This book is devoted to science. Nowadays, science is the major component of the national innovation system in the part of knowledge creation and this branch of activity involves a lot of people all over the world. This book tries to provide a systemic view of the managing science. The phenomenon of science is considered broadly and the consideration includes social, economical, philosophical, methodological and other aspects of the scientific activity. The author provides historical examples, reasoning and description of science organization and provides a complete model of science chapter by chapter.
The book acquaints the reader with science versatility by means of a historical overview of Rutherford’s experimentations around their discovery of a new atomic structure.
The author takes this example as a starting ground to extract methodological difficulties of building an empirically-grounded theory and guides the reader further to inductive, deductive and logical thinking. The author demonstrates the roles of scientific paradigm and ontology in both experiments and subsequent construction of theory.
The Rutherford’s Experiments provide a great learning ground for research structure organization and two major aspects of research management. Firstly, Rutherford needed a team to carry out a research. The team worked under supervision of Rutherford and carried out a research by applying research methodology – i.e. the algorithm for knowledge creation. The methodology determines features of knowledge objectivity, reliability, and validity while organization of a research team provides for the correct implementation. The author defines the first aspect of research management as the interaction between method and organization of research. Secondly, Rutherford’s experiment required funding for equipment and salary for team members. The author defines the second aspect of research management as the interaction between the macro-level of science funding and the micro-level of science performance (p.1).
The basis for the book is the author’s representation of the scientific activity and vision of scientific activity components. The author provides a representation of the scientific activity as a combination of two pairs of characteristics: (philosophy, organization) and (processes of knowledge, state of knowledge). Philosophy underlies science and determines which is method of knowledge creation is scientific, how people could know the nature (epistemology) and what people already know about the nature (ontology). The organization level determines dynamic processes of science administration and research activity, while static existing knowledge about nature is applied in the form of technology.
The first, scientific, activity addresses questions about the structure of the nature (what is the nature?) and provides a current scientific content (ontology) in the form of a set of ideas (representations) about the nature. Philosophy underlies science and determines which method of knowledge creation is scientific as well as determines knowledge processes of the nature (how we know the nature?). As mentioned earlier, the scientific activity has another aspect – organizational.
The book acquaints the reader with the philosophy of science and considers the impact of individual and philosophical schools on the development of scientific methods. Instead of providing a popular historical overview of contradiction of empiricists vs rationalists, the author concentrates on the component of ideas of the empirically-grounded theory (p.22):
A scientific model that could be verified by observation (Copernicus)
Precise instrumental observation to verify the model (Brahe)
Theoretical analysis of experimental data (Kepler)
Scientific laws generalized from experiments (Galileo)
Mathematics to quantitatively express theoretical ideas (Descartes and Newton)
Theoretical derivation of an experimentally verifiable model (Newton)
The author pays great attention to the school of “logical positivism” of the Vienna Circle. The main position of that school is that observation is the starting point for all knowledge. Hence, the scientific theory is logically inducted from experiments. The first position is directed against the metaphysics in science. The author disagrees that the scientific theory construction is simple and necessarily made only by experimental induction.
The heart of the scientific method is the grounding theory construction based upon experimental data (p.30), i.e. construction and validation theory based upon empirical results. The distinctive approach to science is called the empirically-grounded theory. The critical component parts of the scientific method are as follows:
Observation and experimentation
Instrumentation and instrumental techniques
Theoretical analysis and model building
Theory construction and validation
Paradigm development and integration
The Author’s point of view about the empirically-grounded theory includes several ideas. Firstly, the process of scientific inquiry is not linear and goes directly either from the empiricism-to-theory or the theory-to-empiricism (p.367). And the scientific progress has proceeded with circularity, goes around and around. Secondly, as a result of the first position, the nature is observable and science only studies what is observable in nature. The theory is grounded on the observable nature.
