Many of us have heard from an older generation just how hard it was to collect data. And forget about the analysis—I’ve been led to believe that entire reports and scientific papers have been written solely dependent upon the slide rule! But no matter what hyperbole one employes to describe what they once went through, it is absolutely true that we now carry around—and accidentally sit on—more computing power in our jeans pocket than was previously available to entire institutions.
|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)|
4 Comments Add yours
Great post Steve. I agree on most counts, especially regarding the developing world (SE Asia in my experience). However, it did bring to mind the recent article in NAJFM where most anglers in at least one area of the eastern US thought all sunfish were bluegill!
Great ideas here. For fishery resources, the process itself may be the endpoint; involvement=awareness. I'm sure a developer of such an app would also include a proper fish ID component.
Thanks, Dave. You are absolutely correct that there are (serious) limitations on permitting untrained individuals to collect data. So these approaches are clearly not for every project. But like anything, it's tradeoffs; the data might be free, but that might also mean that the researcher needs to put some serious thought into how the questions are asked/presented and what the expectations of data are.
Great article. I am currently working on a Vermont-specific citizen science fishing app for submitting catch results, which will be able to be viewed on the website. I should be launching it next spring.