Vol.:(0123456789) SN Computer Science (2020) 1:335 https://doi.org/10.1007/s42979-020-00338-1 SN Computer Science ORIGINAL RESEARCH An SQL Domain Ontology Learning for Analyzing Hierarchies of Structures in Pre‑Learning Assessment Agents Kennedy E. Ehimwenma 1,2  · Paul Crowther 3  · Martin Beer 3  · Safya Al‑Sharji 4 Received: 27 March 2020 / Accepted: 17 September 2020 © Springer Nature Singapore Pte Ltd 2020 Abstract This paper presents the use of description logics (DL) in the defnition and development of a Structured Query Language (SQL) domain ontology for a multi-agent based pre-assessment system. Description logics is a knowledge representation language for defning terms or classes, the relationships between classes, their instances, including individuals and literals. In a formal school curriculum, modules of learning are inter-dependent. So, teaching and learning follows an ordered sequence of learning from lower-level module(s) to higher-level ones. This process enables students to gain mastery of lower-level materials before moving up the ladder to higher-level learning. To describe an SQL ontology and its representation for a multi-agent based system application, this paper uses a description logic language to present the organization of learning modules into DesiredConcept < D >, PrerequisiteConcept < C > and LeafNodes < N > as well as their associated relation- ships, namely, hasPrerequisite and hasKB between the learning modules. The paper thus presents a TBox and an Abox of a DL ontology and further transformation into a frst-order predicate for a multi-agent based system that was implemented in Jason. Keywords Knowledge representation · Description logics · First-order logic · SQL ontology · OWL · Multi-agents · Teaching and learning · Semantic web Introduction In teaching and learning, activities are arranged in an ordered sequence from known-to-unknown. Also, in a knowledge domain, concepts do not exist in isolation. Like nodes in a semantic net, unit of lessons are linked to one another with common knowledge boundaries or properties that exists in-between them. On one hand, one learning unit can be established to have a relationship with an immediate higher-level unit; and on the other hand, could have a rela- tionship with an immediate lower-level unit. This is because the successful learning of a concept and a unit of lesson is dependent on some prerequisites knowledge. Like vertices in a graph network, units of lessons can be viewed as a con- nection of nodes representing learning structures. As stated in [17] vertices represent objects, such as; people, houses, cities, courses, concepts, etc.; that are modelled as nodes in a knowledge graph. Ontologies are models of information in a domain of interest. To build ontologies, a description logic (DL) language is required for the formal specifcation of the chosen terms, class names, class instances or individuals, literals and the relationships that exists in-between them in the ontology. A DL as a representational language for defin- ing ontologies from scratch is hereby used for: i) the analysis of the DL defned SQL ontology, ii) organiza- tion of learning modules as instances of the chosen * Kennedy E. Ehimwenma kehimwen@kean.edu Paul Crowther crowtherpaultas@gmail.com Martin Beer mdb.shu@gmail.com Safya Al-Sharji safya.alsharji@hct.edu.om 1 Department of Computer Science, Wenzhou-Kean University, Wenzhou, China 2 Department of Computer Science, International College, Hunan University of Arts and Science, Hunan, China 3 Department of Computing, Shefeld Hallam University, Shefeld, UK 4 Department of Information Technology, University of Technology and Applied Sciences, Muscat, Oman