Rosario Ruiz-Baños

Analysis of the field of physical chemistry of surfactants with the Unified Scienctometric Model. Fit of relational and activity indicators

SummaryBy the information system of CoPalRed© and with the treatment of 63,543 bibliographical references of scientific articles, the field of surfactants has been analysed in the light of the Unified Scientometric Model. It was found that the distributions of actors (countries, centres, and research laboratories, journals, researchers, key words of documents) fit Zifs Unified Law better than the Zipf-Mandelbrot Law. The model showed an especially good fit for relational indicators such as density and centrality. Using the Unified Bradford Law, the three zones fit were: core, straight fraction, and Groos droop. The fractality index was used to verify that Science can present fractal as well as transfractal structures. In conclusion, the Unified Scientometric Model is, for its flexibility and its integrating capacity, an appropriate model for representing Science, joining non-relational with relational Scientometrics under the same paradigm.

Bibliometric laws: Empirical flaws of fit

SummaryThe bibliometric laws of Zipf, Bradford, and Lotka, in their various mathematical expressions, frequently present difficulties in the fitting of empirical values. The empirical flaws of fit take place in the frequency of the words, in the productivity of the authors and the journals, as well as in econometric and demographic aspects. This indicates that the underlying fractal model should be revised, since, as shown, the inverse power equations (of the Zipf-Mandelbrot type) are not adequate, as they need to include exponential terms. These modifications not only affect Bibliometrics and Scientometrics, but also, for the generality of the fractal model, apply to Economy, Demography, and even Natural Sciences in general.

The pulsing structure of science: Ortega y Gasset, Saint Matthew, fractality and transfractality

By a new fractal/transfractal geometry of the Unified Scientometric Model, it is possible to demonstrate that science presents an oscillating or pulsing dynamic. It goes alternatively through two types of phases. Some phases are fractal, with crystalline networks, where the Matthew effect clearly manifests itself with regard to the most notable actors and those that provide the best contributions. The other phases are transfractal, with deformed, amorphous networks, in which the actors, considered mediocre, present greater capacity to restructure the network than the more renowned actors. The result after any transfractal deformation is a new crystalline fractal network. Behind this vision lies the Kuhn paradigms. As examples, the scientific fields of surfactants and autism have been analysed.

Structure and dynamics of scientific networks. Part I : Fundamentals of the quantitative model of translation

The fundamentals have been developed for a quantitative theory on the structure and dynamics of scientific networks. These fundamentals were conceived through a new vision of translation, defined mathematically as the derivative or gradient of the quality of the actors as a function of the coordinates for the space in which they perform. If we begin with the existence of a translation barrier, or an obstacle that must be overcome by the actors in order to translate, and if we accept the Maxwell-Boltzmann distribution as representative of the translating capacity of the actors, it becomes possible to demonstrate the known principle of “success breeds success.” We also propose two types of elemental translation: those which are irreverisble and those which are in equilibrium. In addition, we introduce the principle of composition, which enables, from elemental translations, the quantification of more complex ones.

Strategic knowledge maps of the techno-scientific network (SK maps)

Knowledge engineering and information mapping are two recent scientific disciplines in constant development where mathematics, linguistics, computer science, and information visualization converge. Their main focus is to discover and display new knowledge in large document databases. They have broad and innovative fields of application for strategic scouting in science and technology, knowledge management, business intelligence, and scientific and technological evaluation. This article presents a new method for mapping the strategic research network and illustrates its application to the strategic analysis of the knowledge domain “Spanish Research in Protected Areas for the Period 1981–2005.” This strategic knowledge is displayed through a set of two-dimensional cartographic maps and three-dimensional images of two networks: the international network WoS_KWAJ (1981–2005) and the national network IEDCYT_KWAJ (1981–2005). These maps can be very useful in decision-making processes for science and technology policy.

Structure and Dynamics of Scientific networks. Part II. The new Zipf's law, the clusters of co-citations and the model of the descriptor presence

Here, the quantitative theory of translation is shown to be of great utility in describing scientific networks. In fact, we deduce a new Zipfs Law for the descriptors of a set of documents, based on the concepts of centres of interest and of irreversible parallel translations. This new law can be generalized to other phenomena, such as the distribution of the sizes of cocitation clusters. Finally, we have established the model, for descriptor presence in a network, which closely fits the values recorded.