Providing complex digital support for scientific research is an urgent problem that requires the creation of useful tools. Cognitive IT-platform Polyhedron has used to collect both existing informational ontologybased tools, and specially designed to complement a full-stack of instruments for digital support for scientific research. Ontological tools have generated using the Polyhedron converter using data from Google sheets. Tools “Search systems”, “Hypothesis test system”, “Centre for collective use”, “The selection of methods”, “The selection of research equipment”, “Sources recommended by Ministry of Education and Science of Ukraine”, “Scopus sources”, “The promising developments of The National Academy of Sciences of Ukraine” were created and structured in the centralized ontology. A comparison of each tool to existing classic web-based analogue provided and described.
Nowadays, to increase the convenience and eficiency of data processing, the active digital
transformation of all of the areas of human activity [
The scientific method is a way that researchers used for many years. However, until now,
there are no approaches that can support the research process in educational research. For
example, in Crus et al. [
The scientific method is often used in the educational process. Quite often, teachers require
to research to complete an essay. There are various school competitions of scientific works
such as the competition of scientific articles of the Junior Academy of Sciences of Ukraine,
international competitions, those provided by international programs and other [
Often it is dificult for students and pupils to perform a scientific method and therefore,
to simplify it, several authors suggested the use of ontological systems [
It is possible to use a digital ontological-based approach to improve structuration, interactivity.
Smith [
In this article, an “ontological tool” is a term, that means some software or web system, that
consists of nodes with specific data and provide solving of some problem during educational
research. The node from which all branches go is called the parent or root. The top from
which no ribs protrude is called a leaf. The other nodes are called child nodes. If there are
no additional branches in the graph from the parent node, then this ontology is called simple.
Also, a characteristic feature of ontologies systems is that multiple ontologies can be filled with
concepts of various levels of complexity [
Ontologies have been using to visualize the results of the already performed experiment.
In Crus et al. [
To create the structure of the all research process, an ontological system called “Elements
of a common ontology of scientific experiments” (EXPO) [
Ontology constructor MoKi [
It can be useful in the “Do Background Research” stage of educational researchers. At the same time, it is limiting by the Wikipedia database.
There are also more specific ontological systems designed for the scientific method. For
example, an ontological database “Gene Ontology” [
All these ontological systems will be useful only at certain separate stages of scientific method such as “Do background research”, “Construct Hypothesis” and “Report Results”, and in most cases only for specialists in separate fields. So, none of the ontological systems previously proposed couldn’t ofer a universal and complex method to provide digital cloud-based support of educational researches. Also, all these systems haven’t integrated. That means, all these systems cannot fully interact with each other’s ontologies. Users must choose between them or feel discomfort memorizing and switching between them. The results of the comparison of ontological systems in the scientific methods have shown in table 1.
Besides, a common disadvantage of all considered systems [
So, it seems relevant to provide digital support of educational researchers provided by the scientific method using uncomplicated and understandable tools. Unlike observed systems, tools developed using IT-platform Polyhedron are simple to use, and it is possible to create all primary instruments in one environment.
This paper aims to develop the system of the most common ontology-based tools used by
pupils during educational researches using the scientific method characterized by advantages
compare to non-ontological-based tools. To provide it, IT-platform Polyhedron has used due to
its simplicity. These functions can provide semantic web, systematization, internal and external
searches [
This system is multi-agent, and internal sources can be used as agents. In such a way,
ITplatform Polyhedron allows to provide of transdisciplinary and interactivity of educational
research[
Besides, cognitive IT-platform Polyhedron has all advantages of the ontological information
representation [
The cognitive IT platform Polyhedron platform can provide the digitalization of the scientific
method in the learning process. Also, this system can be useful for the education process in
general by creating a centralized Information web-oriented educational environment [
For creating digital instruments, the sheets with data have loaded to editor4, the part of the cognitive IT platform Polyhedron. After that, the generation of the graph nodes with its characteristics have carried out. To provide information storage and exchange Google sheets were used to store data, with their further conversion into the .xls and .csv Excel sheets (see ifgure 2).
