SUGISAKAMASANORI

Journal of Robotics, Networking and Artificial
Life Vol. 10(4); March (2024), pp. 342–352
ISSN (Online): 2352-6386; ISSN (Print): 2405-9021
https://alife-robotics.org/jrnal.html

Research Article

Systems Science: Digitalization of Transdisciplinary Research
Mykola Petrenko, Kyrylo Malakhov
Microprocessor technology lab, Glushkov Institute of Cybernetics of the National Academy of Sciences of Ukraine, Kyiv, Ukraine

ARTICLE INFO
Article History
Received 03 April 2024
Accepted 07 May 2024
Keywords
Transdisciplinarity
Systems science
Ontology engineering
Digitalization
Convergence clusters
Scientific picture of the world

ABSTRACTThe conceptual foundations of transdisciplinary researches with the use of methods and means ofartificial intelligence, including ontological engineering, have been developed. The stages offormation of the theory of transdisciplinarity are defined, in which the processes of building thecategorical level of concepts and integration of subject knowledge, the formation of clusters ofconvergence of subject disciplines, the scientific picture of the world and the corresponding global
network of transdisciplinary knowledge take a special place. In this case, a special role belongs to
informatics as a system-forming branch of knowledge. The development of the NBIC-cluster ofconvergence opens wide, so far completely not assessed, possibilities of a global knowledgeoriented Internet, but with it also the whole of modern civilization. Obviously, this development
will follow first the path of creation of the applied distributed systems in specific subject areas(Internet of Things, Smart systems in telemedicine, environmental monitoring, information
support of goods and services, energy systems, utilities, etc.). Grid-, Block-chain-technologies
and Cloud-computing, as well as virtual organizations, structures and services will occupy thecentral place in them.
© 2022 The Author. Published by Sugisaka Masanori at ALife Robotics Corporation Ltd.
This is an open access article distributed under the CC BY-NC 4.0 license(http://creativecommons.org/licenses/by-nc/4.0/).

activity. Nowadays, in connection with convergent
technologies, the question has arisen, to what extent ishumankind ready to go in these transformations when
they concern the person himself? This question involves
not only the sphere of self-knowledge and selfdevelopment, but also self-preservation. Below the
ontological representation of the noosphere is given, in
which, inter alia, issues of the development of humansociety are touched upon.

1. Introduction
In the modern scientific picture of the world (SPW),
based on the ideas of the general concept of evolution,
self-organization, co-evolution, nonlinearity, it isassumed that the subject understood as a society, enters
the system it cognizes as an active component of thisprocess-system [1], [2].

It was necessary to expand the scientific worldview
what requires science more deeply and intensively
penetrating into the essence of the laws of nature andsociety, than it was possible to do with the help ofdisciplinary and interdisciplinary approaches. J. Piaget
believed that “after the stage of interdisciplinary research,
one should expect a higher stage — transdisciplinary,
which will not be limited to interdisciplinary relations,but will place these relations within the global system,without
strictboundaries
among
disciplines.
Transdisciplinarity should be considered as a new field ofknowledge, different from multidisciplinarity and

There was a philosophical concept called thetranshumanism, which is exploring the possibilities andconsequences of achievements of science and technology,
the dangers and the benefits of using them. In opposition
to transhumanism, the ideas of posthumanism are
represented, the central thesis of which is the acceptanceof Man, Society and Nature as three jointly evolving
systems [3].
Techno-science have become a force capable offundamentally changing the nature of man and his life

Corresponding author E-mail: malakhov@incyb.kiev.ua URL: https://linktr.ee/malakhovks342

interdisciplinarity” [4]. Historical aspects of theformation of transdisciplinary research are considered in[5].

studied simultaneously in different aspects by several
disciplines at once.
In this paper, these terms are understood depending on
the “distribution” of concepts and scientific disciplines
with respect to the ontological levels of hierarchy, which
implies different patterns of their interaction. Such
distribution is essential when considering themethodology of the TD interaction, system integration ofsubject disciplines and formation of the “convergenceclusters” in implementation of transdisciplinary projects
and their information and technology support.

