Citizen science
Al CREAF, la ciència ciutadana representa una línia fonamental de la nostra recerca. Mitjançant la implicació activa de la societat, transformem la manera en què abordem els reptes ambientals i millorem la nostra comprensió dels ecosistemes i els serveis ecosistèmics. La participació ciutadana ens permet recollir una gran quantitat de dades valuoses i diverses, promoure la conservació ambiental, i desenvolupar estratègies efectives per afrontar el canvi climàtic. La ciència ciutadana no només aporta coneixement científic, sinó que també fomenta una major consciència i implicació de la societat en la gestió i protecció del medi ambient.
Que es Citizen science?
What is citizen science?
Citizen science is a form of collaboration between scientists and citizens in the research process. Citizens can participate in different stages of the scientific process through various types of projects:
Contributory projects: Citizens help in the collection of data according to the instructions of the scientists.
Collaborative projects: Citizens actively participate in project design, data collection and analysis, using tools provided by researchers.
Co-creative projects: Citizens are involved in all stages of the scientific process, from design to the interpretation of the results.
These projects allow society to advance its understanding of the environment, improve public health and increase conservation awareness. In addition, they facilitate citizen participation in decision-making and the development of environmental policies.
How can citizen science be implemented in research?
The implementation of citizen science in research can be carried out through several strategies:
- Improve participation and involvement: Develop innovative methodologies and tools that encourage the active and sustained participation of citizens in scientific projects, maintaining long-term interest and involvement.
- Integrate diverse data sources: Create systems to collect and analyze diverse types of data, including sensor data, experiment results, and information from various scientific disciplines.
- Ensure data quality and interoperability: Implement systems based on artificial intelligence to ensure the quality of data collection and develop standards that allow seamless integration and sharing between different citizen science platforms.
- Build effective communication and governance models: Develop effective communication strategies and new governance models that incorporate citizen input, facilitating better decision-making and environmental management.
