Geo Ontology

Carbon Arc’s geo ontology standardizes and unifies location entities across datasets into consistent, easy-to-use geographic identifiers. These geo-spatial representations appear in our ontology as both primary entities and as filter options within the Platform Builder.

This framework allows users to build insights specifically around locations — for example, analyzing activity at Madison Square Garden or trends across California — or to add location-based filters to other entity-insight pairs, such as Credit Card Spend at Walmart locations in California. By harmonizing these geo identifiers, Carbon Arc makes it simpler to explore, compare, and analyze data with a consistent geographic lens.

Geo Crosswalks

Our Geo Ontology crosswalks across geo representations and is a framework that unifies location identifiers across different geographic boundary systems, acting as a consistent lookup layer. It lets you map between country codes, states, counties, MSAs, CBSAs, ZIP/postal codes, DMAs, and venue or POI IDs.

For example, if your data is tagged at the ZIP level but you need to roll it up to a DMA or MSA for media planning, the crosswalk handles that reliably.

In the Platform, this reference table supports:

• consistent rollups
• easier joins across merchant, consumer, and demographic data
• and clean handling of overlapping or ambiguous regions

This standardization ensures you can harmonize data feeds, aggregate metrics, and maintain consistent geographic definitions for reporting — even if the underlying providers use different keys.