The obtained documents have used to create the ontological structure .xml and to fill the ontology graphs with semantic and numeric information for ranking or filtering. Some of the instruments to the web-oriented educational environment is using artificial intellectual features of the cognitive IT platform Polyhedron to provide additional semantic characteristics.
The received documents have 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
the cognitive IT platform Polyhedron. After that, the graph generation and the inputting of
semantic characteristics to each vertex have carried out. Ontological edges have formed using
predicate equations which described in previous work [
For the development of some ontological tools, specific “audit” and “ranking” [
IT Platform Polyhedron allows users creating a system or graph, read, update a system or graph, delete a system or graph and update the system configurations or graph configurations. All these sections we can split into several diferent subsections that are named: customization, data creation, information searching, data processing, data structuration, data validation, data isolation, data visualization and data deletion. Every diferent user has a diferent role in IT Platform Polyhedron. The Expert can create graphs, delete graphs, add metadata, edit metadata. Thus, the Expert is responsible for creating term fields and filling them with data for further processing in the Polyhedron IT platform. The IT Platform Polyhedron administrator performs specialized functions – the formation of a public library of ontologies and the system administration of transdisciplinary representation. The Young researcher can only read the necessary data, for individual purpose. UML diferent types of users functions diagram is shown in figure 3.
Search systems and scientometrics bases have compared with each other and the cognitive IT platform Polyhedron search system according to the following criteria: “Content integration”, “Lack of advertising”, “Interoperability with scientific and a patent search”, “Data security” and “Data Availability”, “Indexing of educational programs”.
Search systems which in response to the user’s query, provides all types of data (links, graphical results, semantic characteristics) meet the criterion of “Content integration”, and those of them. Search systems which characterized by the lack of advertising met the criterion of “Lack of advertising”. Search systems that provide results in the form of articles and patents have considered to meet the criterion “Interoperability with scientific and a patent search”. Search systems which do not find any malicious programs and viruses, meet the criterion of “Data security”. Search systems which don‘t have no one restrictions on access to information (for example, the fee for access or a mandatory registration) meet the criterion of “Data Availability”. Search systems that can use data directly from educational programs and integrated with them has been evaluated as meet the criterion “Indexing of educational programs”.
Proposed ontology-information solutions have compared with their web-oriented analogue criteria (except search systems) according to the following criteria: “Customization potential”, “Multifunctionality of information processing”, “Data structuration”, “Availability of adaptive interface”, “Data validation”, “Multi-user support”, “Data isolation”.
“Customization potential” criterion has used to evaluate possibility of the simply interaction with the system to provide adaptive analysis. Criterion “Multifunctionality of information processing” to evaluate possibility of the systems to provide data processing using few algorithms in same time. If all information is structured, easy to read, and perceived by the user the systems has been evaluated as meet criterion “Data structuration”. The criterion “Availability of adaptive interface” means that the system will be convenient in use for any circle of users, regardless of their computer literacy level. “Data validation” criterion has used to evaluate functionality of data validation by experts (on the absence of inaccurate or incorrect information on the resource and its coresponding to the actucal stadarts; for example, educational programs and national standard such as on the names of chemical compounds used during educational process (DSTU 2439:2018). The criterion “Multi-user support” indicates that the document in the system can be changed at one time by multiple users. “Data isolation” criterion means that system can provide access rights to information according to user roles and publish in the search only those results that relate to the user and his interests. “Multi-user support” criterion has used to evaluate the possibility of the systems to provide access management to information changing according to user roles and publish in the search only those results that relate to the user and his interests.
An ontology-based solution has developed to simplify the process of educational researches using the scientific method. Such ontological solutions were: “Search systems ranking”, “Search systems”, “Hypothesis test system”, “Centre for collective use”, “The selection of methods”, “The selection of research equipment”, “Sources recommended by the Ministry of Education and Science of Ukraine”, “Scopus sources”, “The promising developments of National Academy of Sciences of Ukraine”.
