By Welcome to our “Quick Guide” series, which should equip you with all the knowledge and tools that you need to start and manage a citizen science project!
Part one (this post) covers research questions and big picture planning.
Part two covers design, data collection, and volunteer management.
Part three covers results and follow-up.
Citizen science is a powerful field that empowers individuals of all backgrounds to contribute to meaningful scientific research, usually through the crowdsourced collection or analysis of data – information about the world. This data can be quantitative (numbers and measurements, like inches of rainfall) or qualitative (words and pictures, like images of nature snapped with your smartphone).
Looking to participate in a citizen science project? Visit CitSci.org and learn by doing (stuck on which one to pick? Leave No Trash and the Extremophile Campaign are both featured right now). We recommend the Foundations training from our friends at SciStarter for an overview of citizen science.
But do you have a research question about your community that no one else has asked? Well, then, it’s time to start your own project!
Whether you’re a full-time researcher, environmentalist, educator, or passionate community member, starting a citizen science project can foster collaboration, increase public engagement, and generate scientific results through the collection and analysis of data.
We created CitSci.org back in 2007 because we wanted to fill a gap and provide tools to jumpstart the entire research process, helping you build custom data sheets, manage your participants, share and analyze your data, and gather feedback. We’ve connected thousands of people to scientific discovery.
But where do you begin, if you want to start your own project? This guide outlines the key characteristics of a successful citizen science project and the steps to get started.
Research Questions
Every citizen science project needs to answer at least one compelling research question. Ask a research question that you can answer with the time, tools, and people you have, because your research question sets the stage for everything from data collection to how you share results. We have a longer blog post on the subject you can check out.
We recommend you spend a good bit of time understanding your topic, researching what others have said about it, and identifying gaps of knowledge you may be well-placed to fill. For the actual question itself, avoid “double-barreled” questions that ask two things at once. Instead, focus on a single, measurable idea.
For example, a double-barreled question might be: “How does urban development affect bird populations and public awareness of local species?” — which combines two separate lines of inquiry.
A better approach would be to split that into two distinct questions you could answer with different methods: one about bird population trends (where people count the birds they see), and another about community knowledge or engagement (where people could fill out a survey about their awareness of local species).
A clear, focused research question will help you design better datasheets, engage the right participants, and generate results you can actually use.
Your research question may or may not relate to a targeted and testable hypothesis, which is a proposed explanation about the relationship between phenomena. While many citizen science projects are built around a hypothesis, not all of them have to be.
Some of the most valuable projects aren’t trying to prove or disprove something; they’re about observation, monitoring, or documenting change over time. More about what a hypothesis is, later on in this series!
Different Types of Citizen Science Projects
Before you finalize your hypothesis, design your datasheet, and start collecting data, it helps to clarify what kind of project you’re building. We recommend thinking about this right after you’ve finalized your research questions.
Are you envisioning a large-scale effort with hundreds of participants submitting quick observations from their phones? Or are you coordinating a smaller, dedicated team of volunteers who will receive in-depth training and monitor the same site for months? Do you plan on focusing on monitoring conditions over time?
Also, think about the goal of your project. What do you hope the outcome of your project will be? Do you want people to learn something new (e.g. what species live in their area, and how to take care of them)? Do you want to influence policy (e.g. advocate for supporting pollinator-friendly plants, based on your research results)?
There’s no right or wrong approach: just what’s best for your goals, your topic, and your capacity.
Sauermann and Poetz (initially in an article with Franzoni, and then expanded on in their book) developed a helpful model showing how members of the public (including at scale through the lens of crowd science, or with smaller teams) can be involved at any stage of the research process, from identifying questions to analyzing data to sharing results. We wrote about it in another one of our recent blog posts!
But beyond when people participate, Sauermann and Poetz also introduced a framework for understanding how they contribute: the AKRD model. This model might be useful as you think through what type of project you’re creating.
AKRD stands for:
⬤ Activities – the actual tasks the crowd members/participants perform (like taking photos of wildlife or transcribing historical documents)
⬤ Knowledge – what people know and bring to the project (including lived experience, local expertise, or disciplinary training)
⬤ Resources – what people have access to (like smartphones, tools, transportation, or even funding)
⬤ Decisions – the ability to help shape the project, whether through setting priorities, refining methods, or choosing how results are used
Here are some things to consider as you define the type of project you’re creating:
⬤ Crowdsourcing vs. Small Group: Crowdsourcing works well when data collection tasks are simple and observations can be submitted from many locations. Think: snapping photos of tree buds to track spring bloom. Smaller teams are ideal for projects that require training, consistency, or long-term commitment, like water quality sampling or species tagging.
