National Research Data Infrastructure Ontology (NFDIcore)

The National Research Data Infrastructure (NFDI) initiative has led to the formation of various consortia, each focused on developing a research data infrastructure tailored to its specific domain. To ensure interoperability across these consortia, the NFDIcore ontology has been developed as a mid-level ontology for representing metadata related to NFDI resources, including individuals, organizations, projects, data portals, and more. It provides a structured vocabulary for representing research data infrastructure, supporting both theoretical and experimental research in research data management.

The ontology employs a class-based modeling approach, defining classes for different types of research data infrastructure, metadata, and related entities, along with properties to describe their characteristics and interactions. Hierarchies are used to organize classes into categories, enabling efficient data retrieval and analysis. NFDIcore supports the integration of data from various sources, promoting interoperability and data-driven research in research data management.

Typical applications of NFDIcore include the development of new research data infrastructure methods, the optimization of research data management practices, and the integration of diverse datasets to support advanced analytics and knowledge discovery. By providing a standardized vocabulary and framework, NFDIcore enhances collaboration and innovation in the field of research data management.

Example Usage: Annotate a research data infrastructure project with NFDIcore terms to specify infrastructure types, metadata, and related entities, enabling semantic search and integration with research data management platforms.

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