Ontological Approach to the Presentation of the Subject Area of the

Discipline

Ivan M. Tsidylo

1 a

, Serhii V. Kozibroda

1 b

, Oleksii V. Sysoiev

2 c

, Tetiana I. Gargula

3 d

Anatolii A. Hryhoruk

1 e

, Lyubov M. Lytvyn

1 f

and Andrei V. Voznyak

4 g

Ternopil Volodymyr Hnatiuk National Pedagogical University, 2 Maksyma Kryvonosa Str., Ternopil, 46027, Ukraine

Kyiv International University, 49 Lvivska str., Kyiv, 03179, Ukraine

I. Horbachevsky Ternopil National Medical University, 1 Voli Sq., Ternopil, 46001, Ukraine

Kryvyi Rih State Pedagogical University, 54 Gagarin Ave., Kryvyi Rih, 50086, Ukraine

Keywords:

Ontological Approach, Computer Ontology, Knowledge Representation, Computer Ontology Design Algo-

rithm, Educational Discipline, Subject Field.

Abstract:

The article considers the problem of methodology of designing computer ontology of the subject area of the

discipline by future specialists in the ﬁeld of digital technologies. The scheme of ontology of the subject

discipline is presented in which the set of concepts of the future computer ontology and the set of relations

between them are represented. The main criteria of the choice of systems of computer ontologies for design-

ing computer ontology of the subject discipline: software architecture and tools development; interoperability;

intuitive interface are established. The selection of ontology design methods by means of computer ontology

systems has been speciﬁed. An algorithm for designing a computer ontology of the subject area of the disci-

pline by future specialists in the ﬁeld of digital technologies is proposed. The effectiveness of the proposed

scheme of ontology of the subject area of the discipline and the proposed method of technology has been

investigated experimentally on three indicators: 1) the speed of construction of ontologies; 2) the number of

defects; 3) the speed of addition of already created ontologies.

1 INTRODUCTION

One of the important trends in the development of

modern computer systems is ontologically managed

information systems. The construction of the latter

is closely connected with the development of theo-

retical foundations and design methodologies includ-

ing a formalized approach, fundamental principles

and mechanisms, generalized architecture and struc-

ture of the system, a formal model and methodology

for designing ontology of the subject ﬁeld (including

ontologies of educational disciplines), formal model

of presentation of knowledge, generalized algorithms

https://orcid.org/0000-0002-0202-348X

https://orcid.org/0000-0003-4218-0671

https://orcid.org/0000-0001-5899-0244

https://orcid.org/0000-0003-3335-0501

https://orcid.org/0000-0003-4200-4440

https://orcid.org/0000-0003-3850-6587

https://orcid.org/0000-0003-4683-1136

of procedures for knowledge processing, etc. Ac-

cordingly, each of the listed components of the gen-

eral design methodology is a complex information-

algorithmic structure and falls within the scope of

future specialists in the ﬁeld of digital technologies.

Comprehensive solution of these tasks of design will

provide an opportunity to enhance the role of ontolog-

ical (conceptual) knowledge in solving concrete prob-

lems in applied branches in general and in the educa-

tional process in particular (Dovhyi et al., 2013, p. 9).

Ontologies are a promising technology for the de-

velopment of modern educational systems. Repre-

senting the basic concepts of the subject area in a for-

mat available for automated processing in the form of

a hierarchy of classes and relationships between them,

ontologies allow for automated processing of the se-

mantics of information units.

Depending on the approach used in modeling sub-

ject knowledge (thematic, functional, procedural, op-

erational or semantic), there are different methods of

Tsidylo, I., Kozibroda, S., Sysoiev, O., Gargula, T., Hryhoruk, A., Lytvyn, L. and Voznyak, A.

Ontological Approach to the Presentation of the Subject Area of the Discipline.

DOI: 10.5220/0010925900003364

In Proceedings of the 1st Symposium on Advances in Educational Technology (AET 2020) - Volume 1, pages 527-537

ISBN: 978-989-758-558-6

527

structuring information concepts of the subject area

(Gruber, 1995, p. 911): semantic networks, lattice

theory, operations on graphs, genetic algorithms, neu-

ral networks, ontologies and other mathematical mod-

els.

