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Well-known problem "scientific picture of the world", which means the absence of the integral, universal, and formalized methodology to describe knowledge, remains one of the key problems in interdisciplinary research. What we mean is kind of methodology, which is able to integrate different domains and features of human knowledge (scientific disciplines, cognitive lines, hypothesis, intuitive prerequisites) into common meta-model of knowledge. Theoretical study of such model and its usage as a tool for practical analysis could present the most precise, even parameterized, answers to interdisciplinary question. Nowadays, and apparently in the nearest future, interdisciplinary research at the turn of various areas of knowledge is in line of experts and groups presenting their resumes mostly in verbal, interpretive form (independently from visual, virtual, and stand modeling, or natural studies). It becomes especially noticeable in philosophic and social aspects of research.

There is another distinction of the social aspects of interdisciplinary investigations. Crisis is time for them to be of the first magnitude. When environment (social, economic, situational, psychological etc.) is steady and demonstrates stable regularity of its state and trend, both optimization solutions and parametrical prognostication became urgent. In this conditions detailed elaboration and particular specialty (in research, in modeling, in activity etc.) can provide maximum effectiveness from interaction with such environment. Irrespectively to variety and character crisis always means disturbance of engrained (revealed or set) patterns, rules and expectations. In high suddenness and vagueness something else becomes urgent – it is the skills to choose right strategy orientation, the ability to keep selected guiding line in situational chaos, the ability to recognize trends in the chaos, completeness and priority of active factors, their systematization, revelation of forming patterns, high level of adaptability, mobility, stability, availability of autonomy and resort reserve of solidity. From system-defined analytic point what the crisis demands is not excellent skills in one model but the ability to switch rapidly from one model to another selecting in advance the most appropriate one in the existing situation. This specificity is compatible with non-parametric, destiny-free, analogical and associative elaboration way of interdisciplinary analysis. Same way of elaboration is called for and rated highly in long-run forecast, in perspective and strategic research (long-run perspective is always uncertain).

Human civilization nowadays needs immediate and simultaneous solutions for many accumulated problems – ecological, political, economic, social, scientific, philosophic, ethical etc. At that the broader is certain nation's level of influence (or that of other social formation) the more urgent is the need for complex interdisciplinary analysis of prospects, tendencies and control of changes. It seems that interdisciplinary research domain should develop like avalanche. However the mentioned methodological crisis blocks the way of its development.

Certain hopes in decision of this crisis are pinned on development of systemology and system analysis – scientific school formed in the first half of XX century owing to the works of  A. Bogdanov ("Tectology", 1920) [1, 2] and Bertalanffy L., von. ("General System Theory", 1937) [3, 4]. Since then the interest to the meta-scientific (overdisciplinary) approach never calms down  [5, 6, 7]. Moreover, the theory of systemology improves and provides new tool for its formalization (for example "The language of ternary description", 1978, Prof. Avenir Uyemov – [8, 9]). Some versions of general system theory were proposed, and their level of development meets the requirements of philosophy generalization (system methodologies of third generation) – "The Theory of hypercomplex dynamic systems (THDS)", 1989,  Prof. Alexander Maliuta [10]. The most formalized sections of general system theory have transformed into separate studies (cybernetics, theory of management, etc.) and found broad practical use. More late versions of systemology, THDS [10] for example, do not use methodological tooling borrowed from other disciplines (mathematic instrument, theory of graphs, graphic-analytical stereotype, etc.), but operate by their own tools developed and associated with systemological axiomatics.

Thanks to that the possibility to put to methodological systematization and analysis the domains that can hardly be formalized shows up, in particular the domain of variety of social trends and factor mostly interdisciplinary by nature. However applied aspects of THDS form separate methodological problem where all of the highlighted interdisciplinary specifics and problems have been focused. And we are going to take up this very problem in more details.

 

Consideration of axiomatics, principles, or ontological potential of THDS is not the task of this article. You can learn about this from separate monographs such as [11]. In spite of high level of abstraction in THDS's methodological terms familiarization with it is like studying any other science. However what makes necessary to use epistemological filling (formalization, description in general terms) of the domain of the subject of inquiry on initial level of study is thickness of abstraction. Practical tasks' solutions demand additional adaptation of well-known professional techniques to operate formalities of the problem domain. Therefore, very often narrow specialist of a particular problem domain could decide that meta-abstraction (up to the level of THDS's categories) is pointless. However when solving the tasks of interdisciplinary analysis it is very important to find general (normalization) categories in the problem domains (disciplines) under consideration. By definition THDS as any other well developed system methodology is not just normalization category but normalization methodology. This means that normalization categories if found correctly shall naturally blend with THDS's terms. Moreover, if the THDS's terms and categories have been interpreted in philosophy sense, well-performed local task of interdisciplinary normalization is able to demonstrate a larger analogical analytic potential than utilitarian target setting demands.

