Noospheric Way of Organizing Knowledge in the Knowledge Bases of
Innovate Importance
Yurii Pikalov
a
Department of International Economic and Business, Cherkassy State Technological University, Ukraine
Keywords: Knowledge, Signs, Economic Activity, Infosphere, Phylogenesis and Ontogenesis of Knowledge, Innovative
Activity, Noospheric Knowledge Map.
Abstract: A major part of the flow of new knowledge is knowledge about facts. Its value is inversely proportional to
the increasing amount. It can be enhanced by the way of conceptualization of knowledge, developing and
applying the innovative ways of its organization. It is suggested to use the way of organizing knowledge based
on the model of cognition of objects as spheres of phenomena; convergence of the sphere of natural and
conscious phenomena, models of phylogenesis (Paradigm Innovative Development) and ontogenesis
(Vertical Integration and Parabola of Knowledge) of knowledge as well as based on the paradigm of the
ontology of sign constructions. The above-listed tools have been obtained as a result of studies of M.V.
Polyakov’s scientific school, and they have been adapted by the author of the paper to develop architecture
of the knowledge bases functioning as a part of innovative systems of venture enterprises.
1 INTRODUCTION
Any conscious activity bears information nature. The
economy is not an exception. Information is an
ambiguous term. One of its meanings is measure of
the impact of message on its recipient. Besides,
information is synonym of message. Messages
consist of signs; therefore, we will speak of
fundamentally sign nature of conscious activity.
Signs are the form of existence of knowledge.
Knowledge can be old or new. It also can be genuine
or false. It depends on criteria of genuineness and is
determined in practice. Therefore, almost any
conscious activity is cognitive, even if the subject
does not strive to it. The subject either reinforces old
stereotypes, or gains new experience.
Cognition is inseparable from economy, whether
the subject wishes it or not. Although, in terms of
innovations, it can take place with zero result.
Depending on the object and phase of development,
cognition merges with economy or stands apart of it.
Similar points were raised by Friedrich August
von Hayek in his paper “Individualism and Economic
Order” (1958).
a
https://orcid.org/0000-0002-4968-965X
1.1 Some Related Work and
Relationship with Knowledge
Management Area
Many books and articles on knowledge management
begin with definitions of their essence (Nonaka and
Takeuchi, 1995), (Lundvall, 2007). The diversity of
various definitions of knowledge suggests that they
have failed so far. Most definitions concern not so
much with the essence, but with the origin, purpose
and application of knowledge. Such works as
“Ontology and knowledge economy” (Polyakov,
2015) may be an exception, because it concerns with
the ontology of knowledge that is reduced to the
ontology of signs. Such “knowledge about
knowledge” is necessary, first of all, to optimize the
structure of the denoting part of knowledge, called the
knowledge base. For innovation activity, it is much
more important to be able to recognize the knowledge
necessary and sufficient to solve the innovation task.
Traditionally, there are researches devoted to this
problem which are related to librarianship. The
results are well-known library classification systems
(UDC, educational standards, nomenclature of
subjects for which academic degrees are awarded,
etc.). However, they describe a well-established
250
Pikalov, Y.
Noospheric Way of Organizing Knowledge in the Knowledge Bases of Innovate Importance.
DOI: 10.5220/0008347302500257
In Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2019), pages 250-257
ISBN: 978-989-758-382-7
Copyright
c
2019 by SCITEPRESS Science and Technology Publications, Lda. All rights reserved
picture (more precisely, a map) of knowledge, and
today it is a stream of changes, especially in the
infosphere. Especially when it comes to computer
knowledge base, with its ability to update the
structure and content. This disadvantage is partly
compensated by the efforts of educational
organizations, virtual research networks, organizers
of scientific communications, publishing houses of
specialized literature, etc., institutes, such as
INSTICC, Common Ground, Global Science and
Technology Forum (GSTF) and others. They react to
the facts of changes in science and technology
promptly, but the reactions do not always coincide
and do not always fit into the traditional framework.
It takes time to comprehend and systematize them.
