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We will create a data platform that integrates RemoTrees system data with dense Earth Observation (EO) time series.
We will create a data platform that integrates RemoTrees system data with dense Earth Observation (EO) time series.
By leveraging the power of both in-situ and remote sensing systems, we aim to demonstrate true interoperability and synchronization that meets the rigorous standards of the Global Earth Observation System of Systems (GEOSS).
By leveraging the power of both in-situ and remote sensing systems, we aim to demonstrate true interoperability and synchronization that meets the rigorous standards of the Global Earth Observation System of Systems (GEOSS).
By combining detailed ground-based observations with comprehensive satellite data, our platform will provide unprecedented insights into ecosystem dynamics through an accessible interoperable data platform.
By combining detailed ground-based observations with comprehensive satellite data, our platform will provide unprecedented insights into ecosystem dynamics through an accessible interoperable data platform.
Progress Update (June 2025, Month 18 of the Project)
Progress Update (June 2025, Month 18 of the Project)
Work Package 3 in the first 18 months of the project successfully designed the prototype of the RemoTrees database. First, the database schema and interoperability framework were defined (delivered in December 2024), then the database prototype and description were developed (delivered in May 2025). This work successfully demonstrates the feasibility of a FROST-based data infrastructure that meets project requirements while maintaining compliance with international standards and ensuring scalability for the full RemoTrees sensor network deployment.
Work Package 3 in the first 18 months of the project successfully designed the prototype of the RemoTrees database. First, the database schema and interoperability framework were defined (delivered in December 2024), then the database prototype and description were developed (delivered in May 2025). This work successfully demonstrates the feasibility of a FROST-based data infrastructure that meets project requirements while maintaining compliance with international standards and ensuring scalability for the full RemoTrees sensor network deployment.
Technical Framework and Standards
Technical Framework and Standards
FAIR-Compliant Architecture
FAIR-Compliant Architecture
The data infrastructure is built on FAIR principles (Findable, Accessible, Interoperable, Reusable) to support data-intensive science. The team adopted the OGC SensorThings API (STA) standard as the primary framework, utilizing the Fraunhofer Open Source SensorThings server (FROST) implementation.
Performance Validation
Performance Validation
Comprehensive load testing was conducted to assess FROST's performance and scalability:
Data ingestion: Sustainable performance for expected bulk data loads
Data retrieval: Some API constraints identified for large-scale data management
Scalability confirmation: Architecture aligns with project requirements
Database Architecture Evolution
Database Architecture Evolution
The architecture was refined from initial dual-database design to a streamlined FROST-based solution:
The architecture was refined from initial dual-database design to a streamlined FROST-based solution:
HDF5 layer: Ensures scientific-standard format and ingestion-ready file structure
Quality control processing: Complete validation of time series data
Dedicated API access: Standardized data retrieval interface
Docker containerization: Ensures portability and resource isolation
Final database architecture adopted
Final database architecture adopted
Interoperability Framework
Interoperability Framework
Integration Capabilities
Integration Capabilities
GEOSS compatibility: Deep integration feasible through GEO DAB middleware
Copernicus services: Static dataset provision via periodic data freeze (API limitations noted)
Standard formats: JSON-based data exchange ensuring broad compatibility
Future Integration Plans
Future Integration Plans
Registration process initiation with GEOSS development team
Exploration of Copernicus data upload solutions
Interoperability deliverable scheduled for Month 45
Prototype Implementation
Prototype Implementation
Infrastructure Deployment
Infrastructure Deployment
Current hosting: Virtual Machine at Fondazione Edmund Mach
Future migration: Planned relocation to Nature 4.0 facilities
Architecture: Docker containers for enhanced portability and development efficiency
Data infrastructure - prototype environment
Data infrastructure - prototype environment
Docker architecture
Proof of Concept Results
Proof of Concept Results
Using test data from 10 devices over 70 days (July-September 2023):
Data volume: 6.2MB input → 5.5MB HDF5 → 98,000 Observation entities
Storage requirements: 22MB (Layer 0) + 146MB (Layer 1)
Processing time: ~5 hours ingestion
Scalability projection: 500 devices/month ≈ 5 days processing time
Interactive Dashboard
Interactive Dashboard
Built with Streamlit framework featuring:
Dynamic sensor data querying via SensorThings API
Custom filtering and time range selection
CSV data export functionality
Sensor fault detection and anomaly identification
Web-based interface for real-time monitoring
Example of sensor fault displayed on the interactive dashboard
Development and Access
Development and Access
Repository Management
Repository Management
Source code: Private GitHub repository for consortium collaboration
Distribution: Docker image availability for cross-platform testing
Access: VPN-secured prototype available to FEM internal devices
The RemoTrees database prototype GitHub repository
The RemoTrees database prototype GitHub repository
Next Steps
Next Steps
The prototype serves as the foundation for production-ready environment implementation, with continued monitoring and optimization planned.
Lead
Claudio Donati
Claudio Donati
Edmund Mach Foundation
Contact: claudio.donati@fmach.it
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