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The mentioned properties can be demonstrated by extract of interdisciplinary analysis. For example, studying social aspects of general and broad application of IT. Similar to the case of detailed consideration of THDS's or similar methodology, conducting integral analysis of the social trends, which ride broad application of IT, is not the task of this article. This subject makes separate and extensive studies. But even demonstration of one fragmentary approach to solution of this particular task can become unexpectedly helpful if analyzed in the context of system methodology.

In engineering context of IT it is about hardware, software, data, digital communication. In social aspect it's about how wide application of IT tools influences social relations, mass psychology, creativity, development trends, prospects etc. In philosophic aspect it is about IT influence on human consciousness, on stereotype of reality perception, on estimation criteria, on ideology and world outlook, on vision of the future. Twist of the current moment is that IT is classified as innovation technology, a type of technology that introduces and stimulates changes (what means it provokes crisis). Moreover, IT is innovation product – the result of innovation process. Most of the IT solutions demand active or passive participation of men.

By the way even the listed characteristics of IT are enough to draw attention on some important peculiarities of IT. In particular, even being innovation technology IT makes difference in existing regularities of socio-economic relations. At that IT is the kind of improvement and optimizing technology with its effect beyond the category of used economic and mathematical models. It operates with information and the most of IT-products are aimed at interaction with human mind as this very component part of human nature operates with information. The origin of some economic effect is presumed by means of this interaction. But there is a hidden trick in here. From the very beginning economic benefits gave reasons for expediency of wide application of IT. But we should take into consideration that economics is a discipline, which has formalized mathematically a particular category of existing social relations. Direct influence of IT-products on human mind inevitably leads to inductive change of mind beginning from subconscious changes in mentality and to changes in world outlook. Under such conditions social transformations become unavoidable, as much as inevitability of these changes' influence on economic part of social relations. The signs of all that is aggravated problems around intellectual property in "digital world", or problems of civil freedom and privacy etc. Who can answer how seriously effectiveness of IT-innovations can be measured by operation factors of economic model, which starts transforming if these innovations are widely introduced.

Despite of the fact that IT-revolution has reached the age of twenty years, in spite of huge situational experience (both positive and negative) the effectiveness of IT-innovations is still the subject of wide speculation. Hitherto the patterns and character of macroeconomic influence of IT were not identified. Moreover, the sector of "new economy" remains in epicenter of economic disputes. This problem still needs to be scrutinized thoroughly.

Socio-economic influence of IT is an interdisciplinary problem. And only interdisciplinary approach is able to return to it the only important normalization element without which the analytic problem of expediency, benefit, and harm of IT can't be solved (except for cut-and-try method). This element is a man, or rather his(her) abilities and creativity, which are inseparably linked with his(her) activity and social behavior.

Figure 1. "Elementary innovation (creativity) cycle" presents basic steps of innovation development. This diagram has off-center structure – as normalization elements in this case we have chosen three factors (directories) that forms creativity: volitional, empirical, and heuristic elements. These factors were brought into correlation with three-dimensional co-ordinates. In chosen co-ordinates we have projected the prototype process – elementary innovation cycle. Elements of diagram data are interpreted in diagram's legend. Example of "Elementary innovation cycle" allows following all the above-mentioned peculiarities of interdisciplinary analysis both in the context of the subject of inquiry (social aspects of IT) and in the context of methodological value of diagram itself.

 

IT-innovation as well as any other originates from cumulative experience and its results, creative idea which brings novelty, and application of series of successive efforts. In the domain of IT-engineering innovation evolutionism (the succession of innovation cycles) is well perceptive. For instance, in evolution of microelectronics and especially in development of generations of language tools and methods for programming (such one from Assembler to Object-oriented programming and UML). Only if innovation is embodied in full product with clear benefits, which can be used as an element (base) for the next innovation turn, it can be called accomplished and real.

The following comments and conclusions are appropriate in connection with graphic-analytical associations of diagram:

★       Queue of "coupling" of vectors (the succession of steps) conforms to generally accepted concept of creativity but it is still relative.

★       Internal benefits of innovation (inputs made by the originators, idealized) are formed and laid during the first three steps (vectors 1, 2 and 3). This is the stage of innovation forming. Creation of innovation prototype makes its result.

★       Final benefits of innovation are formed during the last three steps (vectors 4, 5 and 6) of innovation. This last stage is an integration of innovation into environment, its perception by the environment and its benefits by specific characters of the environment.

★       During its first stage the innovation is under integrated control of its creators. During the second (last) stage the innovation is under control of its users and characteristics of the environment.  In the end of the second stage the innovation exists not in the form of "new flashy thing" (as its creators usually imaging) but it the form functioning technological product (tool) "in hands" of its end-users. At that real benefit of this product under provided conditions is already determined, tested, and there is formed a certain conception of the innovation as a tool with particular benefits. Together this makes full cycle of innovation's realization – "elementary innovation cycle". If we say real benefit from new military tank will be determined not by the results of ground test but by estimate given by the tank crew and army headquarters after participation in military mission.

