Tag Resolution

Resolves tags by navigating the ISA-95 and Purdue Model asset hierarchy. Instead of flat tag lists, the system understands parent-child relationships.

• Path-Based Lookup: Resolves Site1.Area2.Line3.Filler4.Temp by traversing the logical tree.
• Metadata Inheritance: A sensor automatically inherits site, area, and line metadata from its ancestors, eliminating manual tagging.
• Contextual Awareness: Distinguishes between Line3.Filler4.Temp and Line3.Pasteurizer.Temp without ambiguity.

Decouples the logical tag name from the underlying industrial protocol. A single tag can resolve to OPC UA, Modbus, MQTT Sparkplug, or EtherNet/IP without the consumer knowing the transport.

• Driver Abstraction Layer: The resolution engine maps the logical path to a specific protocol driver and register address.
• Protocol Translation: Reads from a Modbus register and publishes the resolved value to an MQTT topic seamlessly.
• Legacy Integration: Wraps proprietary PLC protocols behind a standard, discoverable interface.

Resolution returns not just the current value, but the complete digital twin context of the tag.

• Value: The live sensor reading (e.g., 152.3).
• Timestamp: The precise source timestamp, not the time of resolution.
• Data Type & Engineering Units: Float32, Degrees Celsius.
• Quality/Status: OPC UA Good, Uncertain, or Bad quality flags.
• Asset Metadata: Manufacturer, model, calibration date, and documentation links.

Enables plug-and-play integration where consumers discover tags at runtime rather than relying on hard-coded static maps.

• Browsing: A dashboard can query Line3.* to discover all available tags under that node.
• Late Binding: An analytics job can be configured to process *.Filler.Temp across all lines, automatically picking up new lines as they are commissioned.
• Schema Registry Integration: Resolved data structures are validated against a central Schema Registry to ensure type consistency.

Resolution is not read-only. It provides a secure path for control commands back to the physical asset.

• Write Verification: Resolves the target tag, validates the data type and range against the schema, and executes the write through the correct protocol driver.
• Role-Based Access Control (RBAC): Write resolution is gated by user roles, preventing unauthorized actuation.
• Audit Trail: Every resolved write command is logged with the user, timestamp, and value for compliance.

High-frequency resolution requests are optimized through intelligent caching layers to prevent overwhelming downstream data sources.

• Time-To-Live (TTL) Caching: Metadata (which changes rarely) is cached aggressively, while real-time values bypass the cache or use sub-second TTLs.
• Subscription-Based Updates: Instead of polling, the resolver subscribes to OPC UA PubSub or MQTT Sparkplug topics for changed values only.
• Bulk Resolution: APIs support resolving thousands of tags in a single request, reducing network overhead for large visualization screens.

The process of enriching raw tags with machine-readable context. Tag resolution doesn't just return a value; it returns metadata about the value's meaning, unit of measure, and engineering limits.

• Mechanism: Links sensor tags to formal ontologies or knowledge graphs.
• Example: A tag TT-401 is annotated as Temperature Sensor, Degrees Celsius, Min: -20, Max: 150.
• Value: Enables automated reasoning and prevents misinterpretation of raw data.

A formal agreement between a data producer and its consumers. For tag resolution, a data contract guarantees the schema, semantics, and quality of the resolved value.

• Guarantees: Defines the expected data type, valid range, and freshness threshold.
• Enforcement: A schema registry validates the contract upon resolution.
• Purpose: Prevents downstream pipeline breakage by ensuring the resolved tag meets the consumer's expectations.