Trusted data. Transparent quality information.
The EO DataHub provides access to datasets from trusted sources, supported by transparent quality information to help users understand how data has been validated and whether it is suitable for their needs.
Quality assurance is embedded across the platform to support confident use of Earth Observation data for research, policy and commercial applications.
Our Approach to Quality Assurance
The EO DataHub includes a dedicated Quality Assurance (QA) service, led by the National Physical Laboratory (NPL), providing clear and accessible information about dataset quality.
This includes:
- Verified dataset provenance
- Documented validation methods
- Quantitative quality metrics
- Standardised metadata and quality indicators
Datasets are assessed through defined validation processes to ensure they meet expected performance standards and are suitable for use across a range of applications.
Integrated into the Platform
Quality information is integrated directly into the DataHub experience, allowing users to assess data as part of their workflow.
Users can:
- View quality indicators within the data catalogue
- Access validation results alongside dataset metadata
- Compare datasets using consistent quality measures
This ensures that quality is not separate from the data, but part of how it is discovered and used.
Supporting Different Users
The QA service is designed to support both expert and non-expert users.
In addition to technical validation metrics, the platform is evolving to provide more user-focused guidance on whether datasets are suitable for specific applications.
This supports a shift from technical quality assessment towards practical, decision-ready insight.
Continous Improvement
The EO DataHub continues to expand its quality assurance capabilities by incorporating additional validation methods and enabling contributions from domain experts.
This ensures the platform maintains high standards as new datasets, providers and use cases are introduced.
Quality Across Data and Applications
Quality assurance within the EO DataHub applies to both datasets and the applications used to analyse them.
- Data quality focuses on the accuracy, provenance and validation of datasets
- Application quality ensures that tools and workflows operate reliably and produce consistent, reproducible results
Together, this supports confidence in both the data and the insights generated from it.
Learn More
For dataset-specific quality information, refer to the metadata and documentation available within the platform.
