Development of Safety Domain Ontology Knowledge Base for Fall Accidents

Extensive research in the field of construction safety has predominantly focused on identifying the causes and impacts of construction accidents, evaluating safety plans, assessing the effectiveness of safety education materials, and analyzing relevant policies. However, comparatively limited attention has been given to the systematic formation, management, and utilization of safety-related information and knowledge. Despite significant advancements in information and knowledge management technologies across the architecture, engineering, and construction (AEC) industries, their application in construction safety remains underdeveloped. This study addresses this gap by proposing a novel ontology-based framework specifically designed for construction safety management. Unlike previous models, the proposed ontology integrates diverse safety regulations and terminologies into a unified and semantically structured knowledge model. It comprises three primary superclasses covering key areas of construction safety, with an initial focus on fall hazards—one of the most frequent and severe risks, particularly in roofing activities. This domain-specific approach not only improves semantic clarity and standardization but also enhances reusability and extensibility for other risk domains. The ontology was developed using established methodologies and validated through reasoning tools and competency questions. By providing a formally structured, logic-driven knowledge base, the model supports automated safety reasoning, facilitates communication among stakeholders, and lays the foundation for future intelligent safety management systems in construction. This research contributes a validated, extensible, and regulation-aligned ontology model that addresses critical challenges in safety information integration, sharing, and application.

Authors

Institutions

Publication Details

Journal
Buildings
Published
2025-06-30
DOI
https://doi.org/10.3390/buildings15132299
Citations
3
Primary Topic
Semantic Web and Ontologies
Type
article
Field-Weighted Citation Impact
7.44

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Development of Safety Domain Ontology Knowledge Base for Fall Accidents

Sangyun Shin, Hyunsoung Park
3 citations
Buildings
Semantic Web and Ontologies
7.44
article

Development of Safety Domain Ontology Knowledge Base for Fall Accidents

Sangyun Shin, Hyunsoung Park
article en
3 citations

Abstract

Extensive research in the field of construction safety has predominantly focused on identifying the causes and impacts of construction accidents, evaluating safety plans, assessing the effectiveness of safety education materials, and analyzing relevant policies. However, comparatively limited attention has been given to the systematic formation, management, and utilization of safety-related information and knowledge. Despite significant advancements in information and knowledge management technologies across the architecture, engineering, and construction (AEC) industries, their application in construction safety remains underdeveloped. This study addresses this gap by proposing a novel ontology-based framework specifically designed for construction safety management. Unlike previous models, the proposed ontology integrates diverse safety regulations and terminologies into a unified and semantically structured knowledge model. It comprises three primary superclasses covering key areas of construction safety, with an initial focus on fall hazards—one of the most frequent and severe risks, particularly in roofing activities. This domain-specific approach not only improves semantic clarity and standardization but also enhances reusability and extensibility for other risk domains. The ontology was developed using established methodologies and validated through reasoning tools and competency questions. By providing a formally structured, logic-driven knowledge base, the model supports automated safety reasoning, facilitates communication among stakeholders, and lays the foundation for future intelligent safety management systems in construction. This research contributes a validated, extensible, and regulation-aligned ontology model that addresses critical challenges in safety information integration, sharing, and application.

BuildingsVol. 15(13)
University of Evansville (US), Keimyung University (KR)
Keimyung University
Openalex Percentile: Top 3%
Semantic Web and Ontologies
7.44
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Development of Safety Domain Ontology Knowledge Base for Fall Accidents — Sangyun Shin, Hyunsoung Park · Buildings (2025) | TGRS Research Map | TGRS