The purpose of this publication is to develop a
conceptual framework for the digitalization oftransdisciplinary scientific researches.
2. Brief Description of Types of Scientific Researches
In terms of the classification of scientific approaches, it
is useful to choose such criterion as the degree ofcompleteness of knowledge of the surrounding world.
Then all the approaches can be reduced to four maintypes:
disciplinary,interdisciplinary(ID),multidisciplinary and transdisciplinary (TD) approaches.

Such notions as Noosphere, Object, Process, System,
Information, Nature, Society, Man, Subject Branch,
Science, Scientific Activity, Scientific Picture of theWorld, Engineering, Technology, etc. refer to thecategory level. Such concepts as Philosophy, Physics,
Mathematics, Biology, Chemistry, Medicine, Humanities
and Social Sciences, Informatics, Nanotechnologies, etc.
refer to the level of domains of scientific disciplines.
Many scientific disciplines which are directions, sections

Interdisciplinarity is understood as the integration ofscientific areas through mutual penetration of common
concepts. The term “multidisciplinarity” means suchresearch, when an object, process or phenomenon isFig. 1. The analysis times of numerical integrations

343

and sub-domains of domains, refer to the level ofscientific disciplines.

variants of their cross exposure. TD allows one to build a
unified TD-methodology of analysis and synthesis,
including it in the general scientific picture of the world.
In more detail the problems of synergy are considered in[5].

Aforesaid is explained by the scheme presented inFig. 1.

Multidisciplinarity does not imply the transfer of
research methods from one discipline to another. All
disciplines retain their subject directions.

Disciplinarity allows science to develop progressively
within subject directions, and a disciplinary approach
divides the surrounding world into separate subject areas.
If solving a task or problem goes beyond the scope of
disciplinary approaches, it is commonly believed that it is“at the intersection of scientific disciplines”. In theprocess of progressive development of the disciplinary
approach, an opposition occurs, which conditions on the
one hand, the accumulation of disciplinary knowledge,
and on the other, is the establishment of a natural limit to
the fullness of knowledge of the surrounding world. The
way out of this situation is indicated by the following
thesis: “If it is impossible to go beyond the disciplinary
direction, then the scope of disciplinary methodology canbe extended” [6]. In turn, the expansion of the field of
application of disciplinary methodology has led to theemergence of interdisciplinary and multidisciplinaryscientific approaches, which made up the following
levels of classification of scientific approaches. The
process of their development has led to the fact that themetaphor “the junction of disciplines” gradually acquired
the form of interdisciplinary and multidisciplinary
directions, each of which has its own characteristics ofsolving tasks.

In a multidisciplinary approach, researchers form ageneralized picture of the subject of the research, in
relation to which all of its disciplinary pictures appear as
its equal in rights parts. The accumulation of results ofmultidisciplinary research in similar areas of disciplinary
knowledge leads to the emergence of new
multidisciplinary disciplines, such as physic-chemical
biology, ecology, etc. The multidisciplinary approach has
found its practical application, in particular, in the workof expert groups.
TD system approach uses the knowledge generated andaccumulated by disciplinary, interdisciplinary andmultidisciplinary approaches. TD should ensure
coordination and integration of disciplinary knowledge
on the basis of a single axiomatic approach (the TD
general systems). This is how TD was originally
imagined by J. Piaget and E. Jantsch [4], [7].
Transdisciplinarity is a research strategy that crosses
disciplinary boundaries and develops holistic (priority
consideration of the whole in relation to its parts) vision.
TD in the narrow sense means integration of various
forms and methods of research, including special
techniques of scientific knowledge, for solving scientificproblems. TD to wide extent means the unity ofknowledge beyond specific disciplines.

