In the summer of 2013, cicadas in the billions emerged from the ground after 17 years of slumber. The natural cycles that begot the teeming hordes of loud, clumsy insects are as predictable as the moon and the tides, as were many of the stories written by mainstream news outlets covering it.
But in a field that included puff pieces like recipes for cicada tacos, one project stood out from the crowd — the Cicada Tracker from WNYC.
The brainchild of WNYC’s four-person data news team, the project called on the station’s listenership to become amateur scientists. Using either store-bought or homemade sensors, citizens were called on to go out into their back yards, check the soil temperature, and enter their results on the station’s website. The goal was to use the data to predict the emergence of Brood X.
John Keefe, the editor of the data news team, says the idea was born of a brainstorming session on how to cover such a predictable event.
“We were trying to figure out what we could do for the cicadas,” Keefe says. “We found out that you can actually predict, pretty much to do the day, when cicadas have actually emerged if you know the ground temperature just eight inches underground.”
Keefe says he knew it was possible to build a temperature sensor that would do the job, but wasn’t familiar with the specifics. At a hackathon just a week later, he pitched the idea to a couple of programmers, and they jumped on the idea.
They devised a cheap detector that readers could construct for themselves in about two hours from parts readily available at the local Radio Shack. From there, it was a simple matter of building a MapBox map to display the data, put out a call to the station listenership, and the Cicada Tracker was born.
From the start, it’s clear that Cicada Tracker doesn’t tell as interesting and harrowing a tale as the New York Times’ Snowfall (though they did inspire some on-air stories on entomology by the Radiolab team), nor is its public impact likely to garner many awards.
The one thing the project has that so many others are deficient in is reader engagement. In total, more than 1,500 people offered up temperature data on the emergence of the cicadas, along with 2,000 reports on sightings. Where many interactive projects measure their success in bounce rates or time on site, readers were so engaged in the Cicada Tracker that they bought or built temperature sensors, went outside, dug in the dirt, and filed their data.
It’s a remarkably clever way to harness the public’s’ latent interest in an insect swarm and turn that into a sense of ownership in a web project and the station brand. Keefe attributes the success in this respect to the unique nature of the public radio audience.
“We have a pretty engaged audience in public radio, and we have to be; we live off of that,” Keefe says. “If you’re not engaged enough to open your wallet a couple of times a year, then we don’t exist. So we really believe in a higher level of engagement.”
Of course, crowdsourcing has existed for some time, but when a project like this assumes the mantle of predictive accuracy for an almost universally interesting event and can be cited every time a cicada story makes it to air, it acquires a durability that justifies the effort that went into the project.
The next wave of data journalism?
But while the impact of the Cicada Tracker for readers is specific to that one story, journalists have taken heed because it signals that we may have entered a new era of data journalism informed by cheap, readily available sensors. Why rely on data from the government or interest groups when newsrooms can simply acquire their own?
The Cicada Tracker generated so much useful data that Keefe says the team actually reached out to the University of Connecticut Ecology & Evolutionary Biology department, who were trying to collect similar data on the emergence of Brood X. They were able to actually channel some of this cicada data into real scientific research.
Keefe says this kind of partnership is possible because of recent changes in the market for sensors.
“The price of the hardware has come down a lot, and the software is manageable for novices,” Keefe says. “And so then the question becomes: ‘What stories are going to emerge to be told?’”
The possibilities are endless, and of particular public interest, especially in areas of the world where there are gaping holes in government data or serious questions about its legitimacy. Keefe says he can foresee projects were newsrooms monitor pollution levels in local rivers or the location of radiation plumes near the Fukushima plant in Japan.
There are limitations as well, which Keefe acknowledges, particularly when the public is doing the data collection.
“There are common issues with sensor projects from data collection to data accuracy, to the accuracy of the devices,” Keefe says. “There’s a whole issue with even getting them out to people or having them make them themselves.”
Room for improvement
By all accounts the project was a success, but there are areas where the presentation could have been improved.
Integration with station coverage of the cicadas is incomplete, at best. For all the work that went into devising the sensors, creating the map and tracking the project, the most visibility it got was as a “recommended link” in a story. Why not an embed?
To add to that, the map itself is almost useless now that cicada season is in the past. Some way to display a time lapse of the cicada emergence would do a lot to improve the shelf life of the project, as well as lend motion to a page that is almost totally static.
A great emphasis on lowering the hardware barriers of entry for readers may have helped generate more responses as well. Many people don’t have $80 and two hours to build a complex detector, where they could have been pushing the far simpler $8 device.
In all, however, it’s hard to knock the Cicada Tracker. With a minimum of investment, WNYC harnessed the power of data to become the go-to location for information on an event of almost universal interest. They also set the stage for a new era in data journalism, supported by cheap, easily distributed sensors. That qualifies as a success by any measure.