It is worth mentioning researches of
S.Ranganathan (1957) or Karin Karlics (2013).
However, in terms of the connection with ontology
and coverage of the variety of objects and aspects of
knowledge in their relations in this research, we
focused on the works of M.V. Polyakov and his co-
authors (Polyakov, 2017; 2018).
The originality of our research lies primarily in its
conceptual character. It consists in a completely non-
obvious interpretation of the results of the
development of the noospheric approach to cognition
and its transfer to the problem of knowledge, its
essence and properties, with application to the
development of Knowledge Bases that are part of
innovative systems.
1.2 Structure of the Paper
Section 2 discusses the basic concepts and includes:
General requirements to Knowledge Bases; Object
structure of cognition process and knowledge;
Genesis of cognition and economy in the spheres of
phenomena, Vertical integrated units of knowledge
and their genesis.
Section 3 (Outcomes) discusses the concepts of
Knowledge maps and Noospheric knowledge map, as
well as multimaps, which underlie noospheric
knowledge bases. Section 4 is Conlusions.
2 BASIC CONCEPTS
Knowledge, which is the result of activity of such
fields as semantic technologies (Berners-Lee, 2001),
organizational semiotics (Stamper, 2000), ERP-
systems, theory and practice of business processes
(Scheer, 1999), differs drastically from natural-
science and humanitarian knowledge by content as
well as by methods of obtaining and application.
This knowledge is related to infosphere, but relies
on computers, representing the implemented
knowledge of physical phenomena. As a rule, it is
obtained by young people, often by students within
small enterprises or informal groups. These structures
have a chance (not always high one) to become
successful startups. The above-mentioned people do
not have theoretical background in the field of
infosphere, as well-recognized theories just do not
exist there, and it is not even sure whether they could
exist. At the current stage, for the whole period of its
development, infosphere demonstrates maximum
degree of integration of cognition and economy. Here
it is, in fact, two sides of the same coin. The same high
degree of unawareness of what is going on should be
noted, which is quite natural for pre-paradigm phase
of development. This is particularly evidenced by the
words of Grady Booch, who has acknowledged that
“many years will pass and OOAD will become as
usual as motherhood or apple pie, but no one will be
able to explain what the Object Oriented Analysis and
Design is” (Booch, 2004).
Having formulated the productivity paradox of IT
in economy and business, Robert Solow actually
pointed the signs of technological and financial
bubble in the sphere of IT application in the global
economy (Solow, 1987). A discussion took place in
the scientific world, which, in our opinion, was not
able to resolve the paradox, having maintained the
status quo.
Kris Freeman and Carlota Perez have found the
emergence of these bubbles at the stage of adaptation
of innovate technologies to social and economic
environment to be regularly recurring pattern
(Freeman, 1982, Perez, 2011).
All innovations, which have taken place in the
infosphere until today – are based on pure heuristics,
experience (analogy, association) or modelling, when
the abstraction of the deeper level is applied to
simplify the existing practices. This series continues
in future in the form of such trends as Big Data and
Artificial Intelligence.
It is interesting that Peter Druker spoke of the
failure of IT to become a tool for management of
economy and business, like of something very
obvious: “…all of us nonconformists agreed on one
thing: The computer would, in short order,
revolutionize the work of top management. We could
not have been more wrong. The revolutionary
impacts so far have been where none of us then
anticipated them: on operations.” (Drucker, 2001).
One more thing: “But they did not, as a rule,
realize that what was needed was not more data, more
technology, more speed. What was needed was to
Noospheric Way of Organizing Knowledge in the Knowledge Bases of Innovate Importance
251
define information; what was needed was new
concepts.(Drucker, 2001).
In our opinion, quasi-physical approach to
conscious phenomena, and products created on this
basis, in particular, knowledge bases, are of obvious
interest in this respect.
2.1 General Requirements to
Knowledge Bases
Knowledge, indeed, is diversified, and its
development requires different innovative systems
and methods for innovative management.