For systematization, simplification, and providing of a single ecosystem, these tools have compiled into the single simple ontology named “Scientific method”. It is structured according to the stages of the scientific method as “Do Background Research”, “Construct Hypothesis”, “Test with an Experiment”, “Analise results and Draw conclusion”, “Report Results” (see figure 4). The “Ask questions” stage skipped because no software required at this stage. Each of the nodes contains links to ontological tools, that can be used at an appropriate stage. The next part of the article will devote to the analysis of these tools.
Tools like search sites (Google, Bing, Yahoo, etc.) and scientometric databases (Scopus, Web of Science, CiteseerX, Microsoft academic, a miner, refseek, BASE (Bielefeld Academic Search Engine), WorldWideSciense, JURN, Google scholar, and Google patent and others) have represented in the “Do Background Research” ontological node. Each child node were a specific search system or a scientometrics database with a link to it. The general view of “Search systems” ontology has presented in figure 5.
The advantage of the cognitive IT platform Polyhedron internal search function is using
an algorithm, which conducted between the ontological graph with nodes. Additionally, this
algorithm can provide isolation and validation of information based on experts’ decisions called
internal search. That led to extended security and an increase in searching for material quality.
This is significantly important in conditions of developing science society, that led to dynamic
changes of the standards, as was with names of chemical substances of substance in Ukraine
last year. The proposed in this article system also has its search engine (internal and external)
described in previous works [
Scopus, Web of Science, CiteseerX, Microsoft academic, aminer, refseek, BASE (Bielefeld Academic Search Engine), WorldWideSciense, JURN, Google Scholar, Google patent have evaluated as particularly meet the criterion “The content integration”. Scopus, Web of Science, CiteseerX have assessed partly, because they provide only necessary information about article and their metadata.
Scopus, Web of Science, CiteseerX, Microsoft academic, aminer, refseek, BASE (Bielefeld Academic Search Engine), WorldWideSciense, JURN, Google Scholar, Google patent have evaluated as partly meet the criterion “Interoperability with scientific and a patent search”, because they provide search only among between scientific publications or patents in the one time. Google has evaluated as partly meet the criterion “Interoperability with scientific and a patent search” partly because it publishes results of search not only in the form of scientific publications and patents.
Scopus, Web of Science, CiteseerX, Microsoft academic, aminer, refseek, BASE (Bielefeld Academic Search Engine), WorldWideSciense, JURN, Google Scholar, Google patent have evaluated as partly meet the criterion “Data security” and “Data Availability”, because some search results require a fee for full access to information or mandatory registration on the website.
Google has evaluated as partly meet the criterion “Indexing of educational programs”, because it publishes search results primarily in the form of links on normative documents containing educational programs. The search systems have compared to each other. The results of the comparison are shown in table 2.
Thus, the comparison has found that the Polyhedron search system is more appropriate to use because it fully meets all the criteria. Also, has been found and confirmed that the Google search is more suitable for daily search and external literature review, as it meets such criterion: “Content integration”, but do not meet criteria: “Lack of advertising”, “Data security” and “ Data availability”, and only partly meet criteria: “Interoperability with scientific and a patent search”, “Indexing of educational programs”. The rest of the considered systems are suitable only for in-depth scientific research because they meet the criterion “Lack of advertising” and partly meet by the following criteria “Content integration”, “Interoperability with scientific and a patent search”, “Data security” and “Data availability”.
Therefore, the usage of ranking system can be more relevant, comparing to existing
approaches (searching systems). The ranking system expect preparation of numeric data from
scientific papers(reports). It is possible due to the experimental papers includes the same
information, for example, diferent works in the field of anaerobic digestion. All research papers
about anaerobic digestion include data processing parameters such as temperature, type of
substrate, reactor volume, moisture content, initial pH, parameters, characterises of the
eficiency of the process, biogas yield, methane content, average pH during the process, destruction
process etc [
The proposed approach involves the use of an ontology for the management of specialized literature using other functions of the Polyhedron platform such as filtering (according to the parameters created by the user), ranking, and audit (if the user needs it).
