Funding, Research Administration and Projects Ontology (FRAPO)

The Funding, Research Administration and Projects Ontology (FRAPO) is an ontology for describing administrative information relating to grant funding and research projects [1] [2]. It provides a structured vocabulary for representing grant applications, funding bodies, research projects, project partners, project-related roles, and other administrative information commonly managed in Current Research Information Systems (CRIS) [1]. FRAPO is CERIF-compliant and written in OWL 2 DL, making it suitable for representing research administration information in semantic web and linked data environments [2].

The ontology defines classes and properties for modeling funding, project administration, organizations, agents, and project-related relationships [1]. It imports FOAF and is designed to work with related SPAR ontologies such as SCoRO for scholarly roles and FaBiO for documents such as grant applications, project plans, project reports, datasets, and journal articles [1]. This allows FRAPO to represent research administration metadata while linking it to people, organizations, roles, outputs, and related documents [1].

Typical applications of FRAPO include research information management, grant administration, project reporting, Current Research Information Systems, funding analysis, institutional reporting, and integration of research project metadata across repositories and administrative systems [1] [2]. By providing a standardized semantic framework, FRAPO enhances interoperability, data integration, and knowledge discovery in research administration and project management contexts [2].

Example Usage: Annotate a research project with FRAPO terms to specify the funding body, grant application, project partners, administrative roles, project status, and related project documents. This enables semantic search, grant tracking, institutional reporting, and integration with research administration platforms and CRIS systems [1] [2].

Metrics & Statistics

Graph Statistics

Total Nodes

539

Total Edges

1076

Root Nodes

18

Leaf Nodes

274
Knowledge Coverage Statistics

Classes

97

Individuals

25

Properties

125
Hierarchical Metrics

Maximum Depth

3

Minimum Depth

0

Average Depth

0.68

Depth Variance

1.08
Breadth Metrics

Maximum Breadth

18

Minimum Breadth

3

Average Breadth

7.00

Breadth Variance

40.50
LLMs4OL Dataset Statistics

Term Types

25

Taxonomic Relations

82

Non-taxonomic Relations

0

Average Terms per Type

8.33

Usage Example

Use the following code to import this ontology programmatically:

from ontolearner.ontology import FRAPO

ontology = FRAPO()
ontology.load("path/to/FRAPO-ontology.rdf")

# 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