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Short Abstract

This paper shows challenges and opportunities for Marine Citizen Science (MCS) to overcome current contributory models, and it draws actionable strategies to advance CS data quality together with more meaningful blue participation entailing co-design, co-production, and co-ownership.

Abstract

Marine Citizen Science (MCS) operates within a persistent tension between democratic-participatory ideals and prevailing practices. While CS traditionally emphasizes broad public engagement, MCS increasingly prioritizes digital data collection through platforms, apps, and social media or the use of data collection tools like remote sensors, autonomous vehicles, and eDNA etc. requiring minimal involvement from volunteer citizens.

This shift raises critical questions about the role of citizen scientists and how their contributions are validated as scientific knowledge. The paper draws on expert consultation workshops conducted in the EU-funded OBAMA Next project (Fall 2024), which explored challenges and opportunities for MCS in the digital era.

Key findings reveal that MCS is shaped by a narrow vision that values inexpensive data production over meaningful blue participation. Although advanced technologies expand the spatial-temporal scope of research, they constrain interactions between volunteers and researchers, limiting the understanding of each other’s motivations. Furthermore, the pursuit of large, standardized datasets integrating CS data can overlook peripheral or local ecological concerns while reducing volunteers’ emotional engagement. Finally, volunteer participants’ contributions are frequently anonymous and under-recognized, with limited feedback beyond initial phases.

Similar practices risk undermining long-term engagement, which is essential for sustained CS data production and the devising of wide-ranging MCS models.

To address these challenges, this paper advocates for genuinely participatory rather than contributory science approaches that emphasize co-design, co-production, and co-ownership. Such models can foster deeper collaboration, enhance data quality, and ensure that MCS become a truly democratic and empowering tool for blue governance research (and beyond).