The dynamic mapping of science using the data in theScience Citation Index was put on the research agenda of science studies byDe Solla Price in the mid 1960s. Recently, proponents of co-citation cluster analysis have claimed that in principle their methodology makes such mapping possible. The study examines this claim, both methodologically and theoretically, in relation to other means of mapping science. A detailed study of a co-citation map, its core documents' citation patterns and the related journal structures, is presented. At these three levels of possible study of aggregates of citations, an analysis is pursued for the years 1978 to 1984. The many different statistical methods which are in use for the analysis of the respective datamatrices—such as cluster analysis, factor analysis and multidimensional scalling—are assessed with a view to their potential to contribute to a better undérstanding of the dynamics at the different levels in relation to each other. This will lead to some recommendations about methods to use and to avoid when we aim at a comprehensive mapping of science. Although the study is pursued at a formal and analytical level, in the conclusions an attempt is made to reflect on the results in terms of further substantial questions for the study of the dynamics of science.
The theory of autopoiesis, i.e., self-referentiality in the operation of the system, provides us with a production rule for change in the structure of the network. Using information theory, a model system is developed to study the relative likelihood of dynamic transitions: various senses of irreversibility (emergence, and path dependency) are disinguished. A test for path dependency is applied to two sets of empirical data which supposedly reflect historical discontinuities: the budget of theFraunhofer Gesellschaft, and the citation network among AIDS research related journals. The model for the interaction between self-referential developments and goal-referential boundary conditions is further specified, using the example of technological trajectories and selection environments.
In a previous paper a static model for the relations among science indicators was discussed. From the perspective of science dynamics, we are interested not in relations among variables or indicators, but in the prediction of an event, given comparable events about which we already have knowledge. The quality of the prediction can be measured by the expected information valueI of the message, which converts thea priori probabilities of the events stored in the knowledge base into thea posteriori probabilities of the event. The possibility of predicting in terms of specified variables with hindsight, gives a quantitative measure for testing hypotheses concerning the reconstruction of scientific developments. Some implications for the construction of artificial intelligence using textual archives, as a knowledge base will be discussed.
The study discusses the application of various forms of time series analysis to national performance data for EEC countries and the US. First, it is shown that at the aggregated level, a straightforward relation exists between output and input, which varies with time. Various analytical techniques to account for the time factor are discussed. By using information theory, a simple formula can be derived which gives the best prediction for the following year's data. Subsequently, this model is extended to multi-variate forecasting of distributions. Additionally, it can be shown by using this method that in terms of percentage of world share of publications the hypothesis that the EEC develops as a single publication system has to be rejected. However, when co-authorship relations among EEC member countries are used as an indicator, the predominance of a system is suggested.
With respect to the issue of whether the scientometric measurement of the decline of British science is an artifact of the specific database and underlying assumptions in methods, I argue that there are fewer analytical objections against measurement by usingSciSearch Online than against other methods (based on the fixed journal set and fractional counting). The measurement of international co-authorship, i.e. a network indicator, should not be confounded with measurement of performance of a single nation. The time series for the different subsets of UK-publications, which have been proposed, are given. None of the indicators can be shown to exhibit a trend (in contrast to a drift). The hypothesis of a decline has therefore to be rejected.
Clusters of normalized title-words in two sets of patent data in the food-sector (from 1985 and 1989, respectively) are analyzed in terms of their underlying document and word structures. The clusters were generated by using the system LEXIMAPPE of the Paris School of Mines. Both input and output data were kindly made available for validation purposes. Analysis of the data shows that the centrality and the density of the clusters produced by LEXIMAPPE are primarily dependent on the number of word occurrences in the corresponding parts of the input matrix. While the clusters are kept approximately equal in terms of the number of words (with a maximