NIST Example Building 1 Model 1

NIST Example Building 1 Model 1#

Example Building 1 is a simplistic, reference tiny office building consisting of a single story with 5 rooms spanning 5 space types.

This reference building was developed for and first described in the journal article “Metadata Schemas and Ontologies for Building Energy Applications: A Critical Review and Use Case Analysis”.

Example Building 1 Model 1 is provided by current and former NIST staff and Pacific Northwest National Laboratory. See also PNNL Example Building 1 Model 2 for a different modeling approach for the same building.

Schematic view#

Contents#

This model contains a representation of the building architecture, mechanical system, and electrical/lighting system.

Source#

The model was created using TopQuadrant TopBraid Composer Maestro Edition.

Downloads#

What are these files?

Turtle file (original): This is the original source Turtle file that was provided to models.open223.info, usually as the output of some model creation tool.
Turtle file (compiled): This is the original Turtle file with all inferred relationships and values added through SHACL inference against the 223P ontology and other dependencies. You should use this file for any further processing. It does not contain any of the ontologies.
Turtle file (with all imports): This is the compiled Turtle file with all imports included in the file (223P ontology, QUDT ontology, and others). This is helpful when you do not want to deal with downloading and managing ontology dependencies. It is also much larger than the compiled file.
JSON-LD file (original): This is the original Turtle file converted to the JSON-LD format.

Turtle is a syntax for RDF (Resource Description Framework) that is easy to read and write. It is a popular format for representing linked data. Parsers and serializers are available in many programming languages. JSON-LD is a JSON-based format for linked data that is easy to use with JavaScript and other web technologies.

Queries#

Description	Query URL
Select all triples from model.	Query Link

Model Components#

Parent Class	Class	Instances
Equipment	Actuator	12
Equipment	Luminaire	12
Equipment	TemperatureSensor	10
Equipment	ElectricBreaker	6
Equipment	Damper	6
Equipment	HeatingCoil	3
Equipment	FlowSensor	3
Equipment	Fan	3
Equipment	Valve	3
Equipment	PressureSensor	2
Equipment	OccupantMotionSensor	2
Equipment	OccupantPresenceSensor	2
Equipment	SingleDuctTerminal	2
Equipment	AirHandlingUnit	1
Equipment	Boiler	1
Equipment	Filter	1
Equipment	Generator	1
Equipment	Thermostat	1
Equipment	Window	1
Equipment	Coil	1
Equipment	CoolingCoil	1
Equipment	Sensor	1
Equipment	IlluminanceSensor	1
Connection	Pipe	3
Connection	Duct	1
ConnectionPoint	InletConnectionPoint	73
ConnectionPoint	OutletConnectionPoint	70
ConnectionPoint	BidirectionalConnectionPoint	3
DomainSpace		19
Zone		8
Property	QuantifiableActuatableProperty	21
Property	QuantifiableObservableProperty	18
Property	EnumerableProperty	14
Property	QuantifiableProperty	12
Property	EnumeratedObservableProperty	4
Property	EnumeratedActuatableProperty	2

Load and Validate Model#

This code uses the BuildingMOTIF library to load the 223P ontology and the model file into a temporary in-memory instance. It then validates the model against the ontology. If the model is invalid, it will print the validation report.

To run this code, you need to have Java installed on your system. If you do not have Java installed, you can remove the shacl_engine='topquadrant' parameter from the BuildingMOTIF constructor. Be warned that without the shacl_engine='topquadrant' parameter, the validation process will be slower.

Note

BuildingMOTIF installation To install the buildingmotif library, you can use the following command:

pip install 'buildingmotif[topquadrant] @ git+https://github.com/NREL/buildingmotif.git@develop'

If you do not have Java installed, you can use the following command to install the library:

pip install 'buildingmotif @ git+https://github.com/NREL/buildingmotif.git@develop'

from buildingmotif import BuildingMOTIF
from buildingmotif.dataclasses import Library, Model
import logging

# Create a BuildingMOTIF object. If you do not have Java installed, remove the "shacl_engine" parameter
bm = BuildingMOTIF('sqlite://', shacl_engine='topquadrant', log_level=logging.ERROR)

# load 223P library. We will load a recent copy from the models.open223.info
# git repository; later, we will load this from the location of the actual standard
s223 = Library.load(ontology_graph="https://github.com/open223/models.open223.info/raw/main/ontologies/223p.ttl")

# load the model into the BuildingMOTIF instance
model = Model.create("urn:nist-bdg1-1")
model.graph.parse("https://models.open223.info/nist-bdg1-1.ttl")

# validate the model against 223P ontology
ctx = model.validate([s223.get_shape_collection()], error_on_missing_imports=False)

# print the validation result
print(f"Model is valid: {ctx.valid}")

# if the model is invalid, print the validation report
if not ctx.valid:
    print(ctx.report_string[:1000]) # first 1000 characters of the report

# BuildingMOTIF can also interpret the report to provide recommendations on fixes
for focus_node, diffs in ctx.get_reasons_with_severity("Violation").items():
    if len(diffs) == 0:
        continue
    print(focus_node)
    for diff in diffs:
        print("  - " + diff.reason())

---------------------------------------------------------------------------
ModuleNotFoundError                       Traceback (most recent call last)
Cell In[1], line 1
----> 1 from buildingmotif import BuildingMOTIF
      2 from buildingmotif.dataclasses import Library, Model
      3 import logging

ModuleNotFoundError: No module named 'buildingmotif'