README.md

metadata

license: mit
language:
  - en
tags:
  - OntoLearner
  - ontology-learning
  - scholarly_knowledge
pretty_name: Scholarly Knowledge

Scholarly Knowledge Domain Ontologies

Overview

The scholarly_knowledge domain encompasses ontologies that systematically represent the intricate structures, processes, and management systems inherent in scholarly research, academic publications, and the supporting infrastructure. This domain is pivotal in facilitating the organization, retrieval, and dissemination of academic knowledge, thereby enhancing the precision and efficiency of scholarly communication and collaboration. By providing a formalized framework for knowledge representation, it supports the advancement of research methodologies and the integration of interdisciplinary insights.

Ontology ID	Full Name	Classes	Properties	Individuals
CSO	Computer Science Ontology (CSO)	0	0	0
OPMW	Open Provenance Model for Workflows (OPMW)	59	87	2
OBOE	Extensible Observation Ontology (OBOE)	478	30	0
SWO	Software Ontology (SWO)	2746	165	443
SEPIO	Scientific Evidence and Provenance Information Ontology (SEPIO)	129	117	21
LexInfo	LexInfo (LexInfo)	334	189	276
EXPO	Ontology of Scientific Experiments (EXPO)	347	78	0
SPDocument	SMART Protocols Ontology: Document Module (SP-Document)	400	43	45
SPWorkflow	SMART Protocols Ontology: Workflow Module (SP-Workflow)	419	17	5
NFDIcore	National Research Data Infrastructure Ontology (NFDIcore)	302	102	0
TribAIn	Tribology and Artificial Intelligence Ontology (TribAIn)	241	64	21
DCAT	Data Catalog Vocabulary (DCAT)	10	39	0
EURIO	EUropean Research Information Ontology (EURIO)	44	111	0
Metadata4Ing	Metadata for Intelligent Engineering (Metadata4Ing)	48	100	47
FRAPO	Funding, Research Administration and Projects Ontology (FRAPO)	97	125	25
FRBRoo	Functional Requirements for Bibliographic Records - object-oriented (FRBRoo)	83	0	0
DUO	Data Use Ontology (DUO)	45	1	0
DataCite	DataCite Ontology (DataCite)	19	10	70
Framester	Framester (Framester)	59	77	0
CiTO	Citation Typing Ontology (CiTO)	10	101	0
VOAF	Vocabulary of a Friend (VOAF)	3	21	1
AIISO	Academic Institution Internal Structure Ontology (AIISO)	22	0	0
PreMOn	Pre-Modern Ontology (PreMOn)	15	16	0
PPlan	Ontology for Provenance and Plans (P-Plan)	11	14	0
WiLD	Workflows in Linked Data (WiLD)	16	0	4

Dataset Files

Each ontology directory contains the following files:

1. <ontology_id>.<format> - The original ontology file
2. term_typings.json - Dataset of term to type mappings
3. taxonomies.json - Dataset of taxonomic relations
4. non_taxonomic_relations.json - Dataset of non-taxonomic relations
5. <ontology_id>.rst - Documentation describing the ontology

Usage

These datasets are intended for ontology learning research and applications. Here's how to use them with OntoLearner:

from ontolearner import LearnerPipeline, AutoLearnerLLM, Wine, train_test_split

# Load ontology (automatically downloads from Hugging Face)
ontology = Wine()
ontology.load()

# Extract the dataset
data = ontology.extract()

# Split into train and test sets
train_data, test_data = train_test_split(data, test_size=0.2)

# Create a learning pipeline (for RAG-based learning)
pipeline = LearnerPipeline(
    task="term-typing",  # Other options: "taxonomy-discovery" or "non-taxonomy-discovery"
    retriever_id="sentence-transformers/all-MiniLM-L6-v2",
    llm_id="mistralai/Mistral-7B-Instruct-v0.1",
    hf_token="your_huggingface_token"  # Only needed for gated models
)

# Train and evaluate
results, metrics = pipeline.fit_predict_evaluate(
    train_data=train_data,
    test_data=test_data,
    top_k=3,
    test_limit=10
)

For more detailed examples, see the OntoLearner documentation.

Citation

If you use these ontologies in your research, please cite:

@software{babaei_giglou_2025,
  author       = {Babaei Giglou, Hamed and D'Souza, Jennifer and Aioanei, Andrei and Mihindukulasooriya, Nandana and Auer, Sören},
  title        = {OntoLearner: A Modular Python Library for Ontology Learning with LLMs},
  month        = may,
  year         = 2025,
  publisher    = {Zenodo},
  version      = {v1.0.1},
  doi          = {10.5281/zenodo.15399783},
  url          = {https://doi.org/10.5281/zenodo.15399783},
}