ENGAGING WITH CITIZEN SCIENTISTS: INTEGRATING ENVIRONMENTAL AND CLIMATE CONSIDERATIONS INTO RESEARCH PRACTICE
ModulesENGAGING WITH CITIZEN SCIENTISTS: INTEGRATING ENVIRONMENTAL AND CLIMATE CONSIDERATIONS INTO RESEARCH PRACTICE
To enable learners to identify and address environmental and climate considerations in citizen science throughout the research lifecycle, while ensuring fairness, sustainability, inclusion, and responsible engagement with citizen scientists.
At the end of the module, learners will be able to:
- Identify environmental and climate considerations relevant to citizen science activities.
- Apply environmental and climate ethics, including fairness, sustainability, and the Do No Significant Harm (DNSH) principle, throughout the research lifecycle.
- Recognise and address issues related to consent, data protection, power imbalances, and the roles and recognition of citizen scientists.
- Integrate environmental and climate considerations into the design, governance, implementation, evaluation, and long-term stewardship of citizen science projects.
What is this about?
Guidelines
Design and planning This subsection outlines key environmental and climate considerations that should be taken into account when designing and planning citizen science activities.
1. Clarify purpose, roles and expectations
Define your project’s scientific and societal objectives, including any environmental or climate implications and explain why citizen science is appropriate (for example extended spatial or temporal coverage, access to local knowledge, or empowerment of affected communities). Clearly specify the roles and status of citizen scientists, including whether they act primarily as data contributors, co-researchers, co authors, or participants in decision-making or governance processes. Describe what citizen scientists will do in practice, what skills or training are required, and what level of effort and responsibility is expected. Prepare clear, non-technical descriptions of roles, rights, and responsibilities that can be reused in information sheets, consent materials, and terms and conditions.
2. Embed DNSH and environmental ethics from the outset
Conduct a DNSH-oriented scoping of risks, including possible ecological disturbance, social and distributive impacts (who benefits, who may be harmed), and risks associated with the collection and use of data. 1The DNSH principle originates from EU sustainability policy and is used here as a high-level ethical lens to help researchers reflect on whether research activities could cause significant environmental or social harm. This guide does not provide legal guidance on DNSH compliance under the EU Taxonomy or related instruments, nor does it place such responsibilities on citizen scientists. Researchers remain responsible for addressing any formal DNSH or regulatory requirements applicable to their projects
These may include misuse or secondary use of data, for example where environmental or spatial data contribute to surveillance, inform investment or planning decisions that accelerate green gentrification, or enable exploitation of natural resources. Adjust protocols to minimise harm and document mitigation measures. For projects in health and life sciences or areas involving biosecurity, ensure that applicable regulatory requirements are met and approved by local biosecurity committees before involving citizen scientists, and make clear which activities must be carried out or supervised by qualified professionals.
3. Plan for inclusion and fairness
Identify groups most affected by environmental or climate implications that may arise through project activities and plan for their proactive inclusion, including vulnerable communities, youth, local experts and under-represented groups that are historically or structurally under-represented in research participation, knowledge production, or decision making processes relevant to the project domain. Offer diverse participation modes (digital and non digital, synchronous and asynchronous) and budget for accessibility needs such as language support, interpretation, childcare or travel. Aim to design participation protocols and digital tools (such as apps and platforms) in ways that are accessible, usable, and inclusive across different levels of digital literacy, abilities, and technological access. Anticipate power imbalances and consider structures, such as advisory boards or steering groups, in which citizen scientists participating in the research can influence design, governance, and communication.
