HORIZON-CL6-2027-01-BIODIV-01 - Collaboration Opportunity

As Doğuş Teknoloji, we can contribute to this call with two alternatives:

- We can contribute by developing a robust big data platform designed to handle large-scale biodiversity datasets collected throughout the project. This platform will ensure comprehensive data cleaning, preprocessing, and transformation workflows, making the data ready for advanced AI and machine learning models. By implementing scalable data pipelines, we will enable efficient ingestion, harmonization, and integration of heterogeneous data sources, including omics-based datasets, in-situ observations, and remote sensing data. The platform will support FAIR principles, ensuring interoperability with European and global frameworks, and will provide APIs and dashboard interfaces for real-time data access and visualization.

- We can implement advanced workflows for anomaly detection, data cleaning, and deduplication to ensure the integrity and interoperability of biodiversity datasets collected from omics-based sources, in-situ observations, and remote sensing platforms. These processes will address inconsistencies and improve data quality, enabling reliable integration across diverse sensors and platforms in line with FAIR principles. Additionally, Generative AI (GenAI) will be explored for data collection and augmentation, particularly to fill gaps in underrepresented ecosystems and enhance training datasets for AI-driven applications such as habitat classification, ecosystem mapping, and biodiversity trend prediction. These efforts will strengthen the usability of multisensory data for predictive analytics and support the achievement of EU biodiversity and climate objectives.

We can satisfy the below scope/outcomes of the call:

- develop and validate fit-for-purpose multisensory biodiversity data integration systems, to enable omics-based and in-situ data harmonization and integration with remote sensing data from space or sub-orbital platforms, as well as socio-ecological and climatic data for enhancing assessment of ecosystem condition and degradation, and the predictive modelling of biodiversity trends at international, regional and European scales;