=Paper=
{{Paper
|id=Vol-2433/paper14
|storemode=property
|title=TODOS as digital science-support environment to provide STEM-education
|pdfUrl=https://ceur-ws.org/Vol-2433/paper14.pdf
|volume=Vol-2433
|authors=Yevhenii B. Shapovalov,Viktor B. Shapovalov,Vladimir I. Zaselskiy
}}
==TODOS as digital science-support environment to provide STEM-education==
https://ceur-ws.org/Vol-2433/paper14.pdf
232
TODOS as digital science-support environment to
provide STEM-education
Yevhenii B. Shapovalov1[0000-0003-3732-9486], Viktor B. Shapovalov1[0000-0001-6315-649X]
and Vladimir I. Zaselskiy2
1 National Center “Junior Academy of Sciences of Ukraine”, 38/44, Dehtiarivska Str., Kyiv,
04119, Ukraine
sjb@man.gov.ua
2 Kryvyi Rih Metallurgical Institute of the National Metallurgical Academy of Ukraine,
5, Stepana Tilhy Str., Kryvyi Rih, 50006, Ukraine
zaselskiy52@mail.ru
Abstract. The amount of scientific information has been growing exponentially.
It became more complicated to process and systemize this amount of unstructured
data. The approach to systematization of scientific information based on the
ontological IT platform Transdisciplinary Ontological Dialogs of Object-
Oriented Systems (TODOS) has many benefits. It has been proposed to select
semantic characteristics of each work for their further introduction into the IT
platform TODOS. An ontological graph with a ranking function for previous
scientific research and for a system of selection of journals has been worked out.
These systems provide high performance of information management of
scientific information.
Keywords: TODOS, science environment, educational environment, ontology,
taxonomy, STEM-education.
1 Introduction
1.1 The problem of digital science
Nowadays, cooperation and all-world international integration are conducted.
Therefore, it leads us to the generation of a huge amount of not-structured information.
One of the humanity actions fields which is one of the leaders of information production
is science. The situation is being complicated due to the fact that providing science is
foresees knowing of the huge amount of already made scientific researches.
Therefore, in science nowadays is a lot of information generated and there is a
problem to process it. Considering this, educational approaches are adopting and one
the modern approaches which include principles of multidisciplinary and studying to
work with a huge amount of knowledge is STEM-education. The specifics of it is the
lack of digital instruments to provide it [2; 3; 20].
___________________
Copyright © 2019 for this paper by its authors. Use permitted under Creative Commons License
Attribution 4.0 International (CC BY 4.0).
233
1.2 Scientometric databases in post-soviet countries challenge
For post-soviet countries, this situation is even more important due to the fast speed of
integration of their science with worldwide which wasn’t provided previously.
Nowadays, in the example of Ukraine, the huge challenge is to provide publication
in both well-known scientometric databases (such as Scopus or Web of Sciences) and
journals recommended by Ministry of Education and Science of Ukraine (scientific
professional editions of Ukraine; further – SPE). This makes informational chaos in the
field of journal selection to publish the results of scientific work.
1.3 Information processing problem
As was noted before, a huge amount of scientific information is generated nowadays.
However, there is no effective was to process them. Sure, systems which can simplify
exists, such as Mendeley, but they still do not provide analysis and processing of the
information. For example, well-known designs can only provide commenting of the
scientific papers which isn’t provide any analysis and actually do not provide any
systemizing of the information to provide structuration. The interface of commenting
in Mendeley is shown in Figure 1.
Fig. 1. The interface of commenting in Mendeley
We propose using of Transdisciplinary Ontological Dialogues Object-Oriented
Systems (TODOS) [6; 9; 13; 25; 26] to provide systemizing and processing of Big Data
with taxonomy creation, filtering, and ranking of information. A key benefit of this
system is the context-based method of data processing and structuring based on
semantic relations. Previously, there was provided attempts to use ontology-based
approaches in education [1; 7; 8]. However, they were characterized by not attractive
for students and teachers’ interface and by low interactivity such as the absence of
multiagency approaches or wasn’t interactive at all. In the case of Ukraine, it is very
important to provide education in the national language and IT platform TODOS can
implement it.
