|The slide rule and iPhone exemplify the strides we've made in handheld computation. Perhaps ironically, there is a Slide Rule App for the iPhone—I guess for those who are nostalgic. (Photos: Wikipedia; Apple)|
Despite all this additional computing power, there is no shortage of reports out there suggesting that humans are now lazier than we've ever been. So what's all this computing power going toward? Although I suspect the vast majority of smartphone users awaken their machines for a session of Angry Birds or something similar, there is a growing community of citizen scientists who are developing and distributing apps that are designed to capture unique data that will ultimately contribute to a larger investigation. Makes sense, right? While it used to require one person or a few people with expertise to collect all of the data, why not have everyone collect the data using their smartphones?
Currently, a quick search tells me that there are citizen science apps out there for recording bat calls, monitoring birds, temperatures, roadkill, and identifying trees, among others. But when I go to find an app to download in which I can do something fish-related, my search is empty.
A few years ago Scott Baker of North Carolina Sea Grant published a study in which he examined text message reporting of recreational catch data. The results were generally promising, and recreational catch reporting is consistently one of the hardest sectors in fisheries from which to collect data. The project used RECTEX, whereby anglers texted their catch information into a database.
|Example of codes used in RECTEXT to both reduce the volume of characters and standardize reporting. (Source: Rectext.com)|
The field of fisheries is known for its large public stakeholder group, so fisheries science could be in good shape to implement wider public-driven data collection projects. For example, most states operate creel surveys, in which different methods are used to collect fishing data from recreational anglers. Creel surveys have their pros and cons, but they certainly require agency resources to carry out. What if reliable data could be had for free, simply through being uploaded by anglers who had an incentive to report their catch?
One simple and aquatic-related citizen science app I did come across is put out by Creek Watch. Knowing that not all streams and rivers can be observed or sampled with high frequency, this app allows users to 1) take a photo of any stream, and 2) answer three simple questions about the condition of the stream. Both of these pieces of information are then uploaded to a database. Of course, the data aren't high-resolution (there is subjectivity to some of the answers), but the researchers are getting at least some level of data and could even improve on the responses when comparing them to the photo. Given the simplicity of this app, why not one for fish? Snap a photo, and add the length, date, and location?
|Creekwatch App data upload screen.|
Of course, there are pitfalls leaving the collection of your data in the hands of the public. Without confirmation of a species or an easy interface, it's likely your data won't be perfect. However, part of the challenge of these apps is creating something that makes your science a tangible project that excites the public. The upside to this is that data over larger scales of space and time allow us to address more questions, possibly questions we couldn't deal with if only one person is collecting data.
Finally, one interesting aspect of citizen science is the reliance upon cell phones in the third world. Often, people in developing countries don't have landline phones or computers, and thus their reliance upon cell phones can be greater than in places like the U.S. Assuming that future research needs will take place in developing countries, citizen science could be a major form of data collection and management in the near future.
|The future of data collection? (Source: http://www.rnw.nl)|