Interdisciplinarity involves the integration of several
scientific disciplines. One of them plays a leading role,and the results of ID-research are always interpreted interms of leading discipline. The peculiarity of the IDapproach is that it allows direct transfer of researchmethods from one scientific discipline to another. The
transfer of methods in this case is due to the discovery ofsimilarities of the studied subject areas. ID approach isintended first of all, to solve specific disciplinary
problems in which solving in any particular discipline theconceptual and methodological difficulties arise.
Synergetic paradigm as a section of the ID-approach in
the hierarchy of knowledge occupies a special place. On
the one hand, it appeals to integrity and integral
representation, systematically determining the effects ofobjects, processes and subjects’ interaction, on the other
hand, focuses on nonlinearities, instabilities and theappearance of attractors, which ultimately change multilevel organization and system behavior. In both cases, it
is expressed by a set of formal models of selforganization and is directed to reproduce the scientificpicture of the world, which is especially important during
the transition to a transdisciplinary approach to researchand implementation of the paradigm of global
evolutionism. SPW can be represented as a TD-ontology,
which incorporates not only the ontologies of individual
disciplines, but also the methods of the latter, including

Let us note the changes in the structure of science, due
to the transformation of a disciplinary organized sciencein TD research:• highlighting the following signs of the postnonclassical stage: a change in the nature ofscientific activity, due to a revolution in the meansof obtaining and storage of knowledge(computerization of science, fusion of science withindustrial production, etc.); increase of theimportance of economic and socio-political factors
and goals; change of the object of study itself —open self-developing systems (“human-sized”
objects, examples of which are biotechnology
objects, ecological systems, biosphere, etc.) [5];• TD-studies,capturingtheborderzones(demarcation) areas of scientific disciplines,
integrate the essential foundations of the latter,
forming the so-called convergence clusters, inwhich a powerful synergistic interaction occurs due344

to the interpenetration of paradigms and specificcurrent results of each of the disciplines included in
one or another cluster. This interaction reflects theintegrity of the real world, being an incentive and at
the same time a guarantee of the success of TD
research and related practical projects, the nontriviality and significance of their results [8].

improvement of research design processes, developmentof methods and tools for ontological analysis of natural
language objects in order to extract knowledge from them,applied aspects of the use of ontologies, meta-ontologies,
knowledge integration systems in transdisciplinary
convergence clusters [5].
The cluster of NBIC-convergence and intersecting with
it LIInK-cluster (L — language, I — information, In –Intelligence, K — knowledge) can serve as a vivid
example of technoscience. Informatics brings to theseclusters both system-forming, and computertechnological components. The main breakthroughdirections in these clusters are: erasing the faces between
living and inanimate systems, nanorobotics with its
numerous
applications,
globalsupercomputer
agglomerations with a high level of artificial intelligence.
To these should be added the unified distributed TDknowledge system as a globally-communicative version
of a general scientific picture of the world and the nextstage of development of the existing Internet and the
Semantic Web. In [2], a possible scheme for predicting
and targeting the formation of promising convergenceclusters is proposed according to the scheme shown in
Fig. 2.

3. Transdisciplinarity and Formation of Convergence
Clusters
The unity and systemic complexity of the world as an
object of scientific research suggests that, along with theprocess of differentiation, it is advisable to consider theprocess of integration of scientific disciplines andrelevant technologies. After all, it is the fundamental
paradigm of the evolutionary theory of academician
Vernadsky. The process of integration, which began quite
recently, seemingly on a spontaneous (intuitive) basis, isnow becoming conscious and obvious. And mostimportantly, prompted by evolutionary theory, it is aimed
at creating a Single Common Knowledge, the essence of
which clearly appeals to the construction of a ScientificPicture of the World based on a transdisciplinary conceptof the development of science. The first stage of theintegration process can be called the clustering stage. The
most superficial analysis of the clustering phenomenonshows that it is based on a deep interaction of methods,
tools and capabilities of the cluster components, thesynthesis of which generates synergistic effects throughthe integration of the functional properties of thesecomponents and opens up broad prospects for creating
previously unknown scientific theories, samples of new
equipment and technologies. The integration process thathas already begun raises many questions, the answers towhich will allow us to outline new promising ways ofevolution of knowledge and science in general inaccordance with Vernadsky’s noospheric theory. One of
the tasks on this path is to analyze the structure ofknowledge at the conceptual level. General knowledge
and each of its disciplines can be represented by a total
set of concepts-terms that constitute the ontological basis
for describing knowledge, formal or informal. Each term
has its own generally accepted definition, which is
described using lower-level terms (or concepts). A
technological multilevel ontological description of bothgeneral knowledge and its individual disciplines, sections,
theories, etc. has been created, opening up the possibilityof formal knowledge representation using a single
ontological engineering toolkit, which opens up broadprospects for the development of cognitive technologies
and their productive use [2].

