Mapping Source Fields

Mappings tell DFS how a source value relates to an operational target. A mapping can bind a source tag, topic field, table column, file column, or API field to an asset, point, dataset field, or workflow field.

Use mapping after the source path has been validated through an operation that the connector supports: browse, poll read, inbound subscription, connector preview, or file import.

Prerequisites

Before mapping, confirm:

• connector test succeeds;
• a supported validation path confirms the candidate source identity and values;
• source owner has confirmed field meaning, unit, and expected range;
• the target asset, point, dataset field, or workflow field exists or has a stable planned ID;
• downstream consumers have agreed how stale, missing, or rejected values should be handled.

Mapping workflow

Source data inputs

Prepare:

• connector ID or connector name;
• source path or field name;
• target entity type;
• target ID when available;
• target field;
• unit and expected range;
• source owner or reviewer.

Mapping fields

Field	What it means
Source path	The source tag, object, topic field, table column, file column, or API field.
Source type	The type or shape of the source value.
Target entity	The operational target, such as asset, point, equipment, dataset field, or work record.
Target ID	The stable ID of the target object.
Target field	The field to update or populate.
Transform expression	A unit conversion or value normalization expression.
Unit	The unit expected by the target.
Range minimum / maximum	Values outside this range should be reviewed.
Topology tag	Optional topology context for facility, network, or equipment relationships.
Physics type	Optional semantic hint for simulation or Physical AI workflows.
AI confidence	Confidence attached to an AI-assisted suggestion. Review before applying.

Add a manual mapping

1. Open Data Integration > Connectors.
2. Open the connector.
3. Open the mapping area.
4. Add a mapping rule.
5. Select or enter the source path.
6. Select the target entity.
7. Enter the target ID when the target object already exists.
8. Select the target field.
9. Add transform expression when source and target formats differ.
10. Save the mapping.
11. Preview mapped output.
12. Run sync and check sync history.

Review AI-assisted suggestions

If AI mapping suggestions are available, treat them as draft suggestions.

Review:

• source path;
• suggested target;
• confidence;
• unit;
• expected range;
• asset identity;
• whether similar tags could be confused.

Apply only the suggestions that a user or data owner can defend. Keep uncertain suggestions out of production sync until the source owner confirms them.

Common mapping examples

Source value	Target	Mapping concern
chws_temp_f	chilled water supply temperature	Convert Fahrenheit to Celsius if the target expects Celsius.
AHU-03.status	asset operating status	Normalize source status values to target status values.
meter_kw	electrical meter point	Confirm meter, zone, and time interval.
alarm.severity	alarm severity field	Normalize source severity labels.
work_order_id	work record external ID	Preserve external ID for traceability.

Validate the mapping

After saving and syncing, check:

• mapped values appear on the expected target;
• units are correct;
• timestamps are aligned;
• impossible values are rejected or flagged;
• failed rows are visible for review;
• downstream pages or workflows show the expected source timestamp.

When to change a mapping

Update a mapping when:

• source tag names change;
• equipment IDs are corrected;
• units or scale factors are updated;
• the target asset model changes;
• source value quality degrades;
• a reviewer finds incorrect target binding.

Record the reason for important mapping changes so downstream users can understand why data changed.