Then the author constructs a scheme of the scientific event. The scheme provides the components of the scientific activity. As one may see, at the left of the scheme there are empirical components of the scientific activity, such as experiments, instruments, measurements, and perceptual space. The author provides (p.66) definitions of such components:
Experiment is the controlled observation of nature, experiencing nature through the human senses aided by scientific instruments
Instrument is a device which provides a means of extending the range and sensitivity of human sensing of nature
Measurement is an instrumental technique in observing nature that results in quantitative data about the phenomenal thing
Perceptual Space is conceptual framework within which a natural phenomenon is described
At the right of scheme there are theoretical components of the scientific activity, such as analysis, phenomenological law, model, and theory. The author provides (p.66, p.86-90) definitions of such components:
Analysis is inferring a mathematical pattern in the quantitative data of a set of experiments
Phenomenological Law is a generalization of relationships observed between natural objects
Model is a symbolic simulation of the processes of a phenomenal object
Theory is a symbolic description of the processes of the phenomenal field of objects
Social and Natural sciences follow different scientific paradigms. The author discusses the Paradigm of Mechanism, Paradigm of Function, Paradigm of Logic and Paradigm of System. While the paradigm of mechanism is central to physics and biology, it is much less so for mathematics or social sciences. The paradigm of function is central to biology but not to physics.
Secondly, different paradigms follow different phenomenological laws. The causal explanation exists only in physics, biology and chemistry, while mathematics and social sciences use prescriptive explanations.
Thirdly, sciences differ in objectivity. Knowledge in physical science disciplines is context and observer independent, while social science disciplines depend on the context and are influenced by values of the observer. The author describes physical theories as empirically grounded value-free theories, and sociological theories - as both empirical and normative grounded value-loaded (value-laden) theories (p.191-203).
The paradigm of mechanism as instigated by Isaac Newton (p.22) perceives the world in terms of space, time, energy, matter, and force. The paradigm of mechanism provides intellectual framework for value-free description of the nature, with ability to causal explanation and prediction of natural events.
The Paradigm of Function is based on concepts of purpose, intention. Both paradigm of function and the paradigm of mechanism are used in biology as they both help to describe the nature of living beings. The author further describes how the paradigm of system is connected with paradigm of mechanism and function in various ways. The author postulates: a complete scientific description of physical objects requires a prior scientific framework of Mechanism and System (p. 222), with an example of the model of the solar system. Movement of any object in space is covered by paradigm of mechanism, while movement and interaction of a set of objects (like solar system) is described with language and the paradigm of system. Still, a complete scientific description of animate objects requires a scientific framework of Mechanism and Function and Systems (p. 223), with example of Biology - Complex biological organisms contain subsystems.
The Author provides the definition of Paradigm of Logic as an “a priori” framework, which provides both a “transcendental aesthetic and logic” for describing and explaining sentient behavior in intelligent social organisms (p.224). In other words, the Paradigm of Logic provides the intellectual framework for thinking and communication of the sentient beings (p.240) that is completely different from the “ordinary” interpretation of logic as mathematical logic.
However, dominant paradigms are changing, especially when the headwind against dominant paradigms gets strong enough. The author provides examples of acceptance of new paradigms as examples of plate tectonics and transition between the worldview of Newtonian physics and the Einsteinian physics.
As mentioned earlier, the book starts with a story about Rutherford’s Experiments. By the example of Rutherford’s Experiment of Structure of Atom the author describes the organizational aspect of the scientific activity. For instance, Rutherford was a university professor with funding, laboratory, research supplies and equipment. Moreover, Rutherford was able to hire Geiger and Marsden as research assistants (p. 7). Nowadays, the megamachine of science is much bigger, and scientific content is produced in different institutions.
Modern research universities hire professors to organize and manage research projects (in addition to education service). There are two classes of research projects in terms of size. The first target is PhD related research projects in which project young scientists obtain knowledge and demonstrate personal ability to carry out a research. The second group of research projects is often labeled as “big science”, for example, research of the structure of the elementary particle. “Big science” is a special form of organization of a scientific research that includes multiple actors like research institutes, R&D laboratories, research groups in different countries. PhD-sized projects transform to “big science” projects due to increase in the size and number of small projects. Reaching the “critical mass” (p.107) of research projects is necessary for scientific progress advancement and is often performed inside a university research center.