However, the process of designing computer on-

tologies is complex and lengthy and requires knowl-

edge of many declarative languages, and in order to

facilitate it, there is a need for the use of certain sys-

tems created to design computer ontologies that pro-

vide such interfaces that allow them to conceptual-

ize, implement, verify inconsistency and documenta-

tion. In recent years the number of tools for work-

ing with computer ontologies has increased dramat-

ically (more than 50 editing tools). However, most

of these tools are intended to use existing ontologies

by the help of formal languages, such as: Common

logic; Cyc; Gellish; IDEF5; KIF; Rule Interchange

Format (RIF) and F-Logic; OWL; XBRL (Ovdei and

Proskudina, 2004). Therefore, in the process of train-

ing future professionals in the ﬁeld of digital technol-

ogy, there is a need to use these systems for design-

ing computer ontologies that could provide interfaces

that would allow operations to be carried out in con-

nection with the formal representation of sets of con-

cepts and relationships between them. Computer sys-

tem ontology (CSO) are a certain answer to this need,

especially in the context of designing a computer on-

tology of the subject area of the discipline by future

specialists in the ﬁeld of digital technologies.

The process of developing and using ontology in

general form is considered by Noy and McGuinness

(Noy and McGuinness, 2001), Nirenburg and Raskin

(Nirenburg and Raskin, 2004). Problems of ontolo-

gies and their use in computer systems were consid-

ered by Lapshyn (Lapshyn, 2010). The discovery

of the meaning of the concept of “ontology”, given

to it in the computer sciences, the works of Gruber

(Gruber, 1991, 2008, 2007, 2006, 2003, 1993; Gruber

et al., 1996) and others are devoted to it. Some aspects

of the use of computer ontologies, in the context of in-

tellectual technologies, are discussed in (Spirin, 2004;

Lytvyn et al., 2013; Tsidylo, 2014). An overview of

the instruments of ontology engineering was done by

Ovdei and Proskudina (Ovdei and Proskudina, 2004).

Methods for creating an interface based on ontology

in the environment of the web portal were studied by

Popova and Stryzhak (Popova and Stryzhak, 2013),

Stryzhak (Stryzhak, 2016). The modeling of the on-

tology of the educational subject ﬁeld as a means

of integrating knowledge was studied by Yevseeva

(Yevseeva, 2009), Liubchenko (Liubchenko, 2008),

Stryzhak et al. (Stryzhak et al., 2014) and oth-

ers. Modeling the categorical level of the language-

ontological picture of the world was done by Palahin

and Petrenko (Palahin and Petrenko, 2006). Ontolog-

ical representation of decision-making processes was

done by Chaplinskyi (Chaplinskyi, 2009). Using the

ontology of the subject area to eliminate ambiguities

in the computer translation of technical texts was pro-

posed by Morentsova (Morentsova, 2018). The works

of the above-mentioned authors contributed to the ac-

cumulation and systematization of knowledge for im-

proving the practical training of students on the cre-

ation and use of computer ontology. However, they

do not sufﬁciently disclose the peculiarities of train-

ing to create an ontology of a particular subject area

in the training of future professionals in the ﬁeld of

digital technologies, taking into account their profes-

sional engineering and professional pedagogical ac-

tivities.

The purpose of the article is to substantiate the

ontological approach of presenting the subject area of

the discipline as a means and result of systematiza-

tion of knowledge of future specialists in the ﬁeld of

digital technologies.

2 RESULTS

In the process of training specialists in the ﬁeld of dig-

ital technologies at higher educational institutions, the

study of intelligent systems, in which ontologies are

used for the formal speciﬁcation of concepts and con-

nections inherent in a certain ﬁeld of knowledge, oc-

cupies a signiﬁcant place. Since the computer cannot

understand how a person does, the state of things in

the world, it must be submitted with all the informa-

tion in a formal way. Consequently, ontologies serve

as a kind of model of the surrounding world, and their

structure is such that it is easily subjected to machin-

ing and analysis. Ontologies provide the system with

information about well-described semantics of given

words and indicate the hierarchical structure of the

medium and the relationship of the elements. All of

this allows computer programs to draw conclusions

from available information and manipulate those us-

ing ontologies.

Hence, it is Gruber (Gruber, 1991) who authored

the concept of “ontology” in engineering. The task of

constructing a description of knowledge is very spe-

ciﬁc. Therefore, Gruber (Gruber, 1991) has identi-

ﬁed a speciﬁc term for this task – the “speciﬁcation

of conceptualization”. Under “conceptualization,” he

understood “an abstract, simpliﬁed view of the world,

which is used by people to realize a certain goal”

(Gruber, 1991, p. 602). The peculiarity of the task

of conceptualization lies in the fact that for the ex-

AET 2020 - Symposium on Advances in Educational Technology

528

change of knowledge between software systems (in

the context of the concept of artiﬁcial intelligence), it

is necessary to openly specify their conceptualization,

that is to build a description of this knowledge, more-

over, sufﬁciently formal, that it was “understood” by

other systems.

