Core contributor to both BD4NRG (edge-based big data analytics for next-gen energy) and EDI (European Data Incubator for big data SMEs).
UBIMET GMBH
Austrian weather data SME applying big data analytics and AI to energy grid optimization and renewable energy forecasting.
Their core work
UBIMET is an Austrian weather intelligence and meteorological data company that provides high-precision weather forecasts and environmental data services. In the H2020 context, they contribute weather and environmental data analytics to energy and smart grid projects, enabling better forecasting for renewable energy generation and grid management. Their work sits at the intersection of big data analytics, energy systems, and environmental monitoring — turning weather data into actionable intelligence for energy operators and infrastructure managers.
What they specialise in
As a meteorological data company, weather intelligence underpins their contributions across all three projects including SHAR-Q's energy ecosystem optimization.
SHAR-Q focused on storage capacity sharing in energy neighbourhoods; BD4NRG addressed optimized grid asset management and improved grid reliability.
BD4NRG involved hybrid scalable blockchain, off-chain decentralized data governance, and privacy-preserving federated learning.
How they've shifted over time
UBIMET's H2020 trajectory shows a clear shift from energy infrastructure participation toward data-intensive, digitally sophisticated energy applications. Their early involvement in SHAR-Q (2016) focused on energy storage and neighbourhood-level energy sharing — a hardware-adjacent topic. By 2018-2021, their projects (EDI, BD4NRG) moved firmly into big data analytics, blockchain-based data governance, and federated learning applied to energy grids. The trend reveals a company that started contributing domain data to energy projects and evolved into a data analytics and AI player in the energy sector.
UBIMET is moving toward AI-driven energy grid intelligence, combining their weather data expertise with advanced analytics techniques like federated learning and blockchain governance.
How they like to work
UBIMET operates exclusively as a participant — they have never coordinated an H2020 project, which is typical for a specialized SME that contributes domain expertise rather than managing large consortia. With 63 unique partners across 18 countries from just 3 projects, they work in large, diverse consortia where they fill a specific data-provider niche. This makes them a reliable, low-overhead partner: they bring their weather/data capabilities to the table without demanding project leadership.
Despite only 3 projects, UBIMET has built a wide network of 63 partners across 18 countries — a testament to the large consortia they join. Their network spans broadly across Europe with no single geographic concentration beyond their Austrian home base.
What sets them apart
UBIMET occupies a rare niche as a weather data SME that can plug directly into energy and smart grid projects. While many data companies offer generic analytics, UBIMET brings domain-specific meteorological intelligence that is critical for renewable energy forecasting and grid balancing. For consortium builders, they are the kind of specialized data partner that reviewers like to see — a commercial SME with real products contributing to research innovation.
Highlights from their portfolio
- SHAR-QLargest single EC contribution (EUR 260,500), focused on a practical energy storage sharing concept across virtual neighbourhoods.
- BD4NRGMost technically ambitious project combining blockchain, federated learning, and edge analytics for next-generation energy grids.
- EDIParticipation in the European Data Incubator signals UBIMET's positioning as a data-driven SME within the EU big data ecosystem.