In this study, the knowledge, accumulated in the
knowledge base, serves as the major resource for
creation of innovative products, including description
and the process of creation of the products
themselves. However, there is also an inverse
relationship. The experience in empirically heuristic
cognition, being a result of economy, as well as the
experience in application of scientific findings in
economy, is a resource for development of paradigm
and post-paradigm (scientific) cognition.
It is obvious that a skilled carpenter or joiner is
obliged to excel in woodwork, metalworker – in
metalwork, etc. Accordingly, an individual or
collective Subject of Innovative Activity (SIA) at the
enterprise has to know the ropes of knowledge.
Unlike the specialist or teacher, who works in a
narrow sphere, he needs to be able to deal with
an ample sphere of diverse knowledge. In order to be
well-versed in a rapid stream of knowledge, it is
necessary, first of all, to have an idea of architecture
(in other words, structure) of the whole wide range of
knowledge, accumulated by mankind and being
relevant at the current state of cognition. It is critical
to understand what is the state and trends in the
development of knowledge system.
We can implement rational investment policy,
build ideal innovate system, but what will be the
benefit if, due to unawareness of what is going on, the
goals and trends in the development turn to be risky,
or even false and needless? In order to diminish these
risks, Noospheric knowledge base should be not just
a topogram, but also a sort of “roadmap” of the
innovative development of infosphere. Dynamic
properties of the models of PIDev and parabola of
knowledge provide this opportunity.
2.2 Object Structure of Knowledge and
Cognition Process
According to Noospheric thinking of
V.I. Vernadsky, the world as an object of cognition
(the signified part of sign) is divided into the spheres
of phenomena, as follows: a) physical –
physiosphere; b) biological– biosphere; c) conscious
– noosphere.
Figure 2.1 shows the relationship between
physiosphere, biosphere and noosphere within the
universal sphere of phenomena.
Figure 2.1: Object structure of knowledge.
Concentric circles symbolize the levels of
abstraction, from zero (practical knowledge which
can be implemented in bodies or be imitating the
activity) to philosophy and methodology (depth 5).
A complete circle corresponds to noosphere,
segment 240’ – to biosphere, and 120’ – to
physiosphere. Each sphere of phenomena has a
corresponding vertical and parabola of knowledge.
The object and subject structure of physiosphere
and biosphere has been fundamentally developed
within several centuries after scientific revolution of
the 18
th
century. Scientific cognition of noosphere is
at the beginning of its path. In the framework of the
noosphere, we are, primarily, interested in the
infosphere and economic sphere. Figure 2.2 shows
their relationship.
Truncated cone symbolizes the infosphere. As far
as information is an ambiguous term, denoting
messages as well as the extent of their impact on the
recipient, it is more preferable to use the term “sphere
of sign phenomena”.
The discovery of physiosphere (starting from
geosphere) as well as biosphere and noosphere,
scientific revolution in the information sphere,
approaching owing to a wide use of data processing
technologies being physical by their nature, have
caused cessation of the traditional structure of
scientific knowledge to correspond to the goals and
objectives of further innovative development.
Thus, according to interpretation of Vernadsky’s
teaching, provided by M.V. Polyakov jointly with
coauthors (Polyakov et al., 2018), the object of
KMIS 2019 - 11th International Conference on Knowledge Management and Information Systems
252
integral cognitive and economic activity is the sphere
of phenomena. The cognition of phenomena is
concluded by implementation of its results in bodies
and processes, needed by people (artefacts – artificial
phenomena). As Niels Bohr said, “the objective of
science is to make something incomprehensible to
become trivial.”
Figure 2.2: Object structure of knowledge. Noosphere.
In order to handle the arrays of phenomena, they
have to be simplified. Vernadsky, in particular,
suggested breaking down the array of world
phenomena into the series of above-stated spheres,
each with a certain entity (physical bodies, living
organisms, sign bodies) behind phenomena. The
phenomena, related to different sphered, are closely
interrelated between each other, and in each of the
artefacts, as a rule, knowledge about more than one
kind of phenomena is closely intertwined between
each other.
