**1. Introduction**

Nowadays, the ontology description languages RDF, OWL [1], description logics [2], and knowledge graphs provide a modern theoretical basis for the creation of systems and methods of acquisition, presentation, processing, and integration of knowledge in computer systems of artificial intelligence.

There are substantial considerations in favor of the predominant use of inductive reasoning in modern knowledge graphs instead of traditional deduction. Inductive reasoning rules based on consideration of possible alternatives (precedents) allow generating and verifying cognitive hypotheses (fuzzy knowledge) that cannot be obtained directly by deductive reasoning in the graph. Inductive inference is one of the basic technologies of semantic annotation of the WWW content, when it is necessary to refine, expand, and update existing graphs with new knowledge. With the help of the inductive inference, the problems of

classification and clustering of new entities in the semantic database of nuclear knowledge are solved [3].

The aim of the work presented in the chapter is to create a working prototype first and then a semantic web portal of knowledge in the domain of nuclear physics and nuclear power engineering based on ontologies and using databases deployed on cloud platforms [3]. The task of the study was to create the following graphs of nuclear knowledge:

entities and/or properties for ontology O. It can be said that interpretation functions

One of the attractive features of the semantic web is that it becomes possible to extract (infer) new knowledge from the facts which already exist in the knowledge graph. For this purpose, intelligent software agents are used, which are called reasoners. The way inference is carried out algorithmically is not specified in the ontology itself or in the corresponding OWL document, since OWL is a declarative language for ontologies describing. The correct answer to any question is determined by the semantics of the description logic that sets the language standard.

As an illustration of the ontology creation process, **Figure 1** below shows a design pattern for an ontology "Nuclear Training Center" type, which is used in the project [4]. This model was created on the basis of an analysis of the educational programs of the following Russian and international training centers: National Research Nuclear University MEPhI, Physics Department of Moscow State Univer-

*Semantic Web and Interactive Knowledge Graphs as an Educational Technology*

sity, IAEA. The ontology design pattern is represented in the UML notation according to the international standard [5]. The actual ontology in serialized form for the knowledge graph titled "Nuclear Physics at MSU and MEPhI" is available in Ref. [6]. Another approach to the development and refinement of the structure of

ontologies is based on Terminological Decision Trees (TDT) [7].

*Design pattern for an ontology "nuclear training center" type in UML notation.*

map formal ontologies to certain domains.

*DOI: http://dx.doi.org/10.5772/intechopen.92433*

**Figure 1.**

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To ensure the effective use of the nuclear knowledge database in educational activities, additional software agents have been created for reconnaissance contextsensitive search for adequate network content and its semantic annotation based on existing knowledge graphs (for example, with the aim of authoring training materials), as well as public endpoints for easy navigation on international knowledge databases DBpedia and Wikidata.

The potential beneficiaries of information solutions and technologies that are proposed in the chapter are students, professors, experts, engineers, managers, and specialists in the domain of nuclear physics and nuclear power engineering (target audience).