★       Only if two conditions are being simultaneously observed the innovation can become a solid foundation for the next innovation turn (i.e. to be a solid base for the next innovation building on). The first – basic technologies have passed the whole "elementary innovation cycle" and all the revealed and approved features should be taken into consideration. The second – the character and behavior of the environment during the next innovation turn remain immutable.

★       The difference between vectors I and L illustrates how much can differ ideal benefit from innovation (imagined by its creators) from its real benefit. The key idea is that these two types of benefit cannot be identical (vectors I and L are always different!).

★       There is a real danger of that due to different reasons (casual or intentional) substitution of innovation's benefits (L) can occur, in most cases with vector I. The problem becomes more complicated if the last stage of innovation (vectors 4, 5 and 6) is not symmetrical by its character (i.e. it doesn't have an organizational center to consolidate and popularize experience unlike in the first stage). During commercial spinup (most of the products go on the market on the step of vector 6) of the products commercial advertising and marketing also become an aggravating factor. In most cases advertising campaign is not only oriented to idealize benefits of innovation (I) but also to exaggerate it.

★       In most cases the difference between I and L is a interdisciplinary correction. The more narrow specialists are the creators of innovation and the more social influence can the innovation show, the more difference between vectors I and L will be.

Associative situation analysis of the diagram can be continued. However in the current context we will not go beyond one more comment. Even though detailed purposeful investigation of the whole spectrum in IT area with the use of the methods under review was never carried out, proximate analysis of some trends draws attention to itself. There are lots of grounds to claim that for the most of IT-technologies (this number is big enough to be critical) today their innovation cycle is not finished. However these technologies already lay the foundation of new generation of innovations.  At that the next generation of innovations has purposeful social character. Moreover crisis trends complicate the situation what adds one more reason to realize the necessity of serious and pragmatical study of social aspects of IT.

At least the diagram "Elementary innovation cycle" can be useful illustration to the subjects of strict examination of organizational and structural topology of innovation (creative) activity. By the way more abstract approach (as it was mentioned before) will reveal the presence of considerable methodological potential.

 

If we analyze the diagram more thoroughly the necessity to parameterize its categories will arise. For instance in order to answer the question what is the length of each unit vector and in what units are they measured. (Currently the length ratio of unit vectors if defined by means of associative expert valuation). In the meantime units are related to concrete definition (parameterization) of such concepts as "level of novelty", "capitalization of experience ", "intensity of realization", etc. Listed categories represent some analogous functions, which are not formalized in terms of mathematics but presence of which were ascertained empirically and even some of their patterns were revealed.

We all know from our life experience that the result (effectiveness) of application of volitional energies (volitional element) has nonlinear nature. In particular, the effectiveness of energies goes down after it reaches some threshold quantity irrespective to their further reinforcement. Does this threshold originate stochastically or functionally? Evidently clarification of this functionality can present the idea of optimal resources consumption in innovation process. Traditional methodological (mathematics, statistics) approach is hypercomplex and problematic in this case. Meanwhile unexpectedly we can find partial (but available) solution for this problem in methods of general system theory, and THDS [10] in particular.

By adding several successive cycles to our diagram we receive a transformation chain of "real benefit" (vector I after each successive innovation cycle) because of connected succession of innovations. If we add the term "trajectory" to the context involved we can't avoid concomitant questions about optimal and nonoptimal trajectories, about criteria of optimal depletion, about the "figure" ("surface"), what number of possible trajectories is able to form it in considered co-ordinates.

Volitional, empirical and heuristic elements are present in creative activity of people in any area and under any circumstances, no matter in favorable socio-economic climate or in crisis period they act. What does change is structurally morphological nature of the most elementary innovation cycle (the one determinating the direction of vector I in space of co-ordinates). From the other side any innovation cycle is just a "corpuscular" transaction in the system of social relations in any sphere. Consequently, innovation cycle conditioned by general systemological rules.

If we leave system methodology upon the concept of innovation cycle diagram we will receive a diagram of a higher order. For this new diagram an elementary innovation cycle will be a detail about strategy of moving from one point of the diagram to another – "movement". Graphic-analytical idea of systemological philosophy forms "surface geometry" where the "movement" takes place. A point on this "surface" corresponds with a level of complexity of system realization. The "movement" is a passage from one point of system realization to another. Innovation cycle is an ontological basis of such passage. Since "surface geometry" constitutes of a number of various states of system realization, deliberate "movement" on the "surface" in some directions represents nothing but realization of different strategies. The described logic allows making a "Diagram of Strategy Space".

This article is too small to allow us to study the structure and scope of "Diagram of Strategy Space" in details. However by describing its general logic and forming principles we have reaches the purpose of this article – to present an example and foundations of analytic approach to solutions for interdisciplinary problems (in our case in the field of social aspects of IT).  And we have used systemological methodology as a tooling, THDS [10] in particular.

The presented approach was adopted for solving practical problems – for independent analysis of crisis tendencies of IT in national economy of Ukraine and in working out the concept of its development [12]. In this document [12] you can find graded version of "Diagram of Strategy Space" and its analytic interpretation.

 

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