In the process of developing intelligent systems,

the most time-consuming are the stages of conceptu-

alization and formalization, which are considered in

work (Buyak et al., 2018) in the process of designing

a structural model of a neuro-fuzzy expert decision-

making system for determining the professional se-

lection of students for the training of IT specialties.

More speciﬁcally, the concept of ontology is de-

ﬁned by Faure et al. (Faure et al., 1998), who assumes

that ontology is an explicit speciﬁcation of a particu-

lar topic.

Therefore, the ontological approach allows a for-

mal and declarative presentation of a topic covering

a dictionary (or list of constants) to refer to the terms

of a particular subject area, limiting the integrity of

these terms or logical statements that limit the inter-

pretation of terms and how they are combined with

each other.

Thus, ontology deﬁnes a general terminology for

scholars who need to share information in a particular

subject area. It covers suitable for interpretation by

means of a computer deﬁnition of the main concepts

of the subject ﬁeld and the interconnection between

them. With the increasing popularity of usage of com-

puter ontologies, their study should be included in the

curricula of the higher educational institutions, since

they can generate test tasks, create didactic materials

from different disciplines and branches of knowledge,

etc.

However, as mentioned above, the process of de-

signing computer ontologies is complex and time-

consuming and requires knowledge of many declar-

ative languages, so in the activities of future profes-

sionals in the ﬁeld of digital technologies it is more

appropriate to use CSO that are a computer program

or software package that intended for the construc-

tion of computer ontology from a certain subject ﬁeld

and perform operations related to the formal repre-

sentation of sets of concepts and relationships be-

tween them, in addition, computer ontologies can be

exported to a variety of formats, including invoking

RDF (RDF Schema), OWL and XML Schema, etc.

Regarding the choice of a speciﬁc CSO, it should

be implemented according to some of the following

criteria: 1) software architecture and development of

tools containing information about the necessary plat-

forms for using the tool; 2) functional compatibility,

which includes information on tools and interaction

with other languages and tools for the development

of ontologies, translation from some languages on-

tologies; 3) the intuition of the interface, covering the

work with graphic editors, the co-operation of several

users and the need to provide multiple use of ontology

libraries (Kozibroda, 2016, p. 179).

However, to build a computer ontology of the sub-

ject area of the discipline, future professionals in the

ﬁeld of digital technology must also reﬂect the con-

tent of the subject area of the discipline, which is de-

scribed as a list of modules implemented in various

forms of classes in a particular discipline. At the same

time, relevant competencies for each module are indi-

cated besides the content, form and control, and their

extent. Based on the analysis of the subjects and ob-

jects of the learning process, the processes of creat-

ing and managing the educational material, one can

identify the following problems that arise during the

development of the training course:

• high complexity of the process of ﬁnding new

teaching materials;

• the need to assess the conformity of educational

resources with the requirements of the content of

the training course;

• providing educational resources with the full cov-

erage of the modules of the discipline in general

and the course in particular;

• excessive coverage of the modules of the disci-

pline and implementation of the choice of the

most optimal educational resource for a particu-

lar situation;

• the need to assess the quality of educational re-

sources.

Thus, in the process of developing content mod-

ules of the discipline it is important to identify certain

requirements for the model of presentation of knowl-

edge and data on the basis of a systematic analysis of

the speciﬁcs of the subject area, proposed by (Anikin,

2014, p. 62).

To implement a model of presentation of knowl-

edge and data that meet the requirements considered,

it is expedient to use an ontological model of pre-

sentation of knowledge, which combines the proper-

ties and advantages of other models of presentation of

knowledge and data (graph model, tree-based model,

relational model, semantic network, framing, logical

model, etc.).

Solving the tasks of the search and integration of

educational material in the personalized educational

collection can be realized in the ontological model be-

cause of the development and inclusion of the corre-

sponding semantic rules in computer ontology.