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Therefore, this work aims justification of necessarily of digital science supporting
processing and creation of the base of it.
2 Literature review and problem statement
2.1 TODOS as ontology systemizing of information
Using the ontological approach to provide informational systemizing is an important
part of the learning process [4; 5]. Such an educational environment based on the
ontological approach involves filling adaptive educational services with information
resources that reflect the conceptual system of a particular discipline. The methodical
provision of the educational-cognitive process consists of the assimilation of the
conceptual system, axiomatics, rules, syntactic and morphological foundations of this
theory. The set of terms determines the conceptual basis of scientific theories by
determining a certain ordering of the concepts of the discipline. Thus, the ontological
multiagent in content reflects the conceptual system of a certain disciplinary theory. It
takes into account the individual characteristics of each subject of the educational
process.
Structures in TODOS are represented by three categories (O, A, R), where O and A
are a set of elements called objects and attributes, and R, respectively, is the binary
relation between O and A. In particular, if oRa for o O, A, then we assume that “the
object possesses the attribute A” or “the object has the attribute O” [7].
The feature of the ontological graph is the high level of structuring and data
visualization, the possibility of transition between related edges and search for semantic
links between vertices and its elements. The graph provides a transition to scientific
data carried out quickly and understandably. In addition, operationality of information
can be significantly improved by transforming it to taxonomy under using of
ontological approach [6; 22].
TODOS is an innovative complex of programmatic information and methodological
knowledge management tools using ontological management approaches to corporate
information resources, where people are considered as the source of the birth of new
knowledge for transferring them in the form of their own knowledge through the tool
TODOS, which is the only integrated point of access – “the single window” – to the
information and applications of the system to provide interactive interaction with users.
A key benefit of this system is the context-based method of data processing and
structuring based on semantic relations.
The architecture of the formation of transdisciplinary information environments IT-
platform based on the multiple procedures of transdisciplinary interaction with network
information resources is realized on the basis of semantic control and ontological
interface of TODOS [23; 26]. The technical basis of the TODOS is consisted of [25]:
─ SYSTEM CONSPECT provides the construction of terminological trees based on
the analysis of natural language text. It is a linguistic processor that provides the
initial formation of a linguistic case and allows to solve the following practical tasks:
improving the quality of processing of linguistic texts by increasing the vocabulary
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of the system; automatic definition of thematic directions of the document; sorting
of documents according to thematic directions.
─ SYSTEM CONFOR provides the creation of ontology subject areas, classification,
and generation of taxonomies in the form of ontological graphs. The system ensures
the creation of subject area ontology, classification, and generation of taxonomies in
the form of ontological graphs, which allows solving the following practical tasks:
construction of a semantic network of terms of the document; combining semantic
network of terms for several documents.
─ SYSTEM EDITOR ensures the formation of ontological models through the
creation, editing, review and analysis of networks of concepts based on the
construction of semantic links between objects of the subject area and the formation
of patterns, presented in the form of a set of values of attributes, which describes the
initial concepts of subject areas. The isolation of regularities is carried out by the
method of inductive formation of concepts based on the pyramidal network.
─ ALTERNATIVE SYSTEM ensures the organization of objects-concepts of
ontology, on the basis of integrated processing of properties that characterize them.
For this, we use weight, ball, and linguistic scales. Each such scale defines the values
of the criteria characterizing the properties of the objects of the thematic ontology of
the subject area. In general, the properties-criteria are characterized by different
degrees of importance, which when solving the problem of choice are given by some
real numbers – weight coefficients. Before solving the problem for each criterion, it
is necessary to form its value for each alternative. Thus, the formation of ontologies
of the tasks of choice is ensured.
