File size: 2,132 Bytes
cdbdd16 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 |
The ontology of data analysis and management (EDAM)
========================================================================================================================
Overview
--------
EDAM is a domain ontology of data analysis and data management in bio- and other sciences, and science-based applications.
It comprises concepts related to analysis, modelling, optimisation, and data life cycle. Targetting usability by diverse users,
the structure of EDAM is relatively simple, divided into 4 main sections: Topic, Operation, Data (incl. Identifier), and Format.
:Domain: General Knowledge
:Category: General
:Current Version: 1.25-20240924T0027Z-unstable(1.26)
:Last Updated: 24.09.2024
:Creator: Federico Bianchini, Hervé Ménager, Jon Ison, Matúš Kalaš
:License: Creative Commons 4.0
:Format: OWL
:Download: `The ontology of data analysis and management (EDAM) Homepage <https://terminology.tib.eu/ts/ontologies/edam>`_
Graph Metrics
-------------
- **Total Nodes**: 12367
- **Total Edges**: 36215
- **Root Nodes**: 176
- **Leaf Nodes**: 8223
Knowledge coverage
------------------
- Classes: 3513
- Individuals: 0
- Properties: 12
Hierarchical metrics
--------------------
- **Maximum Depth**: 10
- **Minimum Depth**: 0
- **Average Depth**: 2.75
- **Depth Variance**: 4.24
Breadth metrics
------------------
- **Maximum Breadth**: 635
- **Minimum Breadth**: 5
- **Average Breadth**: 196.55
- **Breadth Variance**: 31795.52
Dataset Statistics
------------------
Generated Benchmarks:
- **Term Types**: 0
- **Taxonomic Relations**: 7916
- **Non-taxonomic Relations**: 1314
- **Average Terms per Type**: 0.00
Usage Example
-------------
.. code-block:: python
from ontolearner.ontology import EDAM
# Initialize and load ontology
ontology = EDAM()
ontology.load("path/to/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
|