PRovenance Information in MAterials science (PRIMA)¶
The PRovenance Information in MAterials science (PRIMA) ontology is designed to capture provenance information in the materials science domain [1]. It provides a structured vocabulary for describing research activities and the associated agents, equipment, software, techniques, settings, datasets, and other entities involved in materials science workflows [1].
PRIMA supports the semantic description of experimental and computational research workflows, helping to improve traceability, interoperability, and reuse of materials science data [1]. Its provenance-oriented approach complements broader efforts within the PRIMA initiative to provide consistent terminology and metadata for materials science and engineering [2]. Starting from PRIMA v3, the ontology is further aligned with BFO and PMDco to improve interoperability with other materials science ontology resources [1].
Example Usage: Annotate a materials science dataset with PRIMA terms to describe the research activity, involved users, equipment, software, techniques, experimental or computational steps, data acquisition and analysis activities, and resulting data products, thereby preserving provenance information needed for traceability and reuse [1].
Metrics & Statistics¶
Total Nodes |
444 |
Total Edges |
1073 |
Root Nodes |
18 |
Leaf Nodes |
135 |
Classes |
67 |
Individuals |
0 |
Properties |
67 |
Maximum Depth |
14 |
Minimum Depth |
0 |
Average Depth |
4.39 |
Depth Variance |
16.39 |
Maximum Breadth |
27 |
Minimum Breadth |
2 |
Average Breadth |
7.80 |
Breadth Variance |
48.56 |
Term Types |
0 |
Taxonomic Relations |
186 |
Non-taxonomic Relations |
1 |
Average Terms per Type |
0.00 |
Usage Example¶
Use the following code to import this ontology programmatically:
from ontolearner.ontology import PRIMA
ontology = PRIMA()
ontology.load("path/to/PRIMA-ontology.ttl")
# 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