⬤ Clear Governance Structure: Who’s in charge of what? Whether your project is a class assignment, a nonprofit initiative, or a personal passion, defining roles early helps everything run more smoothly. We recommend reading our governance paper for help. In that paper, we emphasize that every project should be able to set its own governance structure — deciding who can join, how data is shared, and how privacy is protected — and that some projects may have special considerations, like protecting sensitive species data.
⬤ Clearly Defined Goals: Know what success looks like, for both science and your participants. Scientific goal: What question are you answering or what pattern are you documenting? Participant goal: What will people learn, experience, or contribute?
⬤ Know Your Audience: Are you engaging middle schoolers? Retirees? Local fishermen? Designing for the right audience improves participation and data quality. Tailor your training, materials, and outreach accordingly.
⬤ Match Tasks to the Question and the People: Make sure the activities your volunteers do actually help answer your research question and that they’re appropriate for the people doing them. Teachers might log observations with students during a field trip; a local land trust might want detailed monitoring protocols for adult volunteers.
⬤ Plan for Communication: Keep your participants in the loop! Plan how you’ll share updates, answer questions, and report back with findings. (Pro tip: having a communications plan boosts retention and makes your volunteers feel like collaborators, not just data collectors.)
⬤ Share the Results: Your participants deserve to see what their contributions led to. Whether you’re creating a public dashboard or sending an end-of-season report, build in time and tools to share findings back. (For help, read the rest of this series.)
⬤ Make it Meaningful: People participate because they care. They want to connect to nature, learn something new, or contribute to something bigger. Think about how your project can offer: a sense of impact? Learning opportunities? Community connection?
We hear from individuals and organizations every day that want to start a citizen science project. There are many reasons why they generally reach out to us:
⬤ They or their organization has recently discovered citizen science and believes it could be a useful tool for their organization (ex. This set of citizen science training videos was created with and for restoration ecologists in federal organizations)
⬤ They want to engage with their community and believe citizen science can help them make stronger connections (ex. Catch the Hatch with The Watershed Center)
⬤ They want to educate a community about a particular topic, place, or issue through citizen science (ex. #LeaveNoTrash University Challenge)
⬤ They need help answering a science question that would benefit from the power of the crowd (ex. Mountain Goat, Trout Lily)
⬤ They are concerned about a place/issue/topic and want to learn more about it (ex. Trout Unlimited)
All of this is to say, before you finalize your datasheets or set up your first monitoring site, take a step back and ask: Who is this project for? And why will they care?
In a longer blog post, Building Your Citizen Science Community, we explore how to design citizen science projects that are rooted in community needs and priorities. The best projects don’t start with a datasheet: they start with listening.
That’s why we recommend beginning with Customer Discovery and Stakeholder Assessments, tools adapted from business and community organizing. These approaches help you understand the goals, concerns, and motivations of the people you hope to engage. What do they want to learn or change? What questions do they already have? What would success look like from their perspective?
⬤ Customer discovery is the process of interviewing potential participants and partners to better understand their needs, experiences, and pain points, before you design your project. Harvard Business School has some great customer discovery resources.
⬤ Stakeholder Assessments involve mapping out everyone who has a stake in your project’s outcomes, from community members to policymakers, and identifying their priorities, concerns, and levels of influence. The Project Management Institute has some templates you can use.
When you build your project around the answers to those questions, you’re more likely to create something meaningful, something people want to be part of. That means better participation, stronger data, and greater long-term impact.
A Great Citizen Science Project is like a Great Movie
There’s a good storyline. Your project needs a great question or compelling topic that people are actually interested in — that’s your “plot.”
There are plot twists. Every good movie has surprises, and so will your project. Expect the unexpected, especially in your first season. You may find that your data collection method needs adjusting, or that volunteers are interpreting a question differently than you intended. One of our team members always tells students: “My datasheet at the end of my first season of data collection is rarely the same as it was at the beginning, because I always learn something along the way that makes it better.” So build in time to pilot your project and be ready to adapt.
There are great visuals. Just like special effects bring a movie to life, great data visuals bring your project to life. Maps, graphs, photos: they help you tell your story clearly and powerfully. That’s why we always say begin with the end in mind. Think now about how you want your data to look and what kinds of statistics you’ll need to back up your conclusions. Not sure where to start? Ask a local professor, agency partner, or even your friend’s cousin’s statistician sister!
Ready for your movie to begin? Read part two!
CitSci.org Blog 