Therefore, if it is an innovative enterprise and its
mission is “To cognize and manage!”, the object of
innovative activity and the respective knowledge base
shall correspond to the structure, described above.
2.3 Genesis of Cognition and Economic
in the Spheres of Phenomena
A human cognizes the essence of phenomena and
implements it in the artefacts. The outcomes are
represented by knowledge in sign and embodied form
(artefacts). At the same time, the economic is
inseparable from cognition. Theoretically, cognition
can be suspended, but then the economic will cease to
develop and start degrading. Actually, the economic
is also the cognition. Their living connection can be
broken due to specialization and alienation. This
leads to breakaway of cognition from production, and
the latter – from creativity.
Similar assumptions were made by many of
outstanding thinkers, among which are Ferdinand de
Saussure (2017), Friedrich August von Hayek (1958).
Wide application of information technology in the
sphere of conscious phenomena enabled Bertin
Martens (2004) to compare the economy with an
information machine for production of knowledge,
including their embodied form, and Peter Brödner
(2005) compared the organization with a computer
program. The process of cognition is spread over
time, and in diverse time segments, it behaves
differently. Accordingly, it requires a diachronic, in
other words, historical approach.
Polyakov’s work shows an example of the
application of diachronic model of Paradigm
Innovative Development (PIDev) of cognition and
economy (Polyakov et al., 2017).
Being a single whole, every sphere, driven by
innovations, undergoes a number of phases in its
development, as follows: 1) empirically heuristic
(before paradigm); 2) paradigm; 3) scientific (post-
paradigm).
The objects of changes are represented by the
innovative products, i.e. knowledge in symbolical or
embodied form.
Computers emerged as physical technology of
data processing. At that time, the infosphere was and
it is now in the empirical and heuristic phase of
development. It means that innovations take place
there at the level of practices (zero depth), do not
affecting the level of constructions and technologies,
not to mention the deeper levels of abstraction.
Computers have accelerated the development of
infosphere, thereby exposing the problems, and
approached the transfer to paradigm phase.
As far as the spheres of phenomena have
multilayer structure, there can be relict layers, along
with the advanced ones. For instance, physics of
a solid body, liquids and gases, optics, atomic and
quantum physics and other branches of physics
developed asynchronously. Nevertheless, multiple
principal tenets combined them into the physiosphere.
By analogy with Darwin's theory of evolution, we
can say that PIDev model, which determines
historical development of the whole sphere of
phenomena, is phylogenesis. In this case, innovations
act as analogues of specific bodies, and innovative
cycles within the framework of parabolas can be
considered ontogenesis.
Macrogenetic or phylogenetic characteristic of
knowledge stems from PIDev model.
2.4 Structural Units of Knowledge and
Their Genesis
It is difficult for an individual human to acquire
knowledge of all phenomena at once, even in the
amount of a single sphere, and even more so for the
Noospheric Way of Organizing Knowledge in the Knowledge Bases of Innovate Importance
253
universal scale. That is why we have to fragment
knowledge.
Although, it is only holistic and completed
knowledge that can be quite understandable and,
therefore, productive and constructive. Figure 2.3
shows decomposition, and, respectively, integration
of knowledge about a particular sphere of phenomena
(or its parts) “vertically” (by levels of abstraction).
Figure 2.3: Ontogenesis of knowledge (Polyakov et al.,
2017).
The right branch of the parabola describes rising
from the abstract and simple (paradigm) to the
concrete and complex (practice). The abstract
corresponds to the set, and the concrete – to the
individual. In case of rising, every level of abstraction
(depth of innovation) also denotes a step. When the
steps are skipped during immersion and rising, it
means that the method of modelling is applied. For
example, we can see a certain and poorly
understandable correspondence between practical
results and mathematical apparatus.
Further, lacking full understanding, we can risk
applying this apparatus for improvement and
regularization of practical results. At the same time,
the obtained model will require subjective
interpretation, results of which, with a certain
probability, can be useful, useless or even harmful.
