The thematic focus of Ground Truth 2.0 was on flora and fauna, as well as water availability and water quality, for land and natural resources management. The project used mobile apps and social media analytics to collect explicitly and implicitly-sensed citizen data. As such, citizens were enabled to share data about the environment and to take on a new, crucial role in environmental monitoring, decision making, cooperative planning and environmental stewardship. Ground Truth 2.0 recognised the importance of real-life interaction between people and technology to set up a successful system. Its innovative approach combined the social dimensions of citizen observatories with enabling technologies, so that the implementation of the respective citizen observatories was tailored to their envisaged societal and economic impacts. Ground Truth 2.0 built on previous projects related to citizen observatories, earth observation and land-use modelling, undertaken with the participation of Ground Truth 2.0 consortium partners. The consortium partners presented a good mix of industry, SME, NGO, government, research and academia to ensure the worldwide commercialisation of the Ground Truth 2.0 concept.
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.