EO4wildlife
EO4wildlife will bring together a large number of multidisciplinary scientists such as biologists, ecologists and ornithologists around the world to collaborate closely together while using the European Sentinel Copernicus Earth Observation more heavily and efficiently.
In order to reach such important objective, an open service platform and interoperable toolbox will be designed and developed. The platform will offer high level services that can be accessed by scientists to perform their respective research and big data analytics.
Big Data Decision SupportBig Data Research
EO4wildlife research specialises in the intelligent management of Big Data processing, advanced analytics and a Knowledge Base for wildlife migratory behaviour and trends forecast. The research will lead to the development of web-enabled open services using OGC standards for sensor observation and measurements and data processing of heterogeneous geospatial observation data and uncertainties.
The EO4wildlife platform will enable the integration of Sentinel data, ARGOS archive databases and real time thematic databank portals, including Wildlifetracking.org, Seabirdtracking.org, and other Earth Observation and MetOcean databases; locally or remotely, and simultaneously.
IT Innovation's Role
IT Innovation is responsible for the work on Big Data analytics and the Knowledge Base, leading the research work on advanced data mining, machine learning and high level data fusion, reasoning and uncertainty propagation.
We have received a best-paper award for our work in the project:
EO Big Data Connectors and Analytics for Understanding the Effects of Climate Change on Migratory Trends of Marine Wildlife Zoheir Sabeur, Gianluca Correndo, Galina Veres and Banafshe Arab-Zavar in collaboration with Atos Spain, Atos France and Collecte Localisation Satellite (CLS)
Project Fact Sheet
The EO4wildlife project is a 36 month project funded by the EC H2020 framework programme.
Coordinator: Atos Spain SA
Website: http://www.eo4wildlife.eu
Twitter: @EO4wildlife
This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 687275.
