✳️ Citizen science has become one of Europe’s most powerful tools for connecting research with society. From biodiversity monitoring to air quality and health data, citizens are contributing at an unprecedented scale. Yet behind this success lies a critical problem: the digital infrastructures supporting citizen science in Europe are deeply fragmented.

✳️ This insight sits at the heart of Deliverable 2.1 – Challenges Assessment, developed within the Horizon Europe – funded RIECS-Concept project. The deliverable offers ananalysis of the technical barriers that currently prevent the infrastructures supporting citizen science from reaching its full scientific, societal, and policy potential.

The Fragmentation Problem: One Challenge, Many Dimensions

✳️ The assessment identifies fragmentation as the meta-challenge shaping Europe’s citizen science landscape. This fragmentation manifests across five tightly connected dimensions:

📌  Technological fragmentation

Citizen science platforms are often developed in isolation, using incompatible software stacks, architectures, and programming languages. As technologies evolve, older systems become obsolete, resulting in duplicated effort and limited reuse of solutions.

📌 Data fragmentation

Citizen-generated data are stored in diverse formats, with inconsistent metadata and validation approaches. Even when projects collect similar observations—such as air quality or biodiversity records – the lack of shared standards prevents aggregation and cross-project reuse.

📌 Standards fragmentation

There is no common European approach to data quality, validation, or provenance in citizen science. Each project develops its own rules, weakening scientific credibility and limiting integration with institutional research infrastructures.

📌Resource fragmentation

Knowledge, tools, documentation, and lessons learned remain scattered across project websites, repositories, and reports. When projects end, valuable expertise is often lost.

📌 Community fragmentation

Citizen science is not only about data – it is about people. Fragmented technologies make it difficult for participants to move between projects, weakening long-term engagement, collaboration, and learning.

✨ Together, these forms of fragmentation reduce efficiency, limit scientific impact, and undermine the sustainability of citizen science initiatives across Europe.

Why Existing Platforms Are Struggling to Scale

✳️ The assessment shows that many citizen science platforms were created as time-limited project outputs, not long-term infrastructures. As a result:

⚫ Scalability is limited when participation or data volumes grow.

⚫ Maintenance and updates often stop once project funding ends.

⚫ Links break, services degrade, and platforms disappear – creating “digital dead ends” for both citizens and researchers.

✨ This project-based lifecycle is fundamentally misaligned with the long-term nature of research infrastructures.

New Technologies, New Risks

✳️ Emerging technologies such as artificial intelligence (AI) and large-scale data analytics offer exciting opportunities for citizen science – but also introduce new challenges.

📌 The assessment highlights gaps in:

⚫ Ethical and transparent AI use.

⚫ GDPR-compliant data governance.

⚫ Bias mitigation in algorithmic analysis.

⚫ Clear rules for accountability and explainability.

✨ At present, there are no widely adopted AI governance frameworks tailored specifically to citizen science, creating risks for trust, inclusivity, and responsible innovation.

What Can We Learn from Successful Domains?

✳️ To move beyond diagnosis, the deliverable examines successful infrastructures in three domains:

📌 Biodiversity and environment

Initiatives such as Cos4Bio and Cos4Env developed in the Cos4Cloud EU-funded project demonstrate that interoperability is achievable when shared standards (e.g., Darwin Core) and aggregators are used.

📌 Health

The DHIS2 platform illustrates how modular design, open APIs, and strong community governance can sustain a global infrastructure for decades.

📌 Climate

ICOS ERIC shows the value of early institutional commitment, federated models, and long-term governance for operational stability.

✨ Across these cases, common success factors emerge: standardisation, modularity, community engagement, and formal governance ✨

A Strategic Direction for RIECS-Concept

✳️ Rather than replacing existing platforms, the RIECS-Concept proposes a different vision: a federated, modular European Research Infrastructure for Citizen Science.

📌 Key elements include:

Interoperability through shared metadata schemas, open APIs, and FAIR-aligned data practices.

⚫ Ethical data governance

⚫ Open-source, reusable components that platforms can adopt incrementally.

⚫ Participatory co-design involving citizens, researchers, developers, and institutions.

⚫ Capacity building to support responsible use of AI and big data.

✨ In this model, RIECS-Concept acts as a network layer – connecting people, platforms, and data across domains and borders.

From Fragmentation to Federation

✳️ Deliverable 2.1 makes one message clear:
Europe does not lack citizen science innovation – it lacks coordination.

✳️ By addressing technical fragmentation and aligning infrastructures with open science principles, Europe has an opportunity to transform citizen science from a collection of projects into a durable, trusted, and impactful research infrastructure.

✨ RIECS-Concept is not just about better technology. It is about building a shared backbone that allows citizen science to thrive scientifically, socially, and ethically for the long term ✨

🔗More information can be found here: https://concept.riecs.eu/deliverables/

Published 2026-02-13