COVER PHOTO: Image by Image by Albrecht Fietz from Pixabay
Imagine for a moment that you want to study the link between air quality and the properties of rainbows around the world. You decide you want to leverage the power of citizen science and crowdsourcing to ask people to take pictures of the rainbows they see and send you any photos of rainbows they have taken in the past. To study these patterns scientifically, you’d also like to encourage people to tell you the color patterns of the rainbows by annotating the colors in the images and measuring the color band widths.
All of this is doable with today’s technology. All you need to do is build a mobile app, website, and database that can handle large numbers of pictures and organize huge numbers of volunteers. It’ll likely cost you a pretty penny to build and maintain (put on your fundraising hat!), and more than a little people-power to manage and recruit all those volunteers – but it can be done.
Sounds a bit daunting though, doesn’t it? You’re not alone.
For over a decade, the Zooniverse has provided a place for researchers to bulk-upload huge sets of images and then work with volunteers to study, annotate, and analyze them at rates that would be impossible by researchers alone.
Meanwhile, CitSci has specialized in hosting citizen science and community science project data (including images), collected and shared by volunteers from around the world.
Both platforms have helped revolutionize opportunities for doing science. But there have been challenges too. The Zooniverse tools, as designed, do not allow an easy way for individual photos, contributed by volunteers or researchers, to be readily uploaded throughout the course of a project. The upload process can be cumbersome – it has to be done by a Zooniverse project collaborator, who acts as a clearing house for all of the photos shared with the project – a large undertaking. In CitSci, there hasn’t been a good way to analyze or classify image data within the platform. This often means that projects aren’t getting all the information they can from their images. Both problems present barriers to projects, especially those that are just starting out or are under-resourced.
Now, CitSci and the Zooniverse have combined forces through a new integration that is sure to change the way research is conducted once again and will make your research workflows a whole lot easier to implement.
While both platforms long recognized their own limitations, they needed an opportunity to address them. Then, in 2019 researchers from the Mountain Goat Molt Project came to CitSci with a research problem. They wanted to study patterns of goat coat molting across the Intermountain West. They decided to leverage the power of CitSci and iNaturalist to crowdsource the collection of images of goats across space and time. They wanted to use the Zooniverse platform for image analysis, but ran into a snag. There wasn’t an easy way to download the images from CitSci and upload them to the Zooniverse for subsequent annotation – especially since images were coming in a few at a time from many different people. It wasn’t long before the Zooniverse and CitSci teams started discussing an integration. An NSF proposal was written, submitted, funded, and a project was born.
Through that same proposal, the CitSci team began a valuable partnership with the Science Gateways Community Institute (SGCI), a National Science Foundation funded program that provides expertise to help science gateways (like CitSci) succeed. CitSci was offered an opportunity to work with a fantastic programmer, Mona Wong, from the San Diego Supercomputing Center. It wasn’t long before Mona joined the CitSci team and started talking with the Zooniverse about how to build the integration using their Panoptes API. She started writing code soon after for CitSci to enable projects to share pictures and has enjoyed working with the collaborative teams ever since.
The Solution: A CitSci-Zooniverse Integration
Through this new integration, projects can leverage the power of both platforms to collect volunteer contributed images through CitSci and upload them in near real-time to the Zooniverse for subsequent analysis.
And the best part is, you don’t need to be a programmer (or hire one) to do so!
All you need to do is create a project manager account on both the CitSci and Zooniverse platforms. Then, create a project on CitSci and select the integration toggle for the Zooniverse. Once enabled, you can create a parallel project on the Zooniverse by linking your user accounts and linking your project in both places. You’ll then create your datasheets on CitSci, recruit volunteers to enter their data (rainbow photos anyone?), and with a touch of a button, be able to send your photos from CitSci to the Zooniverse. Finally, you’ll configure your image classification or annotation tasks in the Zooniverse project builder and volunteers will be off and running.
And it gets even better!
Two Volunteer Communities are Better than One
As with many volunteer projects, some volunteers are going to be really interested in doing field work, but less interested in data analysis. And the reverse is also true. A great part of this new integration is that you have access to two volunteer communities automatically. First, there are the people you recruited via CitSci to collect and contribute images and other data to your project. The second is the community of volunteers from the Zooniverse that are ready and waiting to classify and annotate images from new projects like yours. It’s a great way to expand your audience from local to global.
A Third Volunteer Community is (Almost) a Click Away
CitSci is currently redesigning a prior integration with the popular citizen science community SciStarter which will soon allow you to automatically share your project information on SciStarter as well. With the SciStarter integration, you’ll be able to expand your volunteer recruitment efforts through the SciStarter Network, including Girl Scouts, libraries, universities, community groups, and more, with just the click of a button.
Could Your Project Benefit from the CitSci-Zooniverse Integration?
So what makes a project a good candidate for using the CitSci-Zooniverse Integration? Ask yourself these questions:
1) Does your project require people power for the collection of images?
If you have a huge set of images captured by camera traps, for example, you’re probably best to use the Zooniverse’s bulk upload tools. However if you want to capture an asynchronous, ad hoc, or other periodic event that would be difficult to capture without human intervention (rainbows or mountain goats, for example) then this integration is for you.
2) Would you benefit from additional annotation or classification from the Zooniverse crowd?
If you would like volunteers to upload photos of their field sites but don’t need to classify or annotate the photos, you probably don’t need the integration- you can just use CitSci. If, however, in the case of the mountain goat or rainbow photo examples, you want volunteers to classify, add to or pull additional data from the photos, this integration is a perfect fit.
3) Are the volunteers you’re recruiting willing to create accounts on CitSci?
Participants in your project will need to create accounts on CitSci to upload and share data. CitSci offers a variety of governance structures for data and volunteer privacy you can explore.
The CitSci-Zooniverse integration will save you time, energy, and money getting your project off the ground, allowing you to focus on your real goals – answering the science questions important to your citizen science, community science or crowdsourcing community.
Trainings, Tutorials, and more
Watch for a detailed tutorial for setting up a CitSci-Zooniverse integrated project in the next few weeks. In the meantime, you may find these resources helpful:
How to create an account in CitSci
To create an account on the Zooniverse, go to their home page and click on the Register button in the upper right corner. A registration screen will pop up for you to fill out.
How to Use Project Manager Tools in CitSci
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