The application of abstractions of the high level to
practical results, bypassing the steps of the vertical of
knowledge, is called the modelling of conscious
phenomena (Fig. 2.4).
The term “modelling”, similarly to many other
terms in the sphere of conscious phenomena, got the
meaning, different from the traditional one. In the
sphere of natural phenomena, it means simplification
of real-life understandable object, while in the sphere
of conscious phenomena it is a hypothetical
understanding of still not understandable phenomena
and their effects.
Figure 2.4: Modelling of conscious phenomena.
The parabola of knowledge determines the
structure of knowledge units as well as their place and
role in the innovative processes. These properties
should find reflection in the structure of the
knowledge base being developed.
Therefore, this paper formulates a methodological
and theoretical background for development of the
architecture of knowledge bases, focused on
identifying, setting and addressing the crucial
innovative challenges in the sphere of conscious
phenomena, first of all related to information and
economy. It also serves as a methodological basis for
analysis of the existing solutions in the field of
knowledge organization in the form of knowledge
base as well as for evaluation of an impact of the
created knowledge base on the economic efficiency
of enterprise’s performance.
3 OUTCOMES
3.1 Knowledge Maps
It is convenient to use the term “Knowledge Map”
(KM) to denote graphical or text representation of the
architecture of knowledge. Its synonyms can be
represented by “topography (topogramma) of
knowledge” (ToK).
The genesis of knowledge is represented by
PIDev and VIK motels. PIDev reflects the
development of the sphere of phenomena, being not
differentiated by innovative products or levels of
abstraction, and, by analogy with biology, it can be
called as phylogenesis of knowledge. Knowledge
maps, PIDev and VIK models are not only mandatory
tools for innovations. It is also the means for
development of the innovators’ holistic world view,
being one of the most critical factors which have
impact on productivity of innovative activity.
The knowledge map should expose the real
significance and trends in development of cognition
KMIS 2019 - 11th International Conference on Knowledge Management and Information Systems
254
and economy, confirming or denying the
appropriateness of the existing trends, or facilitating
the emergence of the new ones.
3.2 Noospheric Knowledge Map
Knowledge base, the concept of which is a practical
outcome of this study, is called noospheric.
Noospheric Knowledge Map (NKM) has a
leading role among the knowledge maps, being a part
of the multimap. Every Structural Unit of Knowledge
– SUK (text, audio, video, and hypertext) should be
characterized by a number of properties, determined
by the acknowledgement of the fact of noosphere as
an objective reality. Table 1 shows the specification
of noospheric properties of NKM and the values
taken by them.
Imposition of the vertical of knowledge on the
infosphere demonstrates the vacancy of the key box,
corresponding to fundamental (ontological) theory of
information (to be more precise, sign) phenomena.
This gap does not allow developing the applied
theories and technologies. It enforces resorting to
modelling, which, in terms of the parabola of
knowledge, looks like the attempts to jump from the
deep philosophical (ontology, object, universal sign)
and mathematical abstractions over the levels of
fundamental and applied theories as well as
technologies to practices. As practice shows, in such
cases, a risk of falling considerably exceeds a
probability of success.
NKM does not assume that we should not deal
with the empirical and heuristic innovations or use
modelling for this purpose. It emphasizes the
necessity in these cases to carefully consider the risks
and use emerging opportunities for paradigm
innovations, which, addressing business challenges,
simultaneously build a ladder for scientifically
grounded innovations, characterized by law
probabilities of continuously recurrent success.
3.3 Application Area and Multimaps of
Knowledge
The noospheric knowledge base is the most important
component of the innovation systems of enterprises,
primarily those that create IT, wherein the noospheric
map should ensure the divergence of knowledge in
relation to the kind of phenomena and the phases of
phylogenesis and ontogenesis of knowledge, as well
as methods of immersion and ascent between
concrete and abstract, using the VIK. The noosphere
map ensures the convergence of knowledge relating
to different areas of phenomena and levels of
abstraction. Distinguishing the phases of the
phylogenesis of knowledge used as an innovation
resource, it allows you to select the mode of the
innovation system corresponding to the pre-
paradigm, post-paradigm or paradigm state of the
VIK used in solving a specific innovation task.