Yes Partly Partly Partly Partly Partly Partly Partly Partly Partly Partly Partly Partly
Yes Partly Partly Partly Partly Partly Partly Partly Partly Partly Partly Partly No
Yes Partly Partly Partly Partly Partly Partly Partly Partly Partly Partly Partly No
Yes No No No No No No No No No No No Partly
There is only one ontological tool “Hypothesis test system” for testing of hypotheses status only
this tool has represented in the “Construct Hypothesis” node. The Polyhedron platform has an
instrument to compare the hypotheses of several works. The instrument is a simple ontology,
where already have tested predictions from the scientific researches are semantic characteristics
of each node. Next, the audit function of the Polyhedron platform described in previous works
[
At the stage of “Test with an Experiment” specific ontological tools have developed and represented in the general ontology as: “Centre for collective use”, “The selection of methods”, “The selection of research equipment”. In Ukraine, it is possible to provide an experiment using tools located in centres of collective use of the National Academy of Science. To simplify the process of selecting the equipment, the web-based tool “Centre for collective use” has been created. However, to simplify the interface and make it more useful, ontology with the same data but with extended functionality have created. The leaf nodes of this ontology are analysis devices. Visual comparison of ontological and non-ontological tools “Centre for collective use” is presented in figure 8.
Non-ontology system “Centre for collective use” has several shortcomings, both visual and functional which are obsolescence and inconvenience of the interface, inconvenient navigation in the system, and the complete absence of a filtering system. These factors make the application unsuitable for the selection of equipment during the process of planning of the experiment.
The proposed ontological-based tool “Centre for collective use” is having not only an upto-date interface but also several advantages. One of the key features is a stable semantic link and the ability of the system to combine all of the innovative applications of digitalization of the educational and research process. Also, have created an ontological-based system “Centres of collective use” is conveniently classifying scientific equipment by departments of science it belongs to. This feature was realized as non-user-friendly in traditional web-based tool.
Besides, the “Centre for collective use” use in the cognitive IT platform Polyhedron platform has several useful filters, unlike web-based tool. These filters are “the sphere of science”, “section of National Academy of Science of Ukraine institution belongs to”, “Location”, “object of study”, and “measured parameter”. All these filters will be especially useful for novice researchers. These two systems have compared each other. The result of the comparison is shown in table 3.
Non-ontology “Cen- Ontological-based system tre for collective use” “Centre for collective use”
As a result of the comparison, it has found that the “Centre for collective use” in the cognitive IT platform Polyhedron is more appropriate to use, because it fully meets all the criteria. It has established that the non-ontology-based version of the “Centre for collective use” is undesirable for use because it doesn’t meet the following criteria: “Customization potential”, “Multifunctionality of information processing”, “Data structuration”, “Availability of adaptive interface”.
There are many potential cases of using “Centre for collective use” in the cognitive IT platform Polyhedron. For example, the user needs to find a device that is located in Kyiv, and which investigates atomic particles. As a result of the user request, the device is the Isochronous cyclotron U-240 of the Institute of Nuclear Physics, which is located on Nauki Avenue. This and some other examples of applications are shown in table 4.
Filters Case 1 Case 1 Case 3
Location: Kyiv The object of study: Atomic particles Location: Kyiv Purpose: Analysis of X-ray spectra Location: Lviv Purpose: Microscopic examinations Results cyclotron U-240 Module for CEM INCAPenteFETx3 Scanning electron microscope EVO 40XVP
In the laboratory MANLab of the National Center of Junior Academy of Science centre of collective usage of the research equipment devoted to the research education has been created. The same approach to simplify (using the ontology) the selection of the equipment called “Selection of equipment in MANLab” has been developed. Leaf node in this ontology is separate equipment located in MANLab. The filters such as the parameter which needs definition, “Measurement accuracy”, “Measuring range” “The parameter which needs definition” will be useful for selection. The General view of filtering input system for “The selection of research equipment in MANLab” ontology is shown in figure 9
Novice researchers can easily find the equipment in both, Centers of collective usage in National Academy of Science and Junior Academy of Science. For example, the researcher needs to provide the information about the content of heavy metals in the water, and it is already known that the content is high. The system can provide both ranking and filtering for solving the tasks. Any of these instruments will propose to use for this task the Universal polarograph EKOTEST-VA. By Choosing of this instrument, novice researchers will be able to use the links on manlab.inohst.com.ua web-page with detailed information on the equipment. The list of cases of application the proposed filtering system is presented in table 5. The General view of ifltering input system for “The selection of methods” ontology is shown in figure 10.
