The EU-funded COS4CLOUD project aims to facilitate open science and citizen science initiatives by designing and implementing services. The project will design and prototype these new services using deep machine learning, automatic video recognition, and other cutting-edge technologies. COS4CLOUD hopes to make it easier for citizen science platforms to share data using improved networks in a user-friendly way. The project will use the experiences of platforms like: Artportalen, Natusfera, iSpot, as well as other environmental quality monitoring platforms like FreshWater Watch, KdUINO, OdourCollect, iSpex and CanAir.io. The project will integrate citizen science in the European Open Science Cloud to service the scientific community and society at large.
The following scores were calculated using a statistically-driven machine-learning approach, a type of AI that learns to perform a task by analysing patterns in data. This is an experimental approach to citizen-science impact assessment, and the exact reasoning behind the scores is not explainable. The scores represent a best guess of the impact the project is having in each domain. Scores are recalculated and updated when “View impact report” is clicked.
Proportion of questions answered in each domain.