However, initial knowledge can enter the
noospheric base as element of different structures
(“maps”) of knowledge that do not fit with the
noospheric structure. Their names, annotations and
content may differ from the noospheric knowledge
map. Therefore, the noospheric knowledge base
provides the possibility of indexing knowledge
fragments according to several “knowledge maps”,
whatever they are called.
Table 1: Noospheric properties in NKM.
Name of SUK property Property value Remarks
1. Sphere of phenomena Physiosphere, biosphere, noosphere
«Spheric» approach,
V. I. Vernadskyi
2. Layer of phenomena
To be determined upon necessity. Unlimited number of layers and
levels. For example, infosphere (semiosphere, sign sphere),
econosphere, etc.
Layer is a part of
sphere of phenomena
and the higher laye
r
3. Innovation (product, process,
service)
Sequence number of product
Product is a part of
sphere or layer of
phenomena
4. Phase of development (cognition)
of the sphere of phenomena
Pre-paradigm, paradigm, post-paradigm (scientific) See PIDev model
5. Level of abstraction
Practice, technologies and constructions, applied theories, fundamental
theory, mathematics, methodology, philosophy
See VIK model
6. Method of cognition (knowledge
gaining)
Heuristics (assumptions). Empirics (experience, analogies). Immersion
from the concrete to the abstract, rising from the abstract to the
concrete. Modelling
See parabola of
knowledge
7. Depth of innovation
Levels: practices, technologies, applied theories, fundamental theory,
mathematics, methodology, philosophy
See VIK model
8. Modality
Problem (left branch of parabola of knowledge), solution (right branch
of parabola of knowledge)
See parabola of
knowledge
Noospheric Way of Organizing Knowledge in the Knowledge Bases of Innovate Importance
255
The users-participants of innovation processes
determine these “knowledge maps”, wherein the
noospheric map performs not only the described
special functions of divergence-convergence of
knowledge, but also serves as a “common
denominator” for many other maps.
4 CONCLUSIONS
This paper suggests the idea of conceptualizing the
knowledge, accumulated in computerized knowledge
base and used in the process of production.
At the present time, historically developed system
of knowledge with its division into natural and
humanitarian knowledge is intensively diffused by
the flows of heterogeneous knowledge about
individual artefacts.
Every flow has a corresponding division of
knowledge into subjects – the knowledge map. Still it
is not possible to tell what of the maps is more
adequate to the reality. Information and software
apparatus of the knowledge base should provide a
user with an opportunity to work with a multitude of
knowledge maps, giving preference to one or another,
i.e., to work with the multimap.
At the same time, we need a special knowledge
map, guiding the innovator in space of knowledge,
warning him of risky challenges and prioritizing him
in the direction where the vertical of knowledge is
filled with content or near to be filled, and, therefore,
the paradigm innovations are highly probable.
In order to manage such knowledge base, we
should use a flexible metadata base, built on the
grounds of noospheric concept (PIDev model, VIK
and parabola of knowledge). Moreover, to develop a
flexible infrastructure of data, we should use the
knowledge about sign constructions, gained as a
result of paradigm innovation.
This article defines the general architecture and
semantics of the noospheric innovation knowledge
base, which defines the semantic structure
(architecture) of its designating part (syntax). It
describes the architecture of the object (array of
knowledge). In the process of creating a knowledge
base, it is necessary to develop its pragmatics and,
accordingly, a pragmatic syntax which describes the
processes of processing (selection, input, structuring,
remembering, searching, assembling, displaying,
etc.) of data. In addition, it is necessary to determine
the structure of the syntactic syntax that reflects the
state of the object, to develop and implement the
organizational and software of the noospheric
knowledge base as an important component of the
enterprise innovation system.
ACKNOWLEDGEMENTS
The authors are thankful to Yuliya Davydova for her
significant assistance with the translation of the paper
into English.
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