**This blog entry orginally appeared on the website oceanspaces.org.**/p>

Last week we kicked off the Coastal and Estuarine Research Federation with a workshop to wrap our minds around the ways citizen science can and does contribute to the science and management of our ocean and coastal resources. We had a great group of people with all kinds of citizen science experience to pull from to tackle the question of how do you make citizen science data useful? There were lots of relatively newly-formed groups collecting data on marine debris, photo by OST staff.

We started with one hypothetical example of a “pathway” from inception to data use: citizens collect data, the data is analyzed and forms the basis of a peer-reviewed scientific publication. That publication then joins the library of expert information on which to base management decisions. This example is far from the most effective if you want to reach managers using citizen science data, but served as good fodder for discussion. We came up with a spider web of other, perhaps more appropriate pathways connecting citizen science to application.

Smaller groups took their individual experiences to think about a wider map of possible avenues to connect citizen science to useful outcomes. Immediately the question arose of who do you start with – the citizen science mission or the data users? Turns out, what is usually depicted as a linear path needs to be more of a circle. This shouldn’t come as a surprise, as the structure fits with patterns of adaptive management approaches. Just think of how monitoring data of any form fits into management efforts, informing the next turn of the adaptive management cycle.

Example of adaptive management from Monitoring Enterprise’s plan for the North Central Coast.

Following the human tendency to classify things, one group quickly distinguished between two types of citizen science and how they engage with the broader public. The first engages as many people as possible for a simple activity, such as observing birds or taking pictures of wildlife in a local park. This type of data is great for monitoring efforts, tracking long-term trends and detecting changes. The second approach uses a small group of people working intensively on a more complicated task, which can approach mechanistic questions (ie. what causes the trend over time). Depending on which category a group falls into, they will fit into the bigger picture in a different way.

Pathway diagram from the group divided citizen science into categories.

Fundamentally, the different types of groups encompass different goals of citizen science outside of producing new scientific data (such as education), engender different concerns about data quality and use, and serve different roles in the broader scientific community.

Discussion of use types echoed around the room – citizen science can directly inform professional science (through both inspiring questions and providing data), monitoring efforts, management, and grassroots community efforts. Each of these ‘end points’ will vet the data differently depending on what kinds of things build credibility in their world, for example quality assurance protocols for scientific endpoints and local relevance to community groups.

Challenges to using citizen science data, according to one of the workshop’s breakout groups.

Relationships between the volunteers and data users are mediated by context and existing support systems. Ultimately, this is a relationship and therefore personal connections, conduct, and reputations all shape the credibility of the data and potential applications it may have. Solid, tailored communication strategies help support these relationships and build new ones. And of course, money to keep the program running, support communication plans, and facilitate application of the data is critical.

The short workshop embedded in a conference was just the starting point for such a discussion. The exercise of mapping program activities from motivating volunteers to manager and science needs is a helpful one for determining where there might be helpful alternatives to try. The steps in the process are mediated by external factors, from technological development to family connections, and these are important to consciously cultivate. Especially for programs hoping to grow, identifying steps in the process where a little help would facilitate the growth process can be a big asset in grant writing and otherwise articulating needs.

As usual, we were left with more questions than we started with, so I’ll leave them for people to continue either here in comments or to ponder moving forward:

  1. What types of questions is citizen science a good approach for?
  2. How do you package your data/results to best fit these pathways?
  3. What are the “frontiers” of citizen science?