Space
Trusted space data provenance
Modern space systems - from Earth Observation (EO) platforms to Space Situational Awareness (SSA) infrastructures and digital twins - rely on increasingly complex data pipelines.
These systems combine data from satellites, ground sensors, simulations, and analytics platforms.
As these ecosystems grow, one question becomes critical: can the data and the results produced by these systems be trusted?
- Trusted data
Space systems ingest data from satellites, ground stations, sensors, and external datasets. Operators and analysts must know that the data they rely on is authentic, intact, and traceable to its origin.
- Traceable processing
Space data pipelines involve multiple processing layers, including calibration, data fusion, analytics, and modelling. Every transformation must remain traceable across distributed processing chains.
- Verifiable outcomes
Space applications increasingly rely on automated processing and simulations. It must be possible to verify how outputs were generated, from the original data to the models and processing pipelines used.
Built for trusted space operations
A trusted space data architecture must provide:
- End-to-end data provenance across space data pipelines
- Traceability of data transformations and processing chains
- Verifiable outputs from analytical and simulation systems
- Audit-ready evidence supporting operational and scientific decisions
These capabilities must operate without disrupting existing space data infrastructures.
Trust must be built into space data systems from the start.