Ontological Approach to the Presentation of the Subject Area of the Discipline

529

The formal model of ontology can be represented

as:

O = <C, R, F>,

where C – the ﬁnal set of concepts of the subject ﬁeld,

which determines the ontology of O; R – the ﬁnal set

of relations between them; F is the ﬁnal set of func-

tions of interpretation given on the concepts and/or

ontology relations of O.

The restrictions imposed on the set C are not in-

ﬁnity and are not empty (C 6= Ø). The sets R and F

can be empty, which corresponds to certain types of

ontology, when it degenerates into a simple dictionary

(R = Ø, F = Ø), taxonomy of concepts (F = Ø), etc.

One of the possible ontological bases for the de-

scription of computer ontologies in the context of the

use of computer ontology systems by future special-

ists in the ﬁeld of digital technologies, presented in

(Pikuliak, 2014, p. 197), are: lasses united in taxon-

omy; relationship (type of links between concepts of

the subject industry); functions (a special kind of re-

lationship in which the n-th element of the relation-

ship is determined by the values of n−1 of the pre-

ceding elements); axioms (simulate offers that are al-

ways true); specimens (entities) that make up speciﬁc

objects of the real or abstract world.

OWL-DL combines OWL expressiveness and

completeness of computations (all logical conclusions

performed on an ontology basis will be thoroughly

calculated) and extensibility (all calculations are com-

pleted at a certain time). The OWL-DL contains all

OWL language constructs that are subject to certain

restrictions (for example, a class may be a subclass

of many classes, but cannot be a representative of an-

other class).

Accordingly, the ontological model of the subject

discipline of the discipline ODD (ﬁgure 1) will be de-

ﬁned as:

ODD = <CDD, InstDD, RDD, IDD>,

where CDD is the ﬁnal set of concepts for

the ontology of the core curriculum knowledge

(CDD = {cDD1, cDD2, cDD3, cDD4, cDD5, cDD6,

cDD7, cDD8, cDD9, cDD10, cDD11, cDD12};

cDD1 – the DataDomain class for the deﬁnition of

the subject discipline; cDD2 – is the Competence

class for identifying competences in a learning dis-

cipline; cDD3 is a Concept class for deﬁning the

concepts (terms) of a discipline subject ﬁeld that is

a subclass of cDD2; cDD4 is a UCompetence class

for identifying universal competencies; cDD5 is a

class of PCompetence for deﬁning professional com-

petencies; cDD6 – ZNKCompetence class for general

knowledge competencies; cDD7 – ICompetence class

tool for determining competence; cDD8 – SOKCom-

petence class for the deﬁnition of social / personal /

general cultural competencies; cDD9 – is the Skill

class for determining the skills obtained in the subject

discipline, which is a subclass of cDD2; cDD10 is

the Ability class for determining the skills obtained in

the subject ﬁeld of the discipline, which is a subclass

of cDD2; cDD11 is a Language class that deﬁnes the

language of presentation of information in the disci-

pline subject ﬁeld; cDD12 – Complexity class to de-

termine the level of development of competencies of

the discipline);

InstDD – is the set of competencies, concepts of

the subject discipline, as well as the skills represented

in the natural language of instances of classes CDD;

InstDD = {iDD1, iDD2, ... iDDm, ... iDDn};

RDD – the ﬁnal set of relations of the ontology of

the knowledge base of the discipline; (RDD = {rDD1,

rDD2, rDD3, rDD4, rDD5, rDD6, rDD7, rDD8,

rDD9}; rDD1 – hasLanguage ratio, rDD2 – has-

Complexity ratio, rDD3 – includes ratio, rDD4 –

hasHierarchicalRelation ratio, rDD5 – dependsOn ra-

tio, rDD6 – isSynonym ratio, rDD7 is the ratio is,

rDD8 – hasTitle, the ratio rDD9 – hasCompetence);

IDD is the set of interpretation rules, IDD = Ø.

The set of concepts for the CDD ontology of the

knowledge base of the discipline is presented in table

1, and the set of RDD relationships is in table 2. The

deﬁning areas and the domains of relationship values

can be both deﬁned concepts and their daughter con-

cepts within the framework of the ontology. Based on

the plurality of these concepts and the relationship be-

tween them using the CSO, future teachers-engineers

will be able to conduct ontological design of the sub-

ject ﬁeld of the discipline they need.

However, the question of how to design a com-

puter ontology remains open. Currently, there are

several methods of constructing ontologies and they

are all based on the principles proposed in (Gruber,

1995, p. 918): 1) Clarity. The ontology must effec-

tively convey the meaning of terms; 2) Compatibility.

