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Virtual Materials Marketplace Ontologies (VIMMP) |
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Overview |
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-------- |
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The Virtual Materials Marketplace (VIMMP) project is developing an open platform for providing |
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and accessing services related to materials modelling. Within VIMMP, a system of marketplace-level ontologies |
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is developed to characterize services, models, and interactions between users; the European Materials |
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and Modelling Ontology (EMMO, recently renamed while keeping the original acronym) is employed |
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as a top-level ontology. The ontologies are used to annotate data that are stored in the ZONTAL Space component |
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of VIMMP and to support the ingest and retrieval of data and metadata at the VIMMP marketplace front-end. |
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:Domain: Materials Science and Engineering |
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:Category: Materials Modeling |
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:Current Version: None |
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:Last Updated: 2021-01-02 |
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:Creator: Ilian T. Todorov, Martin Thomas Horsch, Michael A. Seaton, Silvia Chiacchiera |
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:License: Creative Commons Attribution 4.0 International (CC BY 4.0) |
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:Format: OWL |
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:Download: `Virtual Materials Marketplace Ontologies (VIMMP) Homepage <https://matportal.org/ontologies/VIMMP_ONTOLOGIES>`_ |
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Graph Metrics |
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- **Total Nodes**: 6149 |
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- **Total Edges**: 15298 |
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- **Root Nodes**: 841 |
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- **Leaf Nodes**: 1948 |
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Knowledge coverage |
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- Classes: 1234 |
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- Individuals: 911 |
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- Properties: 771 |
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Hierarchical metrics |
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-------------------- |
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- **Maximum Depth**: 20 |
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- **Minimum Depth**: 0 |
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- **Average Depth**: 3.17 |
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- **Depth Variance**: 12.15 |
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Breadth metrics |
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------------------ |
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- **Maximum Breadth**: 1383 |
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- **Minimum Breadth**: 3 |
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- **Average Breadth**: 263.38 |
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- **Breadth Variance**: 147256.81 |
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Dataset Statistics |
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------------------ |
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Generated Benchmarks: |
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- **Term Types**: 1763 |
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- **Taxonomic Relations**: 2474 |
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- **Non-taxonomic Relations**: 278 |
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- **Average Terms per Type**: 6.14 |
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Usage Example |
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------------- |
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.. code-block:: python |
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from ontolearner.ontology import VIMMP |
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# Initialize and load ontology |
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ontology = VIMMP() |
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ontology.load("path/to/ontology.OWL") |
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# Extract datasets |
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data = ontology.extract() |
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# Access specific relations |
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term_types = data.term_typings |
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taxonomic_relations = data.type_taxonomies |
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non_taxonomic_relations = data.type_non_taxonomic_relations |
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