Native Data Types

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Instrumentation Archetypes

• Signals: These are variations in physical quantities or electromagnetic fields over time or space, essential for information transmission. Classified into analog or digital, and further into continuous or discrete forms, signals are key to capturing the dynamic behavior of systems and their environmental interactions through variations in amplitude, frequency, and phase.
• Measurements: Numerical values extracted from signals, measurements provide quantifiable data on specific physical aspects. Obtained through precise sensor and instrument readings, they cover essential parameters like temperature, pressure, and velocity. The transformation from raw signals to measurements involves detection, digital conversion, and calibration, ensuring data accuracy.
• Parameters: Representing fixed or semi-fixed values, parameters define system characteristics or model properties. They include physical dimensions, operational limits, and environmental factors, crucial for system description and control settings, such as in feedback loops where they adjust system behavior for optimal performance.

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Streaming Archetypes

To enhance time-series analysis, Celestra Space introduces three Data Series Archetypes, each tailored to capture and model data across temporal dimensions:

• Value Series: The Value Series archetype is pivotal for modeling time-stamped numerical data. It provides a granular view of how measurements evolve over time, enabling sophisticated trend analysis and predictive modeling.

• Event Series: The Event Series archetype is designed to represent discrete, time-stamped occurrences within a system. It is particularly suited for modeling events or state transitions that are not continuous by nature but occur at specific intervals or under certain conditions. This includes system alerts, operational status changes, and other critical events, providing clear insights into system behavior and aiding in event-driven analysis and response strategies.

• State Series: Focusing on the continuity of system conditions, the State Series archetype captures sequences of states or modes over time. This continuous data stream is vital for understanding system operations, including on/off states and start/stop cycles.

The Celestra Space platform leverages these data types and series archetypes to equip users with powerful tools for data-driven analysis and decision-making in aerospace and beyond. This structured approach to data categorization and time-series modeling ensures that users can effectively harness the full potential of their data, driving innovation and operational excellence.

Celestra Space offers APIs that supercharge your space software, unlocking the potential for truly captivating outcomes. Create your account today!