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Mapping Fields

DFS Lite mappings describe how a source value becomes useful inside FactVerse. Use this reference when creating, reviewing, or troubleshooting mappings.

Field summary​

FieldMeaningExample
Source pathLocation of the source value./AHU-01/SupplyAirTemp
Source typeType of source value or connector origin.BACnet, OPC UA, REST
Target entityOperational object that receives the mapped value.asset, point, workOrder
Target IDStable target identifier.asset-ahu-01
Target fieldField on the target entity.temperature, status, pressure
Transform expressionUnit or format conversion.Fahrenheit to Celsius
UnitUnit after mapping.C, kWh, Pa
Range minimumLowest expected value.0
Range maximumHighest expected value.100
Topology tagRelationship or system tag.chilled-water-loop
Physics typePhysical quantity category.temperature, flow, power
AI confidenceConfidence score for a mapping suggestion.Review high and low scores before applying.

Source path​

Source path identifies where the value came from.

Examples:

  • OPC UA node ID;
  • BACnet object path;
  • Modbus register;
  • MQTT topic and payload field;
  • REST response JSON path;
  • CSV column;
  • JDBC table and column.

Keep source paths traceable so operators can inspect source data when values look wrong.

Target entity​

Target entity defines what kind of operational object receives the data.

Common targets:

  • asset;
  • equipment;
  • point;
  • meter;
  • location;
  • work order;
  • inspection record;
  • dataset field.

Use the target type that matches the downstream workflow.

Target ID​

Target ID must be stable across source refreshes.

Good target IDs:

  • come from the FactVerse asset model;
  • match the approved asset registry;
  • remain stable across naming changes;
  • can be explained by the source owner.

Use a stable identifier as the target ID because display names can change.

Target field​

Target field defines the destination field on the target entity.

Examples:

  • status;
  • temperature;
  • pressure;
  • flowRate;
  • energyConsumption;
  • alarmSeverity;
  • lastInspectionTime.

Use consistent field names across similar assets.

Transform expression​

Transform expressions handle unit, format, or identity conversion.

Common transformations:

  • Fahrenheit to Celsius;
  • string status to normalized enum;
  • source equipment code to asset ID;
  • cumulative meter value to interval value;
  • timestamp format normalization.

Validate transformed values with preview and sync history.

Unit​

Unit should describe the mapped value after transformation.

Examples:

  • C;
  • Pa;
  • kPa;
  • kWh;
  • m3/h;
  • rpm;
  • %.

Keep unit notation consistent within a site or project.

Range minimum and maximum​

Range checks help detect wrong units, bad scaling, or source errors.

Examples:

  • chilled water temperature range;
  • room humidity range;
  • motor vibration range;
  • power meter range;
  • pressure range.

Set ranges with source-owner input.

Topology tag​

Topology tags help relate values to operational structure.

Examples:

  • chilled-water-loop;
  • air-handling;
  • compressor-train;
  • production-line-1;
  • warehouse-zone-a.

Use topology tags when downstream workflows need system context.

Physics type​

Physics type classifies the physical quantity.

Examples:

  • temperature;
  • pressure;
  • flow;
  • vibration;
  • power;
  • energy;
  • humidity;
  • status.

Physics type helps downstream analytics and simulation workflows interpret values consistently.

AI confidence​

AI-assisted mapping suggestions can include confidence. Treat confidence as a review signal.

Review suggestions against:

  • source path;
  • target asset;
  • unit;
  • value range;
  • naming convention;
  • source owner input.

Apply a suggestion only after the mapping reviewer accepts it.

Validation checklist​

Before saving mappings:

  • source path exists;
  • preview returns recent values;
  • target ID is stable;
  • target field is correct;
  • transform expression is tested;
  • unit is correct;
  • range checks match operational expectations;
  • topology and physics fields are useful for downstream workflows.

Next step​

Use Map Source Fields to Operational Targets for the step-by-step workflow.