Given this background, we see a strong alignment with several C-R&I-As addressed in Topic 2. In particular:

• Decision support systems and FMIS enhancement. Experience developing multi-source data layers, integrating open, private, sensor-based and remote sensing data. Proven work in interoperability through semantic standards and knowledge graphs. Development of multi-criteria simulation and analytics tools, supporting transparent and user-friendly decision-making. Expertise in deriving business models and value-driven analytics, including explainability and ROI-oriented services.

• Farm modelling systems. Experience in forecasting models, including risk-driven predictions and cross-domain integration. Development of complex environmental and systems models, aligned with whole-farm or landscape approaches. Strong capacity in integrating sensor, phenology, weather, and crop data for advanced modelling and scenario analysis. Expertise in using models to support policy-oriented decision frameworks.

• Environmental challenges. Work on precision agriculture data pipelines, including IoT, robotics, and remote sensing integration. Knowledge graph–based approaches for mapping biodiversity, environmental suitability and sustainability indicators. Solutions for continuous soil and water monitoring, IoT-based risk detection and automation. Integration with long-term observation infrastructures and support for modelling soil carbon and health.

• Climate change adaptation strategies. Experience in data-driven resilience analysis, risk modelling and predictive systems for complex environments. Collaboration with domains requiring high-throughput phenotype data and sensor-based crop analysis. Development of transformational DSS and multi-horizon analytics, integrating environmental, climate and socio-economic dimensions.

Khaos Research is a research group at the University of Malaga specializing in data technologies, semantic interoperability, AI, and large-scale data management for agri-food and environmental domains.

We are very interested in joining a consortium that aims to address these challenges, contributing our expertise in:
• semantic data infrastructures
• FAIR data management
• geospatial analytics
• trustworthy AI for agriculture
• policy-related data engineering
• data-based service composition (via TITAN)

If this aligns with your ongoing plans or if you are forming a consortium, we would be pleased to discuss potential collaboration opportunities.

I would be happy to arrange a short meeting to explore synergies in more detail.