Digital Buildings Ontology (DBO)

The Digital Buildings Ontology (DBO) is a structured vocabulary developed by Google for representing information about buildings and building-installed equipment. DBO provides a semantic model for describing building assets, their locations, types, operational states, and relationships, supporting digital twins and smart building applications. The ontology enables integration of data from building management systems, IoT devices, and facility management platforms, facilitating automated monitoring, control, and analytics. DBO is designed to be extensible and interoperable, allowing organizations to adapt the ontology to their specific building types and operational requirements. By providing standardized terms and relationships, DBO supports data-driven decision-making, energy optimization, and predictive maintenance in digital buildings. The ontology is open source and maintained by a community of contributors, ensuring ongoing development and alignment with industry needs.

Example Usage: Annotate a smart building system with DBO terms to describe HVAC equipment, lighting systems, sensors, and their spatial locations, enabling automated control and integration with building management platforms.

Metrics & Statistics

Graph Statistics

Total Nodes

13152

Total Edges

32491

Root Nodes

1

Leaf Nodes

686
Knowledge Coverage Statistics

Classes

3032

Individuals

35

Properties

7
Hierarchical Metrics

Maximum Depth

3

Minimum Depth

0

Average Depth

1.57

Depth Variance

0.82
Breadth Metrics

Maximum Breadth

3

Minimum Breadth

1

Average Breadth

1.75

Breadth Variance

0.69
LLMs4OL Dataset Statistics

Term Types

35

Taxonomic Relations

18738

Non-taxonomic Relations

12

Average Terms per Type

2.06

Usage Example

Use the following code to import this ontology programmatically:

from ontolearner.ontology import DBO

ontology = DBO()
ontology.load("path/to/DBO-ontology.rdf")

# Extract datasets
data = ontology.extract()

# Access specific relations
term_types = data.term_typings
taxonomic_relations = data.type_taxonomies
non_taxonomic_relations = data.type_non_taxonomic_relations