4. Fieldwork in natural landscapes
For field-based projects in natural landscapes, conduct a basic ecological and health-and-safety risk assessment in collaboration with local communities, land managers or park authorities. Agree on a simple code of conduct for fieldwork and communicate it clearly to all citizen scientists and participants before activities begin.Ethics review, governance and data management
This subsection highlights environmental and climate considerations relevant to ethics review, research governance, and data management in citizen science activities
1. Ethics review
Where required by national legislation, institutional policy, or disciplinary standards, citizen science projects or project proposals should be submitted to appropriate ethics review or oversight bodies, particularly when personal data, images, sensitive geodata, or information about individuals or communities are collected, or when participants may also be research subjects (for example, in surveys or interviews). Project teams should clearly explain the roles of citizen scientists (e.g. co-researchers, contributors), consent and withdrawal mechanisms (including for long-term platforms), and how vulnerable or marginalised groups, especially those disproportionately affected by environmental or climate impacts, will be protected. In contexts where formal ethics committees do not routinely review citizen science or non-biomedical research, researchers should seek alternative forms of ethical oversight and guidance, such as consultation with institutional ethics officers, data protection officers (DPOs), or equivalent advisory bodies. Such oversight should consider not only data protection and privacy obligations, but also environmental and climate ethics implications, including risks associated with sensitive information, ecological data, geolocation or community-level environmental knowledge. Project teams should ensure that submissions are supported by a FAIR2-aligned Data Management Plan (DMP) that is supplemented by explicit measures to identify and mitigate ethical risks, including risks associated with personal, environmental, or geospatial data (such as privacy concerns, sensitive ecological information, or harmful secondary uses).
2. Data management, terms and conditions, and open science
Prepare a Data Management Plan (DMP) that covers data types, quality control, storage, access rights, retention periods, and conditions for open or controlled access. Where relevant, address environmental and climate implications of data use, such as risks linked to sensitive ecological data, locations of endangered species, or information that could unintentionally increase environmental pressures.
Apply privacy-by-design principles in apps and platforms by working with anonymous data whenever possible, and, where this is not feasible, with pseudonymised data. Limit the collection of personal data to what is strictly necessary, clarify permissions, and make privacy settings simple and accessible. Where pseudonymisation is used, keep re identification keys separate and securely managed. For sensitive environmental or social data (such as locations of endangered species or informal settlements), consider additional protective measures, including spatial generalisation, restricted-access repositories, or delayed public release, to prevent unintended environmental or social harm.
Ensure that consent, privacy controls and terms of use are visible and understandable, shared with participants before they contribute, and consistent with the DMP and ethics approvals. When designing or using digital tools and platforms (for example, apps, sensors, online portals, AI-supported analysis), allow participants to view their data, change privacy settings and request data deletion. Allow participants to also assess and flag accessibility, potential biases and risks of reinforcing digital divides, and offer alternatives or support where possible.
3. Data ownership, traditional knowledge and benefit-sharing
Before data collection, clarify who will be considered the owner or custodian of different types of data (individual observations, community-level data, aggregated datasets, models, code) and project outputs, and how this will be reflected in licences, access conditions and acknowledgements. When working with local, Indigenous or traditional knowledge, recognise that this may be held collectively and governed by community norms. Some knowledge should not be made openly available, especially if disclosure could lead to environmental harm, resource extraction, over-exploitation, biopiracy or cultural harm. Discuss and document benefit sharing arrangements with relevant communities and partners, such as access to data and tools, capacity building, co-authorship or co-branding, or (where appropriate) participation in financial benefits from commercial uses of results. Information sheets, consent materials and terms and conditions should explain what claims researchers, institutions and third parties may make over data and knowledge, what claims citizen scientists and communities may retain, and how disputes will be handled (especially when data relate to land, natural resources or environmental stewardship).Working with citizen scientists in practice
This subsection addresses environmental and climate considerations that may arise during the practical implementation of citizen science activities.
1. Informed consent and information
Provide layered information (a short overview plus a more detailed description) in plain language. Explain the project’s purpose, methods, environmental risks and benefits, and how data and metadata will flow and be shared (including open-science aspects and whether data relate to local ecosystems, climate vulnerabilities, or sensitive ecological locations). Where relevant, explicitly address the collection and use of visual data (such as photographs, videos, images, maps, or other visual records). Clarify how individual participants can withdraw and what happens to existing data, including whether data may be reused in future research, shared with third parties, or combined with other datasets, and under what conditions. Where research activities affect communities, territories, or shared environmental resources, consider whether additional forms of community-level information, consultation, or consent are appropriate. In some contexts, this may include engagement with community representatives, leaders, or governance bodies before individual participation begins, particularly where research relates to land, natural resources, environmental monitoring, or collective climate vulnerabilities.
