Our projects bring together artificial intelligence, environmental data, citizen science and digital infrastructure to support research, monitoring and decision-making.
Across our work, we design tools and methods that connect environmental observations, public participation and actionable knowledge. This includes citizen observatories, environmental monitoring systems, data and metadata standards, digital platforms, impact assessment methods and AI-supported analysis.
We work with research institutions, public bodies, environmental organisations and citizen-science communities to develop practical solutions that improve how environmental information is collected, shared, interpreted and used.
Featured projects
Citclops / EyeOnWater
Citclops / EyeOnWater was a European citizen-observatory project for coast and ocean monitoring (FP7, 2012–2015), to whose scientific coordination 1000001 Labs contributed. It helped pioneer participatory approaches to marine and coastal observation by combining citizen contributions, environmental sensing and data analysis.
The project explored how citizens could contribute meaningful observations on water conditions and environmental change, while also supporting broader work on coastal awareness, interoperability and digital environmental monitoring.
Citclops FAQs
Citclops FAQs is a maintained resource that supports continued use and understanding of Citclops data and tools. It helps students, researchers and practitioners interpret project variables, datasets and monitoring concepts linked to the Citclops / EyeOnWater initiative.
This resource reflects 1000001 Labs’ ongoing commitment to continuity, accessibility and long-term value in citizen-science infrastructures.
FreshWater Watch
FreshWater Watch is Earthwatch’s global citizen-science initiative for water-quality monitoring. It enables groups around the world to monitor and help protect the health of rivers, lakes, streams, ponds, wetlands and reservoirs.
The project demonstrates how public participation can generate useful environmental evidence at scale while also strengthening local awareness, stewardship and engagement around water systems.
GLOBE programme
The Global Learning and Observations to Benefit the Environment (GLOBE) programme is an international science and education initiative that gives students and the public the opportunity to participate in data collection and contribute to understanding the Earth system and the global environment.
Through work connected to GLOBE, citizen science becomes both a research practice and a way to build environmental literacy, linking observation, education and international collaboration.
Scaling up citizen-science air-quality monitoring
This initiative supports the expansion of citizen science for major global challenges, with a focus on less developed and less well-resourced regions. In air-quality monitoring, the aim is to connect existing projects and practitioners, share resources and strengthen communities of practice.
The project reflects a collaborative approach to environmental sensing in which capacity-building, shared methods and practical cooperation are as important as the technologies themselves.
Hydroino
Hydroino is a low-cost, do-it-yourself sensor buoy system developed to support environmental monitoring by students and citizen scientists. It emerged from work linking marine monitoring, maker technologies, participatory sensing and low-cost instrumentation.
The project illustrates an important strand of our work: enabling wider participation in environmental observation by combining accessible hardware, digital tools and practical monitoring needs.
Citizen Science Data Standards (PPSR Core)
1000001 Labs contributes to citizen-science data standards and interoperability through collaboration around PPSR Core, the Public Participation in Scientific Research Core. PPSR Core is a global, transdisciplinary framework of data and metadata standards designed to help citizen-science information be structured, shared and reused consistently across projects, platforms and scientific communities.
The framework includes four main elements: a Common model that connects the standard as a whole, a Project model describing the purpose and coordination of a project, a Data Set model describing how observations are collected and used, and an Observation model describing individual records such as locations, dates and attributes.
This collaboration reflects our broader commitment to interoperability: helping environmental monitoring systems, citizen-science platforms and research infrastructures work together through shared standards, clearer metadata and better conditions for long-term data use.
How we contribute
Across these projects, we contribute research coordination, digital platform development, interoperability design, environmental-data analysis, citizen-science methods and applied AI. Our work focuses not only on collecting and organising information, but also on turning it into tools, evidence and insights that support communities, researchers and decision-makers.
We are especially interested in projects that connect environmental monitoring with participation, open standards, decision support and long-term public value. By combining technical development with collaborative research, we aim to strengthen the quality, usefulness and impact of environmental data.