The other routine tasks that need to be solved during the planing of the experiment (“Test with an experiment stage) is choosing the methods of research. The main problems in that field that a wide variety of methods are presented in the form of printed text (books or methodical instructions) which is hard to process. However, using filtering systems of IT-platform Polyhedron, it is possible to provide management and simplify this task. The ontology used to solve this task called “The selection of methods”, and the leaf node of it is method itself with the metadata. For example, the youth researcher “is required to select to determine the content of Al (III) in water. As a result of a user request, the system will propose the photometric analysis
The parameter which needs definition: concentration of heavy Universal
polarometals in the liquid Measuring range: 0.1 g / dm3-1g / dm3 graph EKOTEST-VA
The parameter which needs definition: CO2 concentration Mea- Carbon dioxide
sensurement accuracy: 20% Measuring range: 350-5000% sor DT040
The parameter which needs definition: O2 concentration
Measuring range: 0-12,5 mg / dm3 Oxygen sensor DT222A
methodology, and display all necessary information, including chemical utensils, reagents,
needed equipment. Finally, the result will contain a link to the web-methodology at Junior
Academy of Science web-environments (manlab.science or stemua.science [
An example of the application of the proposed ontological system has given at “Analise results and Conclude” node. At the stage of result analysis, both ofline tools like MS Ofice, PTS Mathcad Origin Pro, and cloud-based like G Suite and Ofice 365. The Polyhedron IT-platform can allow to process and present the results of researches. Semantic and numerical characteristics from Excel or Google Sheets have used to construct graphs and diagrams. Also, the necessary data can be taken from the existing ontological graph. This is followed by the standard method of creating
Purpose: Water quality analysis The parameter Investigation of water samples for aluwhich needs definition: Al (III) minum content by photometric method Type of analysis: qualitative The parameter which Deposition of proteins by mineral acids needs definition: The presence of proteins Type of analysis: Titrimetric determination The Determination of vitamin C content in parameter which needs definition: vitamin C food by iodometric method for ontological graphs and further use the module to build graphs and charts. For demonstration results of statistical researches on mortality from various diseases in Ukraine from 2016 to 2020 (include from COVID-19) were taken. The graph with these results of statistical surveys in the Polyhedron system is presented in figure 11.
The “Sources recommended by the Ministry of Education and Science of Ukraine”, “Scopus sources” “The promising developments of National Academy of Sciences of Ukraine” ontological systems have represented in “Report Results” node. Those instruments have compared with their non-ontological web-analogues.
After providing the research and analysing of the results, it may seem relevant to publish the data. Now in Ukraine, it is possible to can be divided into between the journals recommended by the Ministry of Education and Science of Ukraine, and the journals indexed by scientometric bases. However, choosing of the journals, is always the challenge, especially for novice researchers and to simplify the tasks both ontological and non-ontological tools is existing nowadays. The ontological tool developed using IT-platform Polyhedron consist from the leaf nodes (separate journals) with semantic data. To simplify the tasks, the filters like “Field of Science”, “Free of Charge Journals”, “Publication Languages” have developed. There are web-oriented and ontological systems for the selection of sources recommended by the Ministry of Education and Science of Ukraine. A general view of references recommended by the Ministry of Education and Science of Ukraine in bought forms are shown in figure 12.
“Sources recommended by the Ministry of Education and Science of Ukraine” and “Scopus sources” ontologies have created. Both of ontologies are complex and contains branching by branches, of science, type, indexes, and other parameters of journals for publication. The final child nodes are each journal for publication. Such necessary filters as language of the journal, cost of publication (including frees) is absent in web-based application, which may limit it using. For example, today researchers are increasingly paying attention to the citation style of the journal. General view of Scopus sources in standard web-oriented and ontological form are shown in figure 13. All these systems have compared to each other. The result of the comparison is shown in table 7.