─ LINGUISTIC CORPUS and built into its environment SEARCH MACHINE
provides marking and indexing of semantic units that define and describe the
contexts of objects of thematic ontologies of the subject areas. Contexts of semantic
units make up an electronic library with means of associative search of semantically
related information arrays, including determining the level of semantic equivalence
of texts.
Fig. 2. Information management system TODOS
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These modules are working together to transform unstructured incoming data to the
hierarchy of contexts. Information management system TODOS is shown in Figure 2.
2.2 Main features of the TODOS: taxonomy, filtering, ranging
Ontologies are based on taxonomy creation. The main feature of the TODOS platform
is a simplification of its creation. To create the ontology user do not need to know any
programming languages just MS Excel. The example of taxonomy created on TODOS
platform is presented in Figure 3.
Fig. 3. The example of a taxonomy provided by TODOS platform
Fig. 4. The example of an objective view of the ontology created in TODOS platform
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To provide visualizing of the taxonomy, it’s possible using the objective view. This
view presents each edge of the ontology as a personal object. The hierarchy is saved by
creating links between those objects. The example of a taxonomy provided by TODOS
platform is presented in Figure 4.
Analysis of information is provided through the identification and separation of
semantic information of each edge. As edge, we can use any object kind scientific
paper, single microorganism, the technology of water clearing, etc. It depends on the
expert-creator idea, but anyway, it provides separation of the semantic data of edges.
This can provide further data processing and systemize in way of filtering of ranking.
The proposed informational system is characterized by multiagent features and has all
the benefits of such a system.
3 Materials and methods
For creating digital educational programs and other educational content, the sheets were
loaded to the part of TODOS IT-platform editor4. After that, the generation of the graph
edges with its characteristics was carried out.
To store information and provide its sharing, Google sheets were used, with their
further conversion into the .xls and .csv MS Excel sheets (see in Figure 5).
Fig. 5. Google sheet with data
The obtained documents were used to create the ontology structure .xml and to fill the
ontology graphs with semantic and numeric information for ranking and filtering. Some
of the instruments of the web-oriented educational environment are using intellectual
features of TODOS, and to provide it, semantic characteristics were added.
238
The received documents were used to create an ontology structure (xls) and to fill
the ontology graphs of ranking and filtering. To provide it, they were downloaded in
editor4, the part of TODOS IT-platform. After that, the graph generation and the
inputting of semantic characteristics to each vertex were carried out. Ontological edges
were formed using predicate equations [25]:
1, ¬ ( )∧ ( ,..., )
( ,..., )= (1)
0, ( )
where ∈ ; 1 ≤ ≤ .
The relation between taxonomic categories has the properties of the hyperrelation
Gr type – YGrx, where Y is the set of all possible sets of concepts of X taxonomic
category T, x is one of the concepts of this set and Pr – predicate.
The obtained ontological graphs were opened in the appropriate form, ranking or
filtering. To provide filtering, the function of choice has been applied. The function of
choice in terms of taxonomic categories is as follows:
∀ ∅∉ ⇒∃ : →∪ , ∀ ∈ ( ( ) ∈ (2)
where F – is a function of the interpretation of a certain ontology; T – taxonomy.
4 TODOS as the digital science-support environment
All advantages of TODOS can be used to both systemize the science information and
to create useful databases (Big Data based) instruments for the scientist.
4.1 Using TODOS to create Big Data databases
SPE and SCOPUS ontology-based selection systems.
We created the online web-oriented ontological graph for both, SPE and SCOPUS
journals to provide selection. As graph edge, each journal was chosen. For both,
semantic characteristics were separated. For SPE journals they were “Founder”,
“Branch of science”, “Date of inclusion/renewal”, “Journal indexing”, “Journal
specialization ». User can use those characteristics to select a journal du to it needs.
SPE journal selection instrument is presented in Figure 6.
