Collaboration matters: capacity building, up-scaling, spreading, and sustainability in citizen-generated data projects

The paper situates the rapid rise of citizen-generated data (CGD) within broader trends in digital technologies (mobile phones, sensors, online platforms) enabling public participation in addressing societal issues such as air quality, noise, housing, traffic, and biodiversity. While CGD offers opportunities for public sector decision-making, it requires substantial effort and multi-actor collaboration to deliver useful outcomes. The authors note challenges similar to those in citizen science—sustained engagement, suitable technological infrastructure, clear goals and evaluation, and stable funding—and the difficulty of scaling initiatives from local to regional or international levels. In response, the paper examines two CGD projects—one bottom-up (Barcelona, Spain) and one top-down (pan-European)—to address two research questions: (1) How can local CGD projects be transformed into more widespread, sustainable initiatives? (2) How can CGD projects, which normally operate at a local scale, build capacity and reach a larger cross-section of citizens at broader geographical scales? The study contributes strategies and socio-technical means (infrastructuring, matters of concern, community engagement) through which capacity building, up-scaling, spreading, and sustainability can be achieved.

The paper clarifies CGD as data volunteered by people or their organisations to monitor, demand or drive change on issues affecting them, producing alternative datasets that complement official data and amplify citizen voice in democratic processes. CGD overlaps with community-based monitoring, citizen science, and citizen social science, emphasizing policy outcomes and local governance impacts. The literature highlights capacity building as essential, with a five-step process adapted from UNDP (identifying/engaging actors; assessing capacities/needs; formulating vision/mission/action plans; developing resources; implementing and evaluating programs). Shared challenges include funding, technology maintenance, participant recruitment, and infrastructure support. The authors review concepts of sustainability (comprehensive viability), spreading (replication at similar scales), and up-scaling (handling growth and aggregation), noting that data quantity needs depend on purpose and data production organization. A conceptual framework builds on infrastructuring (open, adaptable, long-term socio-technical development supporting community interests and the formation of publics), matters of concern (issue-centric gatherings that motivate participation), and community engagement (collaborative, inclusive approaches facilitating ownership, appropriation, social interaction, and media visibility). Prior work such as the Bristol Approach provides a six-phase participatory pathway (identification, framing, co-design, deployment/collection with data governance, orchestration, outcomes) for sustainable and scalable interventions.

The study employs two in-depth case studies informed by the authors’ direct, multi-year involvement. Case 1 (Making Sense—Barcelona) represents a bottom-up approach in which a local community co-defined matters of concern and co-designed a citizen sensing intervention. The project (2016–2017; H2020 ICT2015) deployed low-cost, open-source sensors (Smart Citizen Kit) and participatory analytics to produce actionable evidence about nighttime noise in Plaça del Sol. Methods included rapid ethnography (interviews with community groups, residents, civic centres), media and open data reviews, open workshops to identify matters of concern, co-design of sensing protocols (25 sensors; continuous 24h monitoring for 6 weeks; sensing diaries), calibration and quality assurance with experts, and collaborative analysis (workshops, meetups, triangulation with two official city sensors). Community engagement was orchestrated through fortnightly meetings, role mapping and task distribution, and trained community champions for technical onboarding and troubleshooting. Sustainability and spread were pursued via open-source tools, a Creative Commons toolkit, media outreach, and replication support. Case 2 (Invasive Alien Species—IAS in Europe) is a top-down, EU-initiated project to support the EU Regulation on IAS (No. 1143/2014) by extending the European Alien Species Information Network (EASIN) with citizen participation. The methodology included the design and deployment of a reusable, open architecture: backend data storage and API, a multilingual smartphone app for reporting/visualisation, and a validation interface. A waterfall engagement model proceeded from the European Commission and JRC to Member States, regions, municipalities, and local stakeholders, with surveys, workshops, and pilots (e.g., in the Danube Region) to capture country-specific needs, add species and languages, and align data flows. A stringent validation process enables integration of CGD into EASIN. Both cases were analysed through the lens of infrastructuring, matters of concern, and community engagement to assess capacity building, spreading, up/down-scaling, and sustainability.