2. Avoid undue inducement and ensure voluntary participation
Offer recognition and modest incentives where appropriate (such as reimbursement of expenses, certificates or training) but avoid financial or material benefits that may pressure individuals or communities to participate especially in contexts where environmental or climate vulnerabilities may heighten dependence on such incentives. Make it clear, in writing and verbally, that participation is voluntary and that declining or withdrawing will not affect access to services, support or future collaboration.
3. Training, support and safety3
Provide initial and, where needed, ongoing training for citizen scientists covering data collection protocols and quality standards, use of equipment and digital tools, and safety procedures and environmental rules (e.g. how to minimise ecological impact). Training should also address research integrity and ethics, including responsible conduct, respectful engagement with communities and environments, and personal data management where applicable. Establish clear channels for support and conduct a basic risk assessment for fieldwork that addresses health (including psychological support), safety (including using equipment) and potential environmental impacts for both researchers and citizen scientists.
4. Recognition, feedback and decision-making involvement
Develop a transparent recognition plan that includes acknowledgement of data contributions, appropriate attribution of individual or collective inputs, and clear criteria for co-authorship, where relevant. Recognition may take different forms depending on the level and nature of contribution (e.g. acknowledgements, contributor lists, dataset citations, co-authorship, or public recognition), and should be communicated clearly from the outset
Provide regular feedback through dashboards, maps, short This helps reduce power imbalances, strengthen trust, and avoid instrumentalising participants solely as data collectors.
Where suitable, involve citizen scientists in decisions about project design and priorities, data governance and access rules, and communication formats, especially when data relate to land, resources, environmental monitoring, or climate vulnerabilities.
This helps reduce power imbalances, strengthen trust, and avoid instrumentalising participants solely as data collectors
5. Conflicts of interest and transparency
Identify and manage conflicts of interest for both professional researchers and citizen scientists, including financial and non-financial interests. Ask team members and citizen scientists in governance or decision-making roles to disclose relevant interests at project start and when circumstances change.
Particular attention should be paid to non-financial conflicts of interest, which may be less visible but can significantly influence research processes and outcomes. These may include strong personal, political, community, advocacy, or professional commitments related to the research topic, local environmental disputes, land or resource use, or anticipated policy outcomes. Project teams should raise awareness of such conflicts, facilitate reflection among participants, and provide clear guidance and examples to help identify them.
Decide how to handle disclosed conflicts in a proportionate manner, for example, by documenting them transparently, using balanced or diverse panels, clarifying roles, or avoiding situations where individuals with strong stakes are solely responsible for critical measurements, interpretation, or communication.
Be transparent with participants and stakeholders about funding sources, institutional partnerships, and policy links, especially where these may raise questions about conflicts of interest, independence, advocacy, or industry influence. updates, or co-interpretation sessions, highlighting where environmental or climate-related findings may have implications for local communities or ecosystems.
Citizen science raises specific ethical responsibilities with regard to research quality. Researchers should not assume that citizen scientists have prior methodological expertise. Adequate training, clear protocols, and ongoing support are essential to ensure data quality while respecting participants as collaborators rather than shifting responsibility or blame for methodological shortcomings onto themEvaluation, learning and long-term stewardship
This subsection highlights environmental and climate considerations relevant to the evaluation of activities, learning processes, and the long-term responsibilities associated with citizen science research.
1. Evaluation
Plan evaluation that covers scientific quality, participant experience (e.g. motivation, perceived respect, learning), ethical performance, and the environmental and social impacts of project activities. Where appropriate, use measurable and transparent indicators to support evaluation, for example indicators related to data quality and reuse, inclusiveness and fairness of participation, handling of ethical incidents or DNSH concerns, and observed environmental or climate-related outcomes of the project.
2. Oversight and long-term stewardship
Document lessons learned and integrate them into institutional policies for citizen science, future project design, and training or micro-modules on research ethics and integrity. For citizen science projects with long-term monitoring objectives, identify appropriate oversight institutions (e.g., public agencies, trusted repositories, community organisations or RPOs) that can advocate for the interests of all stakeholders. Develop a realistic transition plan for long-term data and platform stewardship, including open data preservation where compatible with privacy and safety, governance arrangements for ongoing access and use, and responsibilities and resources after project funding ends.