Criterion name “Sources rec- “Scopus ommended by sources” the Ministry of Education and Science of Ukraine” “Sources recommended “Scopus by the Ministry of Ed- sources” by ucation and Science of cognitive Ukraine” in cognitive IT IT platform platform Polyhedron Polyhedron Customization potential No Multifunctionality of in- No formation processing Data structuration No Availability of adaptive No interface Data validation Yes Multi-user support No Data isolation Yes
No No
As a result of the comparison, it has found that “Sources recommended by the Ministry of Education and Science of Ukraine” in cognitive IT platform Polyhedron and “Scopus sources” by cognitive IT platform Polyhedron are more appropriate to use because it fully meets all the criteria. “Sources recommended by the Ministry of Education and Science of Ukraine” is undesirable for use because it doesn’t meet the following criterion “Customization potential”, “Multifunctionality of information processing”, “Data structuration”, “Availability of adaptive interface”, “Multi-user support”. As a result of the comparison, it has established that the “Scopus sources” is undesirable for use because it doesn’t meet the following criterion “Customization potential”, “Multifunctionality of information processing”, “Data structuration”, “Multi-user support”. So, ontology-based tools “Sources recommended by the Ministry of Education and Science of Ukraine” and “Scopus sources” is more appropriate to use.
For presentation of research results was created “The promising developments in The National Academy of Sciences of Ukraine” in web-oriented non-ontology form containing all the promising scientific projects of Ukraine. Ontology-based tool” The promising developments of National Academy of Sciences of Ukraine” ranking ontology has created with functions of ranking and provides better information management. The ontology is simple with scientific developments, as leaf nodes. General view all the promising projects of National Academy of Sciences of Ukraine and result of the ranking ontology tool presented in figure 14.
This tool will be useful for potential investors who are looking for investments. For example, investor requesting to find the most finalized developments “The promising developments in The National Academy Sciences of Ukraine” by the cognitive IT platform Polyhedron, the system will display the projects “contact digital thermography”, “fibre-optic thermometric system”, “growing of structurally perfect diamond single crystals”, “Technology of support, and anchor fastening of earthworks appointment” are the most finalized developments. The non-ontology tool “The promising developments in The National Academy of Sciences of Ukraine” has been compared with ontological-based form “The promising developments in The National Academy
Sciences of Ukraine” by cognitive IT platform Polyhedron. The result of the comparison is shown in table 8.
Non-ontology “The promising “The promising developments in developments in The National The National Academy Sciences of Academy of Sciences of Ukraine” Ukraine” by cognitive IT platform
Polyhedron
As a result of the comparison, it has been found that Ontological tools for the support of the scientific method created by cognitive IT-platform Polyhedron are more appropriate to use because they fully meet all of the comparison criteria. And all of the non-ontological tools for the support of the scientific method only meet the criteria: “Availability of adaptive interface”, “Data validation”, “Data isolation”. The overall result of the comparison is shown in table 9.
We can use the “search system” ontology in the background research stage, “Hypothesis test
No Yes Yes Yes Yes Yes Yes system” can be used in the construct of hypothesis stage. Depending on the presence or absence of the experiment, we can use two diferent ontological solutions “The selection of research equipment” and “The selection of methods”. In the report results stage it is possible to use three diferent ontologies “Scopus edition”, “The edition recommended by Ministry of education and science of Ukraine” and “The promising developments of NASU”. All proposed ontological tools are extensions and support the method as illustrated in the workflow diagram (see figure 15).
A centralized ontological tool based on the IT platform Polyhedron consisting of “Search systems ranking”, “Search systems”, “Hypothesis test system”, “Centre for collective use”, “The selection of methods”, “The selection of research equipment”, “Sources recommended by the Ministry of Education and Science of Ukraine”, “Scopus sources”, “The promising developments of The National Academy of Sciences of Ukraine” has been created. These ontological tools can be used during almost all stages of the scientific method used in educational research. As a result of the comparison, it was found that all systems created by the cognitive IT-platform Polyhedron are more appropriate to use because they fully meet all the comparison criteria.