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Data Lineage (Provenance)
- Tracks data origins and transformations to ensure transparency, integrity, and traceability.
- Key for error detection, regulatory compliance, and decision-making trustworthiness.
- Challenges: Scalability, privacy, and cross-platform alignment.
Harmonization of Data from Heterogeneous Sources
- Standardizes and integrates data from diverse formats and systems.
- Uses ETL, data cleaning, and semantic integration.
- Challenges: Managing quality, metadata consistency, and structural differences.
Use of Metadata to Automate Data Management
- Automates data discovery, quality management, and governance using metadata.
- Key for indexing, policy enforcement, and consistency monitoring.
- Challenges: Ensuring metadata consistency and managing scale.
Rich Descriptions of Sensing Devices and Actuators
- Provides detailed specs on sensors and actuators (e.g., type, range, precision).
- Crucial for understanding device impact on data accuracy and system performance.
- Challenges: Keeping descriptions up-to-date and ensuring interoperability.
Usage of Sensing Devices and Actuators by Instruments
- Focuses on how sensors and actuators interact with instruments for data collection and control.
- Key for integration, data flow, calibration, and maintenance.
- Challenges: Interoperability, accuracy, and real-time performance.