SMART Protocols Ontology: Document Module (SP-Document)

SMART Protocols Ontology: Document Module is an ontology designed to represent metadata used to report an experimental protocol [1] [2]. It provides a structured vocabulary for representing experimental protocol documents, protocol metadata, and related descriptive information, supporting semantic documentation of experimental protocols [1] [2].

The ontology employs a class-based modeling approach, defining classes for protocol-related metadata such as protocol title, identifier, authorship, application, provenance, reagents, instruments, samples, objectives, and other information needed to report an experimental protocol [1] [2]. Hierarchies and properties are used to organize protocol-document information into structured categories, enabling retrieval, comparison, and analysis of experimental protocol metadata [1]. SP-Document supports the integration of protocol descriptions from different sources, promoting interoperability and data-driven research in experimental protocol documentation [2].

Typical applications of SP-Document include experimental protocol reporting, protocol metadata standardization, semantic annotation of protocol documents, protocol repository development, protocol discovery, and integration of protocol descriptions with scientific workflow and laboratory information systems [1] [2]. By providing a standardized vocabulary and framework, SP-Document enhances interoperability, reuse, and semantic search in the field of experimental protocol documentation [1] [2].

Example Usage: Annotate an experimental protocol with SP-Document terms to specify the protocol title, identifier, authors, application, provenance, reagents, instruments, samples, objectives, and related metadata. This enables semantic search, protocol comparison, metadata integration, and use within experimental protocol documentation platforms [1] [2].

Metrics & Statistics

Graph Statistics

Total Nodes

1489

Total Edges

3044

Root Nodes

18

Leaf Nodes

908
Knowledge Coverage Statistics

Classes

400

Individuals

45

Properties

43
Hierarchical Metrics

Maximum Depth

9

Minimum Depth

0

Average Depth

3.96

Depth Variance

4.49
Breadth Metrics

Maximum Breadth

69

Minimum Breadth

8

Average Breadth

32.80

Breadth Variance

369.36
LLMs4OL Dataset Statistics

Term Types

45

Taxonomic Relations

474

Non-taxonomic Relations

73

Average Terms per Type

2.65

Usage Example

Use the following code to import this ontology programmatically:

from ontolearner.ontology import SPDocument

ontology = SPDocument()
ontology.load("path/to/SPDocument-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

References