Fig. 2. Approximate scheme of formation ofprospective convergence clusters
Here

D1 , D2 ,..., DL

corresponding
convergence–

technologies,

disciplines

andK1 , K 2 ,..., K L

clusters, ={Pi } , i 1, 2,...M < L

their
–
–

selection and application of promising clusters.
Fig. 3 presents the scheme of interaction of domainlevel concepts in the formation of convergence clusters.
Thus, TD research is a qualitatively new stage in the
integration of science and society. For its completion, thescientific community still has much to develop, inparticular:

Currently, there is a tendency to intensify scientificresearch both at the intersection of different subject
disciplines (interdisciplinary research) and inconvergence clusters (transdisciplinary research). To
support these studies, important factors are theconstruction of knowledge-oriented information systems,
345

The listed tasks are generalized and, in turn, include anumber of subtasks.

• general scientific picture of the world, including
subject disciplines, and the corresponding global
network of TD knowledge;• metatheory and metalanguage of TD;• the systemology of TD interaction, the figurative
conceptual apparatus and models, the possibilitiesof which would allow, on the one hand, to cover all
factors forming a complex problem and affecting it,on the other hand, to identify and take into accountthe mechanisms by which this effect is carried out;
• the method (or a set of methods) of system research,
providing access to all disciplinary information andits analysis, is understandable and available tospecialists of any scientific discipline;• prospective and self-sufficient convergence clusters
that make up the core of the sixth technologicalorder;• the methods of conducting experiments that allow
studying the multifactorial effects of objects ofknowledge and evaluating their results. Including
various information technology tools to increase
efficiency and accelerate results [6], [9], [10], [11],[12];• the ways of posing and solving complex multifactor problems in science, engineering andtechnology.

3. Transdisciplinarity-noosphere Сoncept-picture of
the World
It is in the transition to a knowledge society and TDknowledge-oriented technologies the system formingrole of informatics is manifested for real. The path to the
TD lies through the creation of the system of ID
interactions (in the light of the evolution of scientifictheories) as an independent branch of knowledge.
Moreover, informatics, in addition to a clear
mathematical basis, also grasps technologies of posing
and solving complex scientific-engineering problems.
Thus, the essence of the TD approach to the study ofcomplex scientific and technical problems consists ineffectively ensuring the dual unity of the concepts ofdeepening specific knowledge in the subject area, on the
one hand, and expanding the coverage of the problem,
based on the reality of the unity of the world, and recreatea holistic SPW on the other.

Fig. 3. Scheme of interaction of domain level concepts at formation of convergence clusters
346

The terms: noospherogenesis, transdisciplinarity,
ontology-driven systems, virtual paradigm, informationand cognitive support for scientific research,personalized knowledge bases, smart projects, Internet
things clearly outline, first of all, the subject area of
informatics and information technologies of the XXI
century, focused directly on the stage of humandevelopment, based on knowledge economy. In fact, theprocess of noospherogenesis, according to V.I.
Vernadsky, touches on the deeper aspects of interactionin the “Man-Nature” system. It appeals to scientificthought and, consequently, to the cognitive resources of
the human mind and SPW, the construction of which is
impossible without the TD approach to science andhuman civilization as a whole [8]. Fig. 4 shows a variantof the categorial level of the noosphere and possible
prospects for the development of human society.

