Developing Ontology-Based Nuclear Accident Knowledge Base

The society acquired vast amounts of data from past major nuclear accidents, then learned the causes of those accidents, the methods to mitigate their adverse effects, and accident-prevention measures. However, it is challenging to store and organize highly technical knowledge related to nuclear accidents and share it in ways that meet our purposes. That is one reason we still do not have a centralized public database of nuclear incidents, despite efforts by international organizations such as the IAEA and academic institutions. Internet searches and AI queries return answers based on publicly available data sources without curation, thereby posing a risk of biased knowledge representation.

We aim to develop a prototype nuclear accident knowledge base using an ontology-based approach to establish the structured management system of nuclear accident-related knowledge. The top-level classes of the Basic Formal Ontology (BFO) are reviewed and utilized to design the base ontology hierarchy of the entities involved in nuclear accidents. The past ontology work in the nuclear and non-nuclear industries is reviewed, and some of their proposed classes and relationships were imported into the nuclear accident knowledge base structure. The classes, entities, and relations among those entities, and data properties relevant to the knowledge base are defined and are entered in protégé ontology editing software, whose ontology design can be shared digitally with interested parties.

During the development of the ontology structure, five knowledge-ambiguity factors were identified as potential focal points for developing the nuclear accident knowledge base. The ambiguity factors include: 1) terminology definition, 2) location definition, 3) temporal change in knowledge needs, 4) contamination definition, and 5) accident cause definition. When sharing nuclear accident knowledge, these factors must be considered to minimize confusion during the user’s knowledge-finding endeavour. By dissecting those ambiguity factors and providing a logical structure for nuclear accident-related data, this prototype knowledge base will assist in developing a public centralized nuclear accident knowledge base that can serve as a trustworthy data depository for preventing future accidents as well as enabling prompt recovery from the adverse effects of those accidents.

 

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