National Research Data Infrastructure Ontology (NFDIcore)

The NFDIcore ontology is a mid-level ontology developed to support semantic interoperability across the consortia of the German National Research Data Infrastructure (NFDI) [1] [2]. It provides a shared semantic model for describing research infrastructure entities such as persons, organizations, projects, datasets, data portals, services, repositories, and related resources [1] [2].

NFDIcore is designed to bridge general concepts with more domain-specific models, allowing heterogeneous metadata from different NFDI consortia to be represented in a consistent and machine-readable form [2]. Its classes and relations support the description of organizational structures, research activities, digital resources, services, and the relationships between them [1]. This shared modeling layer enables metadata from different research data infrastructures to be linked, integrated, and queried across consortium boundaries [2].

Typical applications of NFDIcore include metadata integration, documentation of research infrastructures, semantic annotation of NFDI resources, modeling of projects and organizations, knowledge graph construction, and cross-consortium interoperability [1] [2]. By providing a common semantic framework, NFDIcore supports more consistent representation, discovery, and integration of research infrastructure metadata within the NFDI ecosystem [2].

Example Usage: Annotate an NFDI research infrastructure with NFDIcore terms to describe participating organizations, researchers, projects, datasets, repositories, data portals, services, and their relationships. This enables metadata from different NFDI consortia to be represented in a shared semantic structure and supports cross-consortium discovery and integration [1] [2].

Metrics & Statistics

Graph Statistics

Total Nodes

1849

Total Edges

3525

Root Nodes

84

Leaf Nodes

1029
Knowledge Coverage Statistics

Classes

302

Individuals

0

Properties

102
Hierarchical Metrics

Maximum Depth

13

Minimum Depth

0

Average Depth

2.85

Depth Variance

5.97
Breadth Metrics

Maximum Breadth

145

Minimum Breadth

1

Average Breadth

39.29

Breadth Variance

1732.49
LLMs4OL Dataset Statistics

Term Types

0

Taxonomic Relations

237

Non-taxonomic Relations

10

Average Terms per Type

0.00

Usage Example

Use the following code to import this ontology programmatically:

from ontolearner.ontology import NFDIcore

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