The Past, Present and Future of Sensor Journalism

This weekend I had the pleasure of being invited to the Tow Centre for Digital Journalism at the Columbia Journalism School for a workshop on sensor journalism.

The workshop (hashtag #towsenses) brought together a “community of journalists, hackers, makers, academics and researchers to explore the use of sensors in journalism; a crucial source of information for investigative and data journalists.” And, it was fascinating to talk about what role sensors – from the Air Quality Egg to aerial drones – should, could or might play in journalism. Even more fun with a room full of DIYers, academics and journalists with interesting titles such as “applications division manager” or “data journalist.” Most fascinating was a panel on the ethics of sensors in journalism of which I hope to write about another time.

There is, of course, a desire to treat sensors as something new in journalism. And for good reason. Much like I’m sure there were early adopters of camera’s in the newsroom, cameras probably didn’t radically change the newsroom until they were (relatively) cheap, portable and gave you something your audience wanted. Today we may be experiencing something similar with sensors. The costs of creating sophisticated sensors is falling and/or other objects, like our cell phones, can be repurposed to be sensors. The question is… like cameras’ how can the emergence of sensors help journalists? And how might they distract them?

My point is, well, they already do sensor journalism. Indeed, I’d argue that somewhere between 5-15% of many news broadcasts are consumed with sensor journalism. At the very minimum the weather report is a form of sensor journalism. The meteorological group is a part of the news media organization that is completely reliant on sensors to provide it with information which it must analyze and turn into relevant information for its audience. And it is a very specific piece of knowledge that matters to the audience. They are not asking for how the weather came about, but merely and accurate prediction of what the weather will be. For good or (as I feel) for ill, there is not a lot of discussions about climate change on the 6 o’clock news weather report. (As an aside Clay Johnson cleverly pointed out that weather data may also be the government’s oldest, most mature and economically impactful open data set).

Of course weather data is not the only form of sensor journalism going on on a daily basis. Traffic reports frequently rely on sensors, from traffic counting devices to permanently mounted visual sensors (cameras!) that allow one to count, measure, and even model and predict traffic. There may still be others.

So there are already some (small) parts of the journalism world that are dependent on sensors. Of course, some of you may not consider traffic reports and weather reports to be journalism since it is not, well, investigative journalism. But these services are important, have tended to be part of news gathering organizations and are in constant demand by consumers. And while demand may not always the most important metric, it is an indication that this matters to people. My broader point here is that, there is part of the media community that is used to dealing with a type of sensor journalism. Yes, it has low ethical risk (we aren’t pointing these sensors at humans really) but it does mean there are policies, processes, methodologies and practices for thinking about sensors that may exist in news organizations, if not in the newsroom.

It is also a window in the the types of stories that sensors have, at least in the past, been good at helping out with. Specifically there seem to be two criteria: things that both occur at, and that a large number of people want to know about at, a high frequency. Both weather and traffic fit the bill, lots of people want to know about them, often twice a day, if not more frequently. So it might be worth thinking about, what are the other types of issues or problems that interest journalist that do, or could conform, with that criteria? In addition, if we are able to lower the cost of gathering and analyzing the data, does it become feasible, or profitable to serve smaller, niche audiences?

None of this is to say that sensors can’t, won’t or shouldn’t be used to cover investigative journalism projects. The work Public Labs did in helping map the extent of the oil spill along the gulf coast is a fantastic example of where sensors may be critical in journalism (as well as advocacy and evidence building) as has been the example of groups like Safecast and others who monitored radioactivity levels in Japan after the  Fukushima disaster. Indeed I think the possibilities of sensors in investigative journalism are both intriguing, and potentially very, very bright. I just love for us to build off of work that is already being done – even if it is in the (journalistically) mundane space of traffic and weather rather than imagine we are beginning with an entirely blank slate.




4 thoughts on “The Past, Present and Future of Sensor Journalism

  1. Pingback: The Past, Present and Future of Sensor Journali...

  2. Rob Cottingham

    This is blurring the lines a little (ok, a lot), but a whole lot of business journalism is, if not sensor journalism, closely related: “the Dow was up 17 points in light trading, while the Shmerzak Composite Index fell by half a klummick.” And whatever context gets added to those numbers is often causation by correlation: “as traders digested the latest housing price report” or “with Jupiter in retrograde, analysts clearly think mineral exploration is a safe bet.”

  3. Pingback: Datenjournalismus im Mai 2013 | Datenjournalist

  4. Pingback: Land unter beim Onlinejournalismus – Verpasste Chancen beim Hochwasser | Datenjournalist

Leave a Reply

Fill in your details below or click an icon to log in: Logo

You are commenting using your account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s

This site uses Akismet to reduce spam. Learn how your comment data is processed.