The ontology must be compatible, i.e. the conclusions

that can be drawn from the deﬁnitions of concepts and

the relationships between them must be compatible

with the original terms; 3) Extendibility. The ontol-

ogy should be constructed so that it can be used effort-

lessly in separate ontology libraries; 4) Minimal en-

coding bias. The designed conceptual scheme should

not depend on the speciﬁc language used to write the

formalized description; 5) Minimal ontological com-

mitment. The ontology should contain as few facts as

possible about the ontology of the world being mod-

eled, while giving the freedom to use this ontology in

other worlds.

However, in the context of designing a computer

ontology of the subject area of the discipline on

AET 2020 - Symposium on Advances in Educational Technology

530

Figure 1: Scheme of ontology of the subject ﬁeld of discipline.

the basis of the selected cloud-oriented environment

WebProt

e, it is most appropriate to use the method

of building an ontology proposed by Lytvyn et al.

(Lytvyn et al., 2013), which consists of seven steps

(Lytvyn et al., 2013, p. 319).

Step 1. Deﬁning the ﬁeld and scale of the ontology.

Step 2. Ability to use existing ontologies.

Step 3. List of important terms in the ontology.

Step 4. Deﬁning classes and their hierarchy.

Step 5. Deﬁning the properties of classes.

Step 6. Deﬁning the facet properties.

Step 7. Creation of instances.

Therefore, to design a computer ontology of the

subject area of the discipline, future specialists in the

ﬁeld of digital technologies in the ﬁeld of computer

technology should be carried out according to the fol-

lowing algorithm:

1. Select on the basis of the scheme proposed in ﬁg-

ure 1, competencies of the ﬁrst level – universal

(general, instrumental, social-personal competen-

cies of subject discipline) and professional – on

the basis of analysis of the work program of disci-

pline and matrix of competencies. Describe them

as instances of the corresponding classes of com-

puter ontology of the study discipline (UCompe-

tence, PCompetence, ZNKCompetence, ICompe-

tence, SOKCompetence). An example of ﬁlling

the PCompetence class is shown in ﬁgure 2.

2. Sequentially allocate competences of the second

level by analyzing the list of acquired knowledge,

skills and abilities. Describe them as instances of

the corresponding classes of computer ontology

of the discipline (Concept, Skill, Ability).

3. Based on the analysis of the work program of the

discipline and the matrix of competencies, allo-

cate the third level competencies that are imple-

mented within each module of the curriculum and

describe them as instances of the corresponding

classrooms of the computer ontology (Concept,

Skill, Ability).

Ontological Approach to the Presentation of the Subject Area of the Discipline

531

Table 1: The set of concepts of ontology of the subject discipline.

Ontology concept Parental concept Concept description

DataDomain Thing Subject ﬁeld of discipline

Competence Thing Competences

Concept Competence Concepts (terms) of the subject discipline

UCompetence Competence Universal competences of the subject discipline

PCompetence Competence Professional competence of the subject ﬁeld of the discipline

ZNKCompetence UCompetence General scientiﬁc competence of the subject ﬁeld of the dis-

cipline

ICompetence UCompetence Instrumental competences of the subject discipline

SOKCompetence UCompetence Sociopersonal / general cultural competences of the subject

discipline

Skill Competence Skills in the subject ﬁeld of the discipline

Ability Competence Ability of the subject ﬁeld of the discipline

Language Thing Language of presentation of information

Table 2: The set of relations of the ontology of the subject discipline.

Correlation Deﬁnition area Value range Description

hasLanguage Competence Language The ratio that sets the language of the presentation

of the ontology

hasComplexity Competence Complexity The ratio that sets the level of competence devel-

opment

includes Competence Competence The relation of inclusion of competences in the

competence of a higher level, concepts, skills and

abilities – in competence (through the mechanism

of imitation)

dependsOn Competence Competence Relationship between the two competencies, con-

cepts, skills or abilities

isSynonym Competence Competence The relation of synonymy to the concepts of the

subject ﬁeld and competencies

is Concept Concept The relationship “is” between the concepts of the

subject ﬁeld

hasHierarchical Concept Concept The ratio of the hierarchy between the concepts

4. Based on the knowledge of the future specialist in

the ﬁeld of digital technologies about the subject

area of the discipline and the availability of ed-

ucational and methodological literature, identify

competencies of lower levels and describe them as

instances of relevant classes of computer ontology

of the discipline (Concept, Skill, Ability). The

recommended number of levels of competence in

describing the set of knowledge discipline – 3-4.