The Fig. 4 shows the main concepts of the noosphericparadigm, they are dominated by the triad “knowledgeoriented concept
collective
mind sustainable
development of society”.
TD-studies allow one to understand the complexity ofthe problems being solved, to take into account thediversity of ideas about the life world and the problems
posed, to link abstract and concrete knowledge with theuse of the “ontological engineering” and global networkof TD knowledge.
Methodologically TD-studies include a number of mainstages:1. analysis of the problem, its identification andstructuring;

Fig. 4. Scheme of the Noosphere categorical level347

2. the development of the missing theoretical material
necessary for problem solving;
3. the construction of clusters of convergence of
subject areas;
4. choice of a language (or development of the newone) for the formalized presentation of knowledge
domain and corresponding computer ontologies;
5. practical implementation of the project.

world are presented in Fig. 5. It is clear that all aspects(even basic ones) of the indicated levels of knowledge
cannot be reflected in one scheme. Therefore, here theemphasis is on the category “Nature → Society → Man→ Knowledge of the World → TD scientific research”.
The figure shows three generalized levels.

These stages are organized in a linear sequence, buthave also feedbacks.

1. Properly, the actual level of categories, structured
into six sublevels (0 ÷ 5) in accordance with thecategorial relationship.
2. The level of domains of subject and scientificdisciplines. It is divided into three sublevels (1 ÷ 3),
which mainly reflects the domains of the branch ofscience. Starting from this level, the semantic
relations between concepts are already amenable tosome scientific understanding. Most of them are
represented by “be whole”, “be part”, “be species”
and “be genus”.
3. The level of disciplines is represented only by theroot vertices of the subject disciplines andtechnologies of the sixth technological structure. At
this level, “whole-part” relationships prevail. Let us
briefly describe the levels listed above.

The Fig. 5 shows three generalized levels.

4. Basis of Ontology-oriented Support for TD
Research
The research methodology and design of themechanism of ID interaction in solving complex
scientific and technical problems are associated with thecreation of a conceptual framework of scientific theories.
A set of C , R, F formal computer ontologies of
specific knowledge domain may be such a framework.
Formally, such an ontology can be represented by foursets:

O = C , R, F , A ,(1)

Categorial level. An unshakable rule for constructing
any ontograph is to indicate the root vertex concept,
which includes in its scope all the underlying verticesconcepts. In this case, such a vertex is the category“Universe” (B) (level 0). Formally, B is a type of thehighest (zero) level of categorization, has nodifferentiation [5], [13].

where C , R, F , A — finite sets respectively: C —concepts of knowledge domain, R — relationshipbetween them, F — interpretation functions (both C andR), A — axioms [10], [13].
The implementation of the ontological concept involves
a complete description of knowledge domain, for this it
is necessary: 1) to form and process (perform semantic
analysis) the integrated linguistic corpus of texts by given
subject areas; 2) to build ontographs (sets C, R) for eachknowledge domain; 3) to formalize descriptions ofknowledge in the form of a scientific theory; 4) to carryout procedures of processing and integrating subject
knowledge using semantic analysis systems of source
text materials and analytical processing and presentation.
An example is the toolkit Polyhedron (transdisciplinary
ontological dialogues of object-oriented systems), which
is presented as a complex of program-informational andmethodical knowledge management tools using
approaches of ontological management of corporate
information resources [14].

Level 1 contains the categories “Cosmos”,“Noosphere”, “Object” and “Process”. The category“Cosmos” on the presented ontograph (see Fig. 5) is notconsidered in detail (at this stage). The category“Noosphere” is represented by the ontograph (see Fig. 4).
The categories “Object” and “Process” are included toseparate concepts into static and dynamic types. The
ontograph does not contain the categories “Material” and“Abstract”, because the thematic focus of the ontographinvolves the inclusion of mainly abstract concepts.
The categories of sublevels 2 ÷ 4 reflect the essential
basis of TD research, and the categories of sublevel 5
detail them.

The role of ontologies of subject knowledge, besides
the traditional functions of conceptualization andspecification of scientific theories, is in theimplementation of ontological management at the levelof computer system architecture.

The level of domains plays an important role in theformation of “convergence clusters” organicallyconnected set of scientific theories, modem technologies
and technical branch achievements. The indicatedcoherence is clearly manifested in the above-mentioned
NBIC-technology cluster.

