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
1
Ternopil Volodymyr Hnatiuk National Pedagogical University, 2 Maksyma Kryvonosa Str., Ternopil, 46027, Ukraine
2
Kyiv International University, 49 Lvivska str., Kyiv, 03179, Ukraine
3
I. Horbachevsky Ternopil National Medical University, 1 Voli Sq., Ternopil, 46001, Ukraine
4
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
a
https://orcid.org/0000-0002-0202-348X
b
https://orcid.org/0000-0003-4218-0671
c
https://orcid.org/0000-0001-5899-0244
d
https://orcid.org/0000-0003-3335-0501
e
https://orcid.org/0000-0003-4200-4440
f
https://orcid.org/0000-0003-3850-6587
g
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
Copyright
c
2022 by SCITEPRESS Science and Technology Publications, Lda. All rights reserved
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 n1 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
´
eg
´
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
´
eg
´
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
´
eg
´
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
´
eg
´
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
´
eg
´
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.
AET 2020 - Symposium on Advances in Educational Technology
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
´
eg
´
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
´
eg
´
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
´
eg
´
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
´
eg
´
e)
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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