Sometimes science is connected with technology and research crosses the boundaries of disciplines. In this case, research becomes interdisciplinary or multidisciplinary. Multidisciplinary research assumes a collective work of research from different scientific areas together at a dedicated multidisciplinary research center. The author indicates (p. 313) three major functions of such centers:
Encourage an integrated strategy for conceiving research projects
Facilitate obtaining of research funding to support research projects
Target progress in science and technology
The multidisciplinary technology-focused-and-targeted basic research can be organized and planned for (p. 319):
Generic technology systems and subsystems for product systems
Generic technology systems and subsystems for production systems
Physical phenomena underlying technology systems and subsystems for product systems and for production systems
Moreover, here is one important aspect: research for technology cannot be planned before the end of the basic technology invention.
Government agencies implement governance in science by supporting selected areas of research in accordance with Strategic programs.
The author generalizes four focuses for research strategies in government programs: Problem, System, Nature and Technology. Each focus can be explained by different research opportunities for the government mission (p. 46). Firstly, research strategy could be focused upon research about problem in a society. Secondly, focus of research strategy could be concentrated upon research for invention to improve technology for dealing with the problems. Thirdly, another aim of the research strategy could be a focus upon the nature (science) underlying the societal problems. And last focus is a representation of the systems (engineering) operating in societal problems.
The figure on page 372 provides mapping from nature to problems, from nature to systems and from technology to nature. Research initiatives on top of such mapping can be formulated through connecting research in science to research in technology to research in problems (p. 52). To explain this point the authors provides five strategic initiatives:
Improvement of systems representation by progress in the science of nature (1)
Improvement of problem analysis by progress in science (2)
Improvement of instrumentation and techniques for science by invention of new technologies (3)
Improvement of techniques for science by invention of new technologies (4)
Invention of new technologies to solve problems (5)
Technology is one of important values for science.
The author describes innovation processes as transformation of knowledge-of-nature (science) to manipulation-of-nature (technology) through acts of research followed by transformation to use-of-nature (economy) through act of commercialization. Definitions of all components are provided using the semantic basis of “nature” (p. 125).
The book is well written and easy to read. The content is structured and provided in logical order. All theses are supported by historical examples. Meanwhile, the contents of the book could be enhanced.
Chapters one, three and six describe government support of science, research and innovation. Still, some important questions have been left out. Can people forecast science and technologies? An introduction to technology forecasting and foresight methods can extend this line of discourse.
Chapters 6-13 describe the concept of the system. They introduce the definition of the system and provide examples. This definition is close to the definition of hard systems provided by Peter Checkland. Checkland conducted research in the area of systems and identified another representation of systems - the soft systems. In his works, the concept of the soft systems is introduced not as an ontological represent of the nature, but as an epistemological notion . In other words, “systemic” - it is a feature of the method of constructing mental constructions by a thinker. Such approach is used in analysis, when the analyzed object (or group of objects) cannot be decomposed and presented as “hard” system. For example, systems with multiple not formalized components and implicit links. High complexity of analyzed system could be another reason to use soft system methodology. In my opinion, conceptions of System thinking and Soft Systems Methodology, supported by examples, could significantly improve the value of this book.
Chapter 13 continues with systems dynamics as the methodological approach for modeling organization of systems. The author provides Porter’s a value-added model of a business enterprise and a model of a managed system. This chapter finalizes examples of systems application. In my opinion, these examples are not enough to represent both examples of systems application and the system or organization of labor. The scientific issues, methods, approaches (and more) to the organization of systems could be explained on top of philosophical background (chapter 2), then linked with basic conceptions of the system (chapter 10), and then extended in accordance with System thinking. And finally, as example of different approach to the organization of management, the conception of methodological organization of research and development provided by Schedrovitsky and Moscow Methodological Circle (MMC) could be presented. For example, they developed  systems-structural methodology, described the role and function of a methodologist in the organization of systems, etc.
In sum, this book is well written and easy to read. Ideas are presented very logically and systemically. The model of Science is presented, described in detail and the book is full of examples and historical material. I recommend it for young scientists and final reading after a course of philosophy of science. Moreover, this book can be interesting to students who study R&D management.
 Peter Checkland. Soft systems methodology: a thirty year retrospective. In Systems Research and Behavioral Science, 1999.
 Lewis Mumford. Technics and Human Development: The Myth of the Machine, Vol. I. Harvest Books, 1971.
 GP Schedrovitsky. Methodological organization of system-structural research and development: principles and general framework. General Systems, 27:75–96, 1982.