The Guardian is an investor in Giga Omni Media, which publishes GigaOM.




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