Additional levels can be used in the description of

knowledge in the form of concepts of the subject

area in the case of availability in the individual

modules of discipline a large number of terms of

the subject ﬁeld, which are related hierarchically.

For the description of skills and abilities, in most

cases it is up to 3-4 levels of competencies.

5. Based on the work program of the discipline and

the links proposed in table 2, as well as knowledge

of the subject area and the analysis of educational

methodical literature, identify the relationship be-

tween the competencies described and set them

with the following relationships of the ontology of

the discipline: includes (the ratio of the inclusion

of competencies in a higher level of competence),

dependsOn (dependency ratio between two com-

petencies, concepts, skills or abilities). If there is

synonymy, set the appropriate relation to isSyn-

onym. In describing the discipline subject ﬁeld,

use the hasTitle and hasLanguage relationship to

describe the description of the respective compe-

tences in the natural language and language of the

description ﬁgure 3.

Thus, we will have a computer ontology of the

subject area of the academic discipline as shown

in ﬁgure 4. However, to conduct an analysis to

obtain numerical estimates of the feasibility of de-

signing such ontologies of academic disciplines, it

is advisable to conduct an experiment and analyze

AET 2020 - Symposium on Advances in Educational Technology

532

Figure 2: Example of ﬁlling the PCompetence class with appropriate instances.

Figure 3: Example of setting the hasInputCompetence relationship between the corresponding instances and classes.

the effectiveness of cloud-based WebProt

e environ-

ment and ontologies based on the criteria proposed in

(Buyak et al., 2019): 1) speed of construction of sub-

ontologies, 2) the number of defects. Another impor-

tant criterion here is the speed of addition of already

created ontologies.

Therefore, an experiment was conducted on the

basis of the engineering and pedagogical faculty of

Ternopil Volodymyr Hnatiuk National Pedagogical

University, which involved 40 students of future spe-

cialists in the ﬁeld of digital technologies (20 stu-

dents in the experimental group and 20 students in

the control group). For the experimental group, the

process of designing a computer ontology of the sub-

ject area of the discipline was carried out on the basis

of the proposed ontological model and methodology

based on the use of cloud-oriented WebProt

e envi-

ronment. The students in the control group carried out

the design of a computer ontology of the subject area

of the discipline without the use of a model and with

the help of declarative programming languages.

The construction of the computer ontology of the

subject area of the discipline in both control and ex-

perimental groups was modular, i.e. developed as

a set of small modules (sub-ontologies), which are

then assembled for the formation and use as a sin-

gle modular ontology. Like ontology learning (ontol-

ogy extraction, ontology generation, or ontology ac-

quisition), it is the automatic or semi-automatic cre-

ation of ontologies, including the extraction of con-

cepts from the corresponding domain and the relation-

ship between these concepts from a natural language

text block and their coding with ontological language

for easy retrieval. Therefore, each student (both in

the experimental and control groups) built 1 ontology

of the subject area of the discipline. However, these

ontologies can later be combined as sub-ontologies

into one computer ontology of educational resources

of the university.

In the process of building ontologies of the subject

area of the discipline, students use general concepts,

which are sufﬁciently deﬁned in one of the ontolo-

gies, and they will be available for other ontologies,

which will avoid excessive description of objects of

the subject area by reusing certain concepts. It will

also make it possible to simplify the semantic rules

for ﬁnding didactic materials in a particular discipline

(Tsidylo and Kozibroda, 2018, p. 259).

Ontological Approach to the Presentation of the Subject Area of the Discipline

533

Figure 4: Graphical representation of the computer ontology of the discipline and the relationships between components and

classes.

As mentioned above, the process of analysis of

the design of computer ontologies of the subject area

of the discipline by students of the experimental and

control groups was carried out according to the fol-

lowing criteria:

1) speed of construction of ontologies. The students

of the control group (20 students) and the experi-

mental group (20 students) were allotted with 20

disciplines with appropriate structural elements

that should be reﬂected in the ontology, on the

basis of which students should build ontologies

of the subject area of the discipline. How long

it took the students of the groups to build these

20 ontologies was also taken into account. The

results show (ﬁgure 5) that the students of the ex-

perimental groups coped with this task on average

2.5 times faster;