In more detail the categorial and domain levels ofknowledge in the scientific and ontological picture of the

The level of disciplines specifies the subject
disciplines, scientific theories and technologies. The
348

scheme of categorial level of concepts (see Fig. 5) is
structured in accordance with ontological principles, thelogical law of the inverse relationship between thevolume and content of concepts and claims-statementsthat are recommendatory in nature [13].

This is because modem science explores complex andself-developing systems that require cooperativeinteraction of various scientific disciplines. So, ecology,
general systems theory, cybernetics, informatics, andsociobiology are examples of a complex of naturalscience, technical, and humanitarian research. In
particular, there is a well-known approach to thedescription of complex reality, which is connected with
the ideas of constructing artificial intelligence, inparticular, with its sections: neurocomputing, patternrecognition, multi-agent systems, decision making and5. Information Technologies of Supporting TD
Research
Currently, the development of science is characterized
by increasing trends of integration in the study of objects.

Fig. 5. Scheme of interaction of concepts of categorical level349

expert systems, developing intelligent information
systems.

same time, the social component is added to therequirements, for which the parameters of reliability,
efficiency and safety prevail. When considering theprocess of natural development of science and increasing
demands on it by society, an integrated information
technology system, which provide organizational
processes, monitoring of scientific research, regulates allstages of their life cycle and electronic document
management, analysis and evaluation of research results,
decision making and determination current trends, etc.,
should be a basis for managing TD research. As a result,a common integrated space TD-knowledge is created,
where synergistically many teams of professionals fromdifferent subject areas can interact, which will focus on
solving the most important TD scientific and practicalproblems [16].

Fig. 6 summarizes in the generalized form theinteraction of the pair: “Transdisciplinarity ↔ Computer
Science”.

The core of integrated information technologies for TD
scientific research consists of systematically integrated
bases of structurally presented knowledge, distributed
knowledge-oriented services, providing highly organizedaccess to information and computing resources, theperformance of such functions: identification of patterns,
support of decisions making, cooperative collaboration
virtualization, outsourcing, application of modern
methods of processing multimedia information resourcesin virtual hyperspace.

Fig. 6. Scheme of interaction of the pair
“Transdisciplinarity ↔ Computer Science”
Development and application of intelligent information
systems (IIS) in various areas of human activity led to thecreation of IIS of a new class, combining the propertiesof TD, ontological management, united by the conceptsof purposeful development and virtuality. This is TD
class of developing ontology-driven systems of research
design. In addition to the tasks of infrastructural support
for scientific research, here the tasks of their
methodological support and ensuring the processes ofintegration, convergence, unified representation of TD
knowledge and operations on them come to the fore. A
significant role is played by systemological skills training
and expansion of range of worldviews of scientificresearchers to ensure the dual unity of the concepts ofdeepening knowledge in a particular subject area, on the
one hand, and expanding the scope of the problem, basedon the reality of the unity of the world and need to forma unified system of knowledge about the world, on theother hand [15].

Transition from the nondeterministic mode of
production and use of knowledge by subjects of thescientific process to the mode of effective knowledge
management, presented in a unified form at all stages of
their life cycle, will ensure the growth of the effectivenessand quality of scientific research. At the same time,sustainable knowledge will become an intellectual capital,
and the subjects of science will be direct participants inthe economic activities of the society, which will create
favorable conditions for stimulating the development ofboth science and creative society [16].
TD in turn puts forward the requirement of integrationof scientific disciplines on the basis of formalism,
common to all subject areas. This is the formal computer
ontology. Hence, the process of noospherogenesis isbased on the paradigmatic tuple (noosphere-SPWtransdisciplinarity-ontologicalconcept-applied
intellectual systems and technologies).

From the positions under consideration all the evolving
information systems can be divided into four interrelatedclasses: genetic; with virtual architecture andreconfiguration; knowledge-oriented; transdisciplinary.
In addition, they include two fundamentally different
subclasses: autonomous and nonautonomous systems.
The latter are intended for active human-machineinteraction, or more precisely, natural and artificial
intelligence. Examples of intelligent technologies andcomputer systems such as “Systems of research design”,“Multi-agent technologies and neurocomputing”, “Gridcomputing and cloud computing” are considered in [5].