• Making Sense (Barcelona):
  • Community and participation: 35–40 neighbourhood participants, 14 community champions, 5 facilitators, 2 scientists, 2 technicians; ~100 people in a public assembly.
  • Data collection: 25 Smart Citizen sensors; continuous 24h monitoring for 6 weeks; sensing diaries to contextualise readings; sensors calibrated at a public university; participant training and onboarding improvements.
  • Results: Average noise ~70 dB around midnight; peaks >80 dB between 2–5am (Thu–Sun). Triangulation with two official city sensors (dBA vs project’s dBC) confirmed WHO-exceeding levels; subsequent sensor versions measured dBA.
  • Actions and impact: City implemented co-created measures—benches/urban design changes, awareness campaign in multiple languages, earlier cleaning to disperse late-night gatherings, installation of a children’s playground.
  • Capacity and sustainability: Co-design, community champions, regular face-to-face meetings, skill mapping, and open resources (toolkit, documentary) built capacity and supported horizontal spread to other neighbourhoods; replication by at least two other communities.
  • Challenges: Divergent views on solutions (policing vs nudging); reconciling CGD with official measures (dBC vs dBA); privacy and data governance concerns leading to flexible continued data collection.
• IAS in Europe (pan-EU):
  • Technology and uptake: Smartphone app downloaded several thousand times; a few hundred active users; partners across multiple EU/associated countries; used in Joint Danube Survey, national reporting, and local BioBlitzes.
  • Data integration: Validated CGD integrated into EASIN; combined maps show CGD complements official data, with higher densities near urban areas; compliant with GDPR; translations into 11 languages; open-source components and open licensing.
  • Capacity and sustainability: Top-down coordination by EC/JRC with decentralised national/regional engagement; flexible architecture (species lists, languages, decoupled data management) enables country adaptations; sustainability through institutional embedding and community of practice.
  • Challenges: Limited uptake by external software developers; effort-intensive adaptation for other domains and country-specific rollouts; need for governance to pool technical expertise.
• Cross-case insights:
  • Matters of concern shape engagement and sustainability (local vs distributed regulatory drivers).
  • Infrastructuring and open, adaptable tools enable capacity building, spreading, and integration into official data flows.
  • Data ownership, privacy, licensing, and standards critically affect trust, reuse, and scaling.
  • Spatial-temporal variability of CGD and uneven coverage are persistent constraints when interpreting and scaling results.

The findings address the research questions by demonstrating that sustained community engagement around clearly articulated matters of concern, combined with deliberate infrastructuring and open, adaptable technologies, can transform local CGD projects into more sustainable and spreadable initiatives. In Barcelona, a bottom-up, co-designed process aligned tools, data practices, and social organisation to create credible evidence, mobilise publics, and achieve policy-responsive change. The success hinged on participatory framing, co-created protocols, data quality and triangulation, and visible pathways from data to action. For broader reach, open toolkits, media dissemination, and community orchestration supported horizontal spread. In the IAS case, a top-down, policy-anchored approach provided institutional scaffolding and technical infrastructure for distributed adoption. By engaging Member States and intermediaries, and by designing flexible, open components (languages, species, decoupled data management), the project enabled “down-scaling” to local contexts and integration of CGD into authoritative databases. Together, the cases show that the interplay of infrastructuring, matters of concern, and engagement determines capacity building, scaling strategies (horizontal vs vertical), and sustainability. Addressing data governance (ownership, privacy), licensing, and standards enhances trust, reuse, and policy impact, while recognising spatial-temporal variability and local priorities informs realistic expectations for scaling.

The paper contributes an empirically grounded account of how CGD projects can build capacity, spread, and sustain by aligning issue-driven participation with long-term infrastructuring and open, adaptable socio-technical systems. Bottom-up projects benefit from co-design, local facilitation, and open resources to enable replication, while top-down initiatives can embed CGD into institutional processes and data flows, offering reusable architectures that local actors can adapt. Across both, early and continuous engagement around matters of concern is essential to sustain participation and realise impact. Future research should examine the entanglement between CGD, apps and platforms, development environments, interface components, and data ecosystems, as well as governance models that pool technical expertise, standardise licensing and data management, and address spatial-temporal biases in CGD.

• Context dependence: Bottom-up impacts are highly local; sustainability may wane once the local issue is mitigated. Top-down rollouts require significant adaptation to country-specific contexts.
• Data variability and coverage: CGD exhibits spatial-temporal unevenness (e.g., clustering near urban/tourist areas), complicating interpretation and up-scaling.
• Data governance and privacy: Open sharing can reveal personal behaviours; protocols must adapt to evolving participant privacy perceptions and rights (e.g., GDPR compliance, flexible opt-in/opt-out).
• Technology adoption and maintenance: Open-source tools still require documentation, training, and resources; limited external developer uptake in IAS necessitated continued institutional support.
• Licensing and interoperability: Vague/absent licensing and heterogeneous tech stacks hinder data integration and reuse across apps/projects.
• Expectation management and funding: Participant expectations for policy response may not always be met; bottom-up projects are vulnerable to post-project resource gaps, whereas top-down projects rely on continued institutional prioritisation.