Cloud-based platform simplifies access to Earth observation data for everyone
The exponential growth of (Earth and) Environmental observation data demands innovative solutions to access and utilise it more effectively. Simply downloading and processing this vast volume on limited local resources is inefficient and conflicts with modern big data philosophies. Persistent challenges, such as identifying, accessing and making full use of these datasets, diminish their potential impact. The EU-funded FAIRiCUBE project addresses these issues by opening gridded data and algorithms to a broader audience, extending access beyond traditional Earth observation communities. Its mission is to facilitate the findable, accessible, interoperable, reusable (FAIR) and TRUSTable sharing of data. To this end, researchers are developing the FAIRiCUBE HUB – a crosscutting platform designed for data ingestion, provision, analysis, processing and dissemination. To showcase how the HUB helps to tackle these issues FAIRiCUBE crafted five use cases (some are urban adaptation to climate change and biodiversity and agriculture nexus), focusing on various dimensions of the European Green Deal (EGD) priority actions.
Breaking down data silos and enhancing decision-making
“Our core innovation, the FAIRiCUBE HUB, seamlessly brings together diverse Environmental Observation datasets and data science workflows, empowering you to effortlessly access, analyse, and visualise critical information,” notes Stefan Jetschny, project coordinator. Combining state-of-the-art data science tools and workflows, geospatial data cubes and machine learning applications, the Hub simplifies complex analyses and processing steps, cutting down the need for technical customisation. Shared workflows and scripts of the existing use cases document the potential and usability of the Hub for future users like researchers and data scientists. The cloud-based infrastructure enables scalable and manageable resources and decision-ready information, offering actionable insights tailored for decision-making. Customisable interactive dashboards and visualisation tools help users to effectively present findings, making the platform invaluable for policymakers, journalists, researchers and non-governmental organisation alike.
Overcoming obstacles to climate and environmental data management
“Datacubes, which organise large datasets across space and time, are vital for environmental science. However, their size, complexity, completeness and inconsistency often lead to challenges which restrict machine learning applications,” explains Kathi Schleidt, FAIRiCUBE technical coordinator. “FAIRiCUBE addresses these challenges by developing distributed machine learning techniques tailored to datacubes. These methods efficiently process complex datasets, reconstruct missing data through gap-filling and enhance downscaling precision.” Fragmented geospatial data catalogues add another layer of difficulty, complicating data discovery, access and use. FAIRiCUBE showcases with its own data catalogue how users can benefit from improved meta data description and thereby standardised and harmonised FAIR data. Finally, researchers from different fields and background contribute to the FAIRiCUBE knowledge base – a common library that describes how the FAIRiCUBE HUB solves complex research questions using state of the art data processing and machine learning algorithms to analyse complex datasets.
Innovative data tool users
FAIRiCUBE is working on business models to make available the FAIRiCUBE Hub to non-technical users and industry professionals in fields such as agriculture, biodiversity and urban infrastructure to access tailored Earth observation data solutions that optimise operational planning and decision-making. “Service providers could leverage its centralised datasets and pre-built analytical tools to enhance workflows and client delivery,” outlines Jetschny. “The Hub could also benefit eco bureaus in conducting environmental assessments, ensuring regulatory compliance and ecological monitoring, while policy analysts could leverage processed data for evidence-based recommendations.” For indirect users like urban planners and non-governmental organisations, the Hub can deliver decision-ready information. “City administrators and regional planners could gain geospatial insights to drive urban planning and sustainable development initiatives. For policymakers, the Hub delivers actionable data to shape climate risk strategies and environmental policies,” concludes Jetschny and Schleidt.
Keywords
FAIRiCUBE, Earth observation, platform, decision-making, machine learning, centralised repository
