Sensors: The next step in data-driven journalism?
Before last week, I really didn't know too much about the world of sensors and citizen sensing. I found that I was a little hesitant about sensor-fueled data collection at first -- not unlike drone surveillance, the idea of sensors becoming as ubiquitous cell phones made me think -- and wince -- about the possibility of our society driving full steam ahead into an irreversible, Orwellian, and voyeuristic future.
But after learning more about how sensors are being used -- especially within the context of citizen sensing -- I have really come around to the idea of using sensors in the journalism field. I think that some of the ideas that have been posted on the class blog so far -- reading sources' moods by sensing body heat or heart rate or determining energy output in athletes -- are really creative and productive uses for journalistic sensors.
For me, and perhaps this is because I am coming off the heels of a data visualization class, I have thinking more and more about how sensors could revolutionize data collection and visualization. Finding comprehensive, reliable, and unbiased data can be a real challenge. As if finding and sorting through pages and pages of spreadsheets weren't taxing enough, journalists also need to be constantly questioning where their data is coming from, whether it is objective and whether it supports a comprehensive story. However, when I think about how sensors -- such as the Air Quality Egg for example -- could change how journalists gain access to data and statistics, I am very optimistic about what lies ahead.
Of course, this is not to say that there wouldn't be privacy/consent issues or ethical considerations to be made when collecting certain kinds of data, but I am looking forward to watching how sensors and citizen sensing begins to unfold and transform data visualization in the journalism arena.
