- Volunteer-powered science resides in a state of ambivalence.
- Standardizing citizen science data and metadata will enhance discoverability and legitimacy.
- Citizen scientists offer another safeguard when regulatory agencies fail.
We’ve been following the advent of citizen science for some time now at the Science Node. Citizen science has come a long way, and to improve its reach and efficiency, the US National Science Foundation (NSF) -supported Citizen Science Association (CSA) recently created a Data and Metadata Working Group (DMWG). If all goes as hoped, citizen science will come out of the shadows and continue to join the ranks of respectability enjoyed by traditional scientific research practices.
When most of us think of science in practice, we probably envision a white-coated, bespectacled senior scientist delegating field research to apprentice researchers (i.e. graduate students). These fledgling scientists port their observations and samples back to the lab, where fully credentialed researchers verify, clean, and analyze the data. Findings are eventually forwarded on to the public in the form of peer-reviewed publications.
The citizen science model rocks this boat. “Citizen science is challenging because on the one hand it asserts that normal people can do this,” observes NSF-funded researcher Anne Bowser, program associate with the Science and Technology Innovation Program (STIP), and Commons Lab co-director. “It asks a lot of questions about what peer review and publication mean, and it brings up debates about open access to data. People need to publish papers in order to advance their careers, so should data be proprietary?”
Despite these challenges posed to formal scientific structures, citizen science offers a tremendous increase in data available to inform public policy. What’s more, it presents a unique chance for citizens to participate in their democracies, notes Chris Higgins, project coordinator for the EU-funded Citizen Observatory Web (COBWEB).
“We ran an extensive co-design project throughout the 2015 field season, and we got a lot of feedback about how much people valued the thought that the data they collected was of value for policy formation and delivery,” he says.
To hasten the acceptance of citizen science data, the DMWG is spearheading an effort to increase interoperability — the ability of diverse citizen science projects to coordinate toward common ends.
“If you can describe citizen science projects in a way that resonates with formal scientific researchers, then that data can have a lot more reach.” ~Anne Bowser
Along with the European Citizen Science Association and the Australian Citizen Science Association, the DMWG shares the objective of identifying data and metadata standards. They laid out their plan to reach that end at a recent workshop hosted by European Commission’s Joint Research Centre. (Read the report from the meeting here.)
Among the checkpoints along the way to this destination will be the development of common terminology, the emergence of coordination among existing data repositories, and the creation of a citizen science observational data model.
A common vocabulary in the project metadata, for instance, would spell out various participation models and tasks, delimit metrics related to data attributes, and describe models of governance.
Standardization is expected to enable data discoverability and connection between the citizen scientists around the world. On the other hand, notes Higgins, there are already many standards in existence dealing with data discovery and access. Organizations like the Open Geospatial Consortium have worked hard over the last few decades to create open interoperability standards. “It’s important not to 'reinvent the wheel',” he cautions.
Higgins’ COBWEB is engaged in implementing those standards and is partnering with the DMWG to see if existing standards are fit for citizen science purposes. Whichever set of standards is ultimately adopted, “The starting point is the recognition that there is a huge variety of potential citizen science projects and that any generic solution has to be very flexible and interoperable,” Higgins insists.
Another hurdle on the route toward standardizing citizen science data and metadata is the need to respect the bottom-up, grass-roots nature of volunteer science. The very informality of citizen science is its strength due to its potential as a mechanism for influencing public policy. Citizen science has the ability to challenge and change existing regulations and laws, and in order for that function to operate, no one wants to hamper the creativity of these volunteer researchers.
For example, the formal science regulatory model has recently and very publically failed in Flint, Michigan when it declined to acknowledge serious water quality issues. It was only due to the persistent efforts of citizen scientists like Lee Ann Walters that we know about it at all.
The Flint example may be an extreme instance of the shortcomings of the formal model. However, through standardization, the DMWG could enable citizen scientists to identify different environmental quality metrics than those promoted by existing regulatory bodies.
“We are giving people a vocabulary through these standards for framing their activities in a way that we know regulators could perhaps more easily accept,” says Bowser. “In this way, we can prove citizen science data is as good as data a traditional scientist would go out and collect, and then you have all of these voices participating in something like regulation or collecting data to set conservation policy.”