The Modular Ontology for Materials and Data Science (MDS-Onto)¶
MDS-Onto is a domain-level ontology for Materials Data Science that provides structured terminology for representing materials-related data and applied data science concepts [1]. It is organized into six major modules: BuiltEnv, Exposure, Chemistry, Manufacture, Characterization, and Geospatial, with sub-modules such as FTIR, AFM, Chem-Rxn, PV-Module, and Accelerated Exposure [1].
MDS-Onto follows a modular approach, defining classes and properties for each module to represent the complexity of materials data science [1]. It supports semantic annotation, interoperability, data integration, and knowledge graph construction across heterogeneous materials science datasets and digital platforms [1]. By providing a standardized framework, MDS-Onto facilitates data sharing, cross-domain integration, and reuse of materials and data science knowledge [1].
Example Usage: Annotate a materials database with MDS-Onto terms to specify material properties, manufacturing or synthesis processes, characterization data, exposure conditions, photovoltaic module information, or geospatial metadata, enabling semantic search and integration with materials informatics platforms [1].
Metrics & Statistics¶
Total Nodes |
4362 |
Total Edges |
13095 |
Root Nodes |
92 |
Leaf Nodes |
2226 |
Classes |
1710 |
Individuals |
1 |
Properties |
169 |
Maximum Depth |
7 |
Minimum Depth |
0 |
Average Depth |
1.03 |
Depth Variance |
2.01 |
Maximum Breadth |
92 |
Minimum Breadth |
1 |
Average Breadth |
25.75 |
Breadth Variance |
1093.94 |
Term Types |
1 |
Taxonomic Relations |
1648 |
Non-taxonomic Relations |
259 |
Average Terms per Type |
1.00 |
Usage Example¶
Use the following code to import this ontology programmatically:
from ontolearner.ontology import MDSOnto
ontology = MDSOnto()
ontology.load("path/to/MDSOnto-ontology.owl")
# 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