To create a database on SCOPUS journals “SJR”, “SNIP”, “CiteScore”, “Activity
status” (active or not), “All Science Classification Codes (ASJC)”, “Language in the
source (three-letter ISO language codes)” and “Publisher’s Country” were separated
from each journal and added to edges as semantic data. Scopus journal selection
instrument is presented in Figure 7.
Ontology-based catalog of the microorganisms.
Systematization of knowledge in the field of biotechnology may also be complicated
by the fact that semantic characteristics cannot always be quantified, and therefore the
ranking system cannot always solve the issue of information management. For such
239
systems, it was suggested to separate the semantic information and apply a filtering
function. The semantic characteristics of each microorganism were also proposed and
input into the Google Sheets. All semantic characteristics were added in the collective
access mode [19].
Fig. 6. SPE journal selection instrument
Fig. 7. Scopus journal selection instrument
The resulting ontological graph provides the possibility to use the filtering, and it is
possible to find the discovered microorganism or group of microorganisms. General
view of the ontological taxonomy of microorganisms is presented in Figure 8 and a
general view of the microorganisms selecting system is presented in Figure 9.
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Fig. 8. General view of the ontological taxonomy of microorganisms
Fig. 9. General view of the microorganisms selecting system
4.2 TODOS to systemize scientific information
To construct a system of ranking of previous studies, we have identified semantic
characteristics of the scientific research devoted to biogas production from chicken
manure. These semantic characteristics include “Temperature (° C)”, “Volume of
reactor (l)”, “Chicken manure content (%)”, “Moisture content (%)”, “Active sludge
content (%)”, “Final solids content (%)”, “Biogas production (ml/g VS)”, “Methane
production (ml/g VS)”, “methane content (%)”, “Year of the research”, “Ammonium
nitrogen content (mg/l)”, “Final pH”, “Initial pH”, “Minimal pH” and “Maximum pH”
241
[14; 17; 18; 27]. The characteristics were selected from the studies on dry fermentation
of chicken manure and were input to the google sheets.
The data were processed by the methods described in detail in our previous works
[3; 16]. As a result, it was possible to use ranging from previous research results. The
general view of the taxonomy is presented in Figure 10. The interface for selecting the
importance of indicators is presented in Figure 11, and the interface for ranking the
results is presented in Figure 12. The interface for selecting the priorities of numerical
information for ranking allows taking into account the priority of modern articles, with
the correct marking of important criteria. The considered system allows a quick search
of the information by the necessary criterion [19].
Fig. 10. The general view of the taxonomy
4.3 Transdisciplinary using scientific results in education and science.
Single science digital environment to provide STEM-education
As it was proposed previously, the ontology-based system can be used to provide
integration and transdisciplinary using internal sources [20; 15]. Databases created by
a group of scientists who provides research will be able to share it to the open-source
general database. That knowledge can be used by a huge amount of people not just
scientist. As it was proposed previously, the ontology-based system can be used to
provide integration and transdisciplinarity using internal sources. It means, that
multidisciplinary ontology-based educational environment can’t be used as the main
instrument which provides scientific method of education and can integrate other
instruments of STEM-education such as augmented reality or mobile phones involving
[10; 11; 12; 15; 20; 24]. The proposed system will be very useful for students and young
scientists who just start their research work.
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Fig. 11. The interface for selecting the importance of indicators
Fig. 12. The interface for ranking the results
5 Conclusions
1. A huge amount of scientific information can be systemized by using TODOS IT-
platform.
2. TODOS IT-platform can provide a high level of informational structuring and
information processing through the creation of the hierarchy and using TODOS
instruments such as ranking and filtering.
3. TODOS can be used to both systemize the science information and to create useful
databases (Big Data based) instruments for the scientist.
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4. We developed the method of systemizing scientific information which is
characterized by a higher level of informational processing.
5. TODOS integrate the scientific processed data in a single scientific informational
field which involves scientists and students to provide transdisciplinary researches.
6. The proposed system can be used not just for a huge amount of people not just
scientist and provides integration of internal and external sources to provide research
approach in STEM-education.
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