Public Lab Research note

Reflection on Sensor Journalism Module

by amarini | October 06, 2014 19:40 06 Oct 19:40 | #11245 | #11245

Sensor journalism is an exciting, but challenging new frontier in the journalism field. Data collection with sensors performed by journalists shows promise as a new way for them to tell stories, but certainly has potential pitfalls.

There seem to be many benefits of sensor journalism. For one, journalists can gather the data themselves which keeps them from waiting for someone else to do it. If they want data on a particularly subject and it’s attainable, they can go out and get it themselves. There is certainly a great desire for more data This will allow for journalists to be in control of the data they collect and where they collect it from which creates for more specific reporting. If journalists want to use sensors to collect data themselves, they’ll have to immerse themselves even further into the subject they’re interested in collecting data about. They need to know the subject backwards and forwards so they can fully understand what kind of data they’ll need to collect to make proper conclusions. This causes more engagement and familiarity with the subject the journalist is covering which will make them better able to explain the subject to their audience as well as ask better questions. The more familiar you are with a subject, the more capable you are of telling a better story. Sensor journalism also means studying up on technology. In the Tow/Knight Report “Sensors and Journalism” written by Fergus Pitt, he mentions some key themes that emerged during researching and writing sensor journalism case studies. “..the journalists in these case studies learned as they went. They found out about technology and researched its processes. Even the reporters who had formal training or long experience in their specialized beats had to study up to get the story right — and not just on the subject of their articles (which journalists almost always do) but on techniques and practices from professions outside their own” (47). It’s clear that a lot of studying and research is necessary to do this kind of journalism.

This leads to some of the challenges of sensor journalism. First, most journalists probably do not know how to create or use sensors properly by themselves. There is a lot of room for error if you’re not professionally trained in data collection. When we planned to conduct water conductivity data collection in our Data Visualization course, nearly all of us would not have been able to build the sensor we did without step-by-step help. Even with what I think was a very basic sensor, we ran into problems while building and utilizing it. Even then, the data we collected was not really enough to draw any conclusions or write a story about. If we wanted to write a story on the data we collected, we would’ve had to do a lot more research prior to collecting the water samples and create much more complicated sensors. In the case of our course, the purpose of collecting data and testing water samples around Boston for conductivity was just to get our feet wet in sensor journalism, not to write a story, though. As Lily Bui said in her presentation “Sensors, Uncensored”, sensors are becoming ubiquitous. The more people building sensors and making them easier to use, the easier data collection with sensors will be.

Of course, sensor journalism takes a great deal of time. Not only do you have study hard and even receive formal training in the techniques and practices of using sensor journalism, but you have to actually take the time to collect the data, analyze and interpret it, and then write a story or create a visualization about it. Collecting data is just one more thing to add to the list of tasks journalists already have to do. There’s preliminary research and interviews, reporting, fact checking, and editing. Things could easily fall through the cracks. It’s, of course, much easier to speak with professionals already in the data collection field, read their findings, and ask them questions.

Sensor journalism may take off especially in the environmental journalism field. One great example of this that shows how powerful this emerging field can be mentioned both by Bui and in our class is the sensor journalism done in Beijing to measure air quality levels. The government wasn’t giving them the data they wanted so they sought after it themselves and were able to make a change for the better. Part of our job as journalists is to be the watchdogs of society and this is an example of how sensor journalism can help us to do that. This shows one of the other key themes that emerged during researching and writing sensor journalism case studies in the Tow/Knight Report. “And lastly, but crucially, these journalists were not collecting their sensor data in isolation. Not only did they add context to the data, to make their audiences care, they rendered colorful pictures of the affected people.” (Pitt 47).

Sometimes data collection doesn’t make a difference, though, such as in the case of Street Bump, which Bui also mentioned. Street Bump is a mobile application that can downloaded onto a smartphone and will collect data using an accelerometer and GPS to track potholes in the city. People took the time to create the Street Bump software, collect the data, and input the information into data visualizations, however, it has made no difference. Despite the 37,016 bumps recorded, no potholes have been filled as a result, according to the application’s data. Perhaps, this is a fluke in the data collection, or, maybe, no action has really been taken despite the technology and data. While the data itself has not made any changes, perhaps if someone did a story outlining that no potholes have been filled, this sensor journalism could make a difference.

Another key theme in the sensor journalism case studies was community involvement. “Journalistic sensing is often intertwined with community. The physicality of sensing tends to mean that reporters have to work actually in their communities and must consider how their activity will interact with the people living where they are taking measurements,” (Pitt 47). This is beneficial because it gets journalists away from their computers focusing in on the numbers reported and actually interacting with a community and the people who live there. Journalists and scientist alike can learn a lot from data, but interacting with the community adds another level of understanding and may help them ask better questions.

Sensor journalism lends itself to citizen science. This causes people to interact with their communities or other communities they would never interact with otherwise just like in the case of professionally trained journalists. While this is a beneficial model, sometimes it just doesn’t work. One example is the personal air monitors used in Louisville by citizen scientists to check levels of certain regulated pollutants. According to an article published in the Courier Journal, the purpose of this citizen science initiative was to identify pollution hot spots and compare neighborhoods for particular pollutants. The monitors even had ozone capabilities to measure temperature and humidity. It turned out that the monitors were not calibrated for accurate comparisons so this data collection by citizen scientists proved to be ineffectual.

For sensor journalism to really work for telling well-reported, engaging stories, journalists need to fully understand their equipment and need working, calibrated devices. They also have to understand that it may not work and accept that. There may not be a story with every sensor journalism assignment, but it will always be good experience.


Login to comment.