So, let us formulate an open (complemented anddeveloping) system of requirements to information
technologies supporting TD research.
1. New computer technologies should be built on thebasis of knowledge adequate to the processes ofsolving problems in science, nature and society.
2. Continuous improvement of both the technologies
themselves and the methods of manipulating them.

As stated above, the fields of application of TD studies
are constantly expanding, which, in turn, requires thecontinuous improvement of information (including
supercomputer) technologies to support them. At the350

3. Information and knowledge have the property ofidempotency,
andtherefore
information
technologies must support this property(information sharing and knowledge sharing).
4. Promising modem methods of processing data,
information and knowledge should be supported,
including: close interaction with Grid-, Cloud- andSupercomputer technologies; ability to handle large
amounts of data (Big Data); multi-factor
authentication; focus on Green Computing(environmental technologies).

technologies have already become the basis of almost all
Hi-Tech and construction of knowledge-oriented society,capable of resolving all essential contradictions of thedevelopment of modem (technological) civilization.
7. Credit Authorship Contribution Statement
Mykola Petrenko: Supervision, Conceptualization,
Methodology, Writing – original draft.
Kyrylo Malakhov: Validation, Resources, Term,
Writing – review & editing.

6. Conclusion

Acknowledgements

V.I. Vernadsky teaching about the noosphere in its
essence appeals to the SPW, which must be built in orderto overcome ID barriers and increase effectiveness ofinterdisciplinary interaction and modern science ingeneral. It is about creating universal TD knowledge.

The Microprocessor Technology Lab research teamextends sincere thanks to Oleksandr Palagin, adistinguished scholar and leader in the field, for his
invaluable guidance and supervision throughout thisproject.

The development of the NBIC-cluster of convergence
opens wide, so far completely not assessed, possibilities
of a global knowledge-oriented Internet, but with it also
the whole of modern civilization. Obviously, thisdevelopment will follow first the path of creation of theapplied distributed systems in specific subject areas(Internet of things, smart systems in telemedicine,environmental monitoring, information support of goods
and services, energy systems, utilities, etc.). Grid-,
Block-chain-technologies and Cloud-computing, as well
as virtual organizations, structures and services will
occupy the central place in them.
Thus, the problems of effective support for scientific
TD research will lead to the formation and systems
analysis of the service-oriented paradigm ofnoospherogenesis,
transdisciplinary
approach,
ontological concept, the SPW, taking into accountpromising and informational technologies. The essentialfunction of this paradigm is fully defined and, in fact,
makes the methodological basis of modern scientificresearch as the basis for the development of civilization.
Noospherology, as noted above, is a complete body ofknowledge that ensures harmonic interaction in the“Man-Nature” system under the control of scientificthought and the will of man. It is organically linked withthe scientific and technological components of thedevelopment of civilization. The development of sciencehas moved from the stage of differentiation to the stageof integration, making it possible to implement the TD
concept of the development of science, which appeals to
SPW in the formulation and conducting of research andimplementation of complex research projects. Without it,a purposeful positive process of noospherogenesis isunthinkable. Here informatics fulfills its mission as a
backbone branch of knowledge. An ontological concept
has arisen in its depths, the essence of which consists inthe formal ontological description of subject regions and
SPW as a whole. Finally, modem information

The results of these studies were obtained during 2022
– 2024: Grant contract of the National Research
Foundation of Ukraine – “Development of the cloudbased platform for patient-centered telerehabilitation of
oncology patients with mathematical-related modeling”[17], [18], [19], application ID: 2021.01/0136 (2022–
2024, project is still in progress).
References
1.

