How can we ensure uptake of CO-generated data?

Why is it relevant?

If you want to ensure uptake of CO-generated data, you need to demonstrate its quality, reliability, and relevance. By doing so, you help participants see the value of their contributions, give policymakers confidence to base decisions on the data, and enable researchers to incorporate it into scientific analysis. Showing both robustness and potential impact is key to building the trust needed for wider use.

How can it be done?

You can build or strengthen trust in CO-generated data by combining scientific rigour with practices that make the data socially meaningful. This means ensuring data quality, while also recognising citizen contributions, communicating uncertainties openly, and presenting results in accessible formats such as visualisations or dashboards. By doing so, you help stakeholders see the data as both credible and relevant, which increases its legitimacy and use in decision-making.

Existing (adapted) approaches	Featured tools
Building legitimacy and credibility in data through communication and recognition	i) Feedback and recognition mechanisms - Showcasing small wins / celebratory events, ii) Data storytelling and visualisation platforms to make results relatable using CSTIA, and iii) Boundary objects such as Dashboards that can be understood and used across stakeholder groups.

A. Building legitimacy and credibility in data through communication and recognition

Data uptake depends not only on technical quality but also on whether it is perceived as legitimate and aligned with the needs and values of stakeholders. Recognition of citizen contributions, transparent communication of uncertainties, and accessible presentation formats help to build trust in CO-generated data and strengthen its social legitimacy (Tsang et al., 2009). By valuing contributors and making data relatable, you encourage stakeholders to see your CO’s outputs as credible and worth integrating into decision processes.

One way is by ensuring that participants see their efforts acknowledged and celebrated, since recognition strengthens legitimacy and sustains engagement. This can be done by feedback and recognition mechanisms that go beyond technical validation and create moments of visibility and pride for participants. Showcasing small wins in newsletters or social media posts highlights how individual contributions add up to broader outcomes, reinforcing the sense of collective achievement. Organising celebratory events - such as community gatherings, award ceremonies, or exhibitions of citizen-collected data, provides opportunities for recognition in public settings and builds social capital among participants. Recognition can also be embedded into platforms themselves, for instance by naming contributors on dashboards or issuing certificates of participation. An example of this is in flood-risk observatories such as WeSenseIt, citizens were shown in real time how their rainfall observations updated official flood maps, and community events were used to celebrate their role in improving preparedness. Research on participatory governance underscores that such recognition is not merely symbolic: it enhances perceived fairness, strengthens trust, and signals that citizens’ efforts are valued and consequential (Fung, 2006). In this way, celebration becomes both a motivational tool and a means of consolidating the legitimacy of CO-generated data.

A second way is by making data accessible and relatable across audiences. This can be done by using data storytelling and visualisation platforms such as participatory GIS, story maps, and the Citizen Science Impact Story Telling Approach (CSISTA). CSISTA incorporates testimonials and provides a structured process for practitioners to generate and communicate impact stories of citizen science initiatives (Wehn et al., 2021). Using the CSISTA Impact Inquiry Instrument, leaders collect qualitative data on realised and potential policy and decision-making impacts, thereby gaining insight into the initiative’s influence. Practitioners then define their storytelling goals, select the appropriate storytelling instrument (Impact Brief or Impact Narrative), and craft concise or narrative stories that effectively convey policy impacts to broader audiences. In this way, CSISTA not only enhances accessibility but also explicitly links citizen-generated data to societal and governance outcomes. Storytelling and impact assessment tools have been shown to improve both understanding and uptake by bridging technical information with shared cultural meanings and decision-making needs.

Finally, uptake also relies on data being credible and usable across institutional and community boundaries. This can be done by creating boundary objects such as dashboards or joint monitoring reports, which translate complex, heterogeneous datasets into accessible and actionable formats. Dashboards function as shared ‘translation devices’ that allow different stakeholder groups to engage with the same information from their own perspectives. For policymakers, dashboards provide aggregated indicators and visual summaries that can be quickly integrated into decision processes (Kitchin, Lauriault,& McArdle; 2015); for community members, they offer transparent access to raw data, interactive maps, or time series that validate local experiences. When co-designed with users, dashboards serve not only as technical artefacts but also as platforms for negotiation, enabling iterative discussion around what data means and how it should be acted upon. In this way, they embody the credibility–legitimacy–salience framework, ensuring that data is scientifically robust, socially trusted, and directly relevant to governance.

A practical example comes from flood risk citizen observatories in Europe, where dashboards provided real-time rainfall and water-level data collected by citizens and sensors. Policymakers used aggregated flood-risk indicators for emergency planning, while residents accessed localised alerts and maps to take precautionary action. Similarly, in air-quality observatories such as Luftdaten (now Sensor.Community), dashboards displaying community-collected particulate matter (PM2.5 and PM10) have been used by both local governments and neighbourhood groups to press for clean-air interventions. These cases show how dashboards, when participatory in design, enable citizen-generated data to travel across boundaries, becoming trusted inputs in both community action and institutional decision-making.

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