Imagine a giant digital library that automatically sorts and identifies every plant and animal species across Europe. It uses AI to recognize species from data and organizes it like a 3D map so you can see how nature changes over time. It's like having a high-tech crystal ball to predict how climate change will shift where wildlife lives.
Natural resource managers and policy makers struggle to access and analyze fragmented biodiversity data. Manual species identification is slow, and legacy data is often trapped in non-standard formats, making it hard to comply with EU nature directives.
A Single Access Point featuring AI taxon identification, a web-GIS data viewer, and Virtual Research Environments (VREs) for data analysis across land and sea.
If you are an ecological impact assessment firm dealing with slow manual species identification — this project developed AI taxon identification services that speed up the processing of biodiversity data. This allows for faster reporting and more accurate site analysis for clients.
If you are a large-scale land management company dealing with unpredictable land cover changes — this project developed projections of land cover and climate change on species distribution. This helps in planning sustainable land use and protecting valuable natural assets.
If you are a municipal spatial planning department dealing with complex EU nature directive reporting — this project developed a web-GIS data viewer and data cubes. This ensures compliance with reporting obligations using up-to-date knowledge.
Based on available project data, no specific pricing or cost model for end-users is mentioned; the project is funded by an EU contribution of EUR 7,265,660.
The project is designed as a Single Access Point utilizing high-throughput monitoring tools and multi-dimensional data cubes, suggesting a high capacity for scaling across terrestrial, freshwater, and marine realms.
Based on available project data, specific licensing terms are not listed, but the project emphasizes FAIR data repositories and open access via a Single Access Point.
It integrates by mobilizing historical baseline and legacy data into FAIR repositories and harmonizing them across space, time, and taxonomy.
The project period runs from 2025-03-01 to 2029-02-28, indicating that full deployment of the VREs and tools will occur within this window.
The consortium is heavily weighted toward research and academic expertise, with 9 research organizations and 2 universities. There is a low industrial presence (1 industry partner, 1 SME), representing a 7% industry ratio. This suggests the project is primarily focused on technical development and data standardization rather than immediate commercial productization.
Contact Stichting Naturalis Biodiversity Center in the Netherlands
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