Shyrokov V. Evolution as universal natural law(prolegomena to the future general evolution theory).
Bionics Intell 2017; 88:3–14.
2. Palagin O. Information technology tools forcontrolled evolution. Probl Control Inform 2021;
66:104–23.
3. Bostrom N. A History of Transhumanist Thought. J
Evol Technol 2005; 14:1–25.
4. PiagetJ.
L’Epistémologie
desRelationsInterdisciplinaires. In: Schwarz R, editor. Wiss. Als
Interdiszip. Probl. Teil 1, De Gruyter; 1974, p. 154–72.
5. Palagin O, Petrenko M. Methodological Foundations
for Development, Formation and IT-support ofTransdisciplinary Research. J Autom Inf Sci 2018;
50:1–17.
6. Petrenko M, Cohn E, Shchurov O, Malakhov K.
Ontology-Driven Computer Systems: Elementary
Senses in Domain Knowledge Processing. South Afr
Comput J 2023; 35: 127–44.
7. Jantsch E. Technological Planning and Social Futures.
London: Littlehampton Book Services Ltd; 1972.
8. Palagin O. Transdisciplinarity Problems and the Roleof Informatics. Cybern Syst Anal 2013; 49:643–51.
9. Kaverinsky V, Malakhov K. Natural LanguageDriven Dialogue Systems for Support in Physical
Medicine and Rehabilitation. South Afr Comput J
2023; 35:119–26.
10. Palagin, O. V., Kaverinskiy VV, Malakhov KS,
Petrenko MG. Fundamentals of the Integrated Use of

351

11.
12.

13.

14.

15.

16.
17.

18.

19.

Neural Network and Ontolinguistic Paradigms: A
Comprehensive Approach. Cybern Syst Anal 2024;
60:111–23.
Petrenko NG, Sofiyuk AA. On one approach to thetransfer of an information structures interpreter to
PLD-implementation. Upr Sist Mashiny 2003:48–57.
Malakhov K, Petrenko M, Cohn E. Developing an
ontology-based system for semantic processing of
scientific digital libraries. South Afr Comput J 2023;
35:19–36.
Palagin O, Petrenko M, Kryvyi S, Boyko M,
Malakhov K. Ontology-Driven Processing ofTransdisciplinary Domain Knowledge. Iowa State
University Digital Press; 2023.
Malakhov K, Velychko V, Palagin O, Prykhodniuk V.
A Guide to TISP: Hospital Information System for
Rehabilitation. Iowa State University Digital Press;
2022.
Palagin O. An Introduction to the Class of theTransdisciplinary Ontology-controled Research
Design Systems. Control Syst Comput 2016; 266:3–
11.
Kurgaev O, Palagin O. Concerning the information
support for research. Visnyk Natl Acad Sci Ukr 2015:
33–48.
Malakhov KS. Letter to the Editor – Update from
Ukraine: Development of the Cloud-based Platform
for Patient-centered Telerehabilitation of Oncology
Patients with Mathematical-related Modeling. Int J
Telerehabilitation 2023; 15: 1–3.
Malakhov KS. Insight into the Digital Health Systemof Ukraine (eHealth): Trends, Definitions, Standards,
and Legislative Revisions. Int J Telerehabilitation
2023; 15: 1–21.
Palagin O, Kaverinskiy V, Litvin A, Malakhov K.
OntoChatGPT Information System: Ontology-Driven
Structured Prompts for ChatGPT Meta-Learning. Int
J Comput 2023; 22: 170–83.

Authors Introduction
Dr. Mykola Petrenko
DSc (Doctor of Sciences in Technical
Sciences), PhD, Professor, leadresearcher in in Microprocessor
Technology Lab, Glushkov Institute ofCybernetics of the NAS of Ukraine.
Research interests: AI, Semantic Web;
Ontology
engineering;Transdisciplinary research.
Mr. Kyrylo Malakhov
MSc, Researcher, Backend developer,
DevOps engineer in Microprocessor
Technology Lab, Glushkov Institute ofCybernetics of the NAS of Ukraine.
Research interests: AI, Computational
linguistics; Ontology engineering;
Digitalhealth(Hybriderehabilitation). Member of the expert
subgroup on technical issues andarchitecture of telemedicine within theInterdepartmental Working Group for the development of
the concept of implementation of telemedicine in Ukraine.

352