SMART Protocols Ontology: Workflow Module (SP-Workflow)

SP-Workflow module represents: i) the executable elements of a protocol; ii) the experimental actions and material entities that participate in instructions, such as samples/specimens, organisms, reagents, and instruments; and iii) the order of execution of the instructions [1] [2]. It provides a structured vocabulary for representing workflows, experimental actions, protocol instructions, material entities, and related data, supporting semantic representation of experimental protocol execution [1] [2].

The ontology employs a class-based modeling approach, defining classes for different types of protocol instructions, experimental actions, workflow elements, samples/specimens, organisms, reagents, instruments, and related data, along with properties to describe their characteristics and interactions [1] [2]. Hierarchies and relations are used to organize workflow concepts into structured categories, enabling retrieval, comparison, and analysis of experimental protocol workflows [1]. SP-Workflow supports the integration of protocol workflow information from various sources, promoting interoperability and data-driven research in experimental workflow management [2].

Typical applications of SP-Workflow include the semantic representation of experimental protocol execution, documentation of protocol instructions, optimization of experimental workflows, workflow comparison, protocol retrieval, and integration of workflow descriptions with laboratory information systems and workflow management platforms [1] [2]. By providing a standardized vocabulary and framework, SP-Workflow enhances interoperability, reuse, and semantic search in the field of experimental workflow documentation [1] [2].

Example Usage: Annotate an experimental workflow with SP-Workflow terms to specify protocol instructions, workflow steps, experimental actions, samples/specimens, organisms, reagents, instruments, and the order in which instructions should be executed. This enables semantic search, workflow comparison, protocol reuse, and integration with workflow management platforms [1] [2].

Metrics & Statistics

Graph Statistics

Total Nodes

1446

Total Edges

3017

Root Nodes

4

Leaf Nodes

834
Knowledge Coverage Statistics

Classes

419

Individuals

5

Properties

17
Hierarchical Metrics

Maximum Depth

13

Minimum Depth

0

Average Depth

7.23

Depth Variance

8.19
Breadth Metrics

Maximum Breadth

36

Minimum Breadth

3

Average Breadth

14.07

Breadth Variance

120.78
LLMs4OL Dataset Statistics

Term Types

5

Taxonomic Relations

577

Non-taxonomic Relations

22

Average Terms per Type

1.00

Usage Example

Use the following code to import this ontology programmatically:

from ontolearner.ontology import SPWorkflow

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