2) the number of defects. The study of this indica-

tor was based on the analysis of 20 constructed

ontologies of the subject area of academic disci-

plines. According to the results of the analysis

(ﬁgure 6) it was found that future students of the

experimental groups, who used the proposed on-

tological model of the subject area of the disci-

pline and methodology based on the use of cloud-

based environment WebProt

e, had signiﬁcantly

fewer defects (almost 2 times) than the students

of the control groups, who designed the computer

ontology of the subject area of the discipline with-

out the use of the model and with the help of

declarative programming languages;

3) the speed of addition of already created ontolo-

gies the number of defects. This indicator re-

ﬂects how quickly future specialists in the ﬁeld

of digital technologies will be able to integrate

their ontologies of the subject area of the disci-

pline into the supra-ontology of the educational

resources of the university. According to the

results of the analysis of these indicators (ﬁg-

ure 7), the students of the experimental group who

used the cloud-oriented WebProt

e environment

to integrate their ontologies coped with this task

much faster (almost 3 times) than the students of

the control groups who did the integration using

declarative languages.

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534

Figure 5: Comparison of the speed of construction of on-

tologies by the students of the control and experimental

groups.

Figure 6: Comparison of the number of defects in ontolo-

gies built by the students of the control and experimental

groups.

Figure 7: Comparison of the speed of completion of com-

puter ontology by the students of the control and experi-

mental groups.

Thus, in the context of the ontological approach,

for the construction of computer ontologies the

scheme of ontology of the subject area of the dis-

cipline and the use of cloud-oriented environment

WebProt

e improves the quality characteristics of

designed ontologies such as speed of ontologies,

number of defects and speed of addition of already

created ontologies.

3 CONCLUSIONS

1. The scheme of ontology of the subject area of the

discipline is presented, on the basis of which fu-

ture specialists in the ﬁeld of digital technologies

will be able to describe many concepts of the fu-

ture computer ontology of the subject area of the

discipline. In addition, a set of relations between

them and the corresponding domains of deﬁni-

tion and domains of values of relations is pre-

sented, in which there can be both the speciﬁed

concepts, and their child concepts within the on-

tology. Based on the set of these concepts and

the relationship between them using the cloud-

oriented WebProt

e environment, future experts

in the ﬁeld of digital technology will be able to

conduct ontological design of the subject area of

the discipline they need.

2. The main criteria for choosing a CSO are: 1) soft-

ware architecture and tools development contain

information on the required platforms for using

the tool; 2) functional compatibility contains in-

formation on tools and interaction with other lan-

guages and tools for the development of ontolo-

gies, translation from some languages ontologies;

3) intuitive interface – covers work with graphic

editors, collaborative work of several users and

the need to provide multiple uses of ontology li-

braries.

3. In the process of selecting a method of designing

computer ontologies by means of computer on-

tology systems, the best option in the educational

process of the future specialist in the ﬁeld of digi-

tal technologies is the method proposed by Lytvyn

et al. (Lytvyn et al., 2013), which provides a num-

ber of stages of designing a computer ontologies.

4. The methodology of designing the computer on-

tology of the subject area of the discipline by fu-

ture specialists in the ﬁeld of digital technologies

is proposed. Which includes the scheme of the on-

tology of the subject area of the discipline, selec-

tion of a computer ontology systems(a web-based

environment WebProt

e) with the help of which

the design, the method of computer ontology de-

sign and the algorithm for designing a computer

ontology of the subject area of the discipline by

future specialists in the ﬁeld of digital technolo-

gies will be carried out.

5. The effectiveness of the projected ontologies of

the subject area of the discipline in the context of

training future professionals in the ﬁeld of digi-

tal technologies has been experimentally tested on

such indicators as: 1) the speed of construction

Ontological Approach to the Presentation of the Subject Area of the Discipline

535

of ontologies; 2) the number of defects; 3) the

speed of addition of already created ontologies.

Based on the analysis of the results, it should be

noted that by all criteria the indicators of students

of the experimental group, where the process of

designing computer ontology of the subject area

of the discipline is carried out on the basis of the

proposed scheme of ontology and methodology

based on the use of computer ontology system (in

our case, web-oriented environment WebProt

were higher than the indicators of the students of

the control groups who carried out design using

declarative programming languages.

6. The continuation of scientiﬁc research on the

given problem is useful in the study of the de-

pendence of constructed hierarchy concepts in the

computer ontology of the subject discipline and

the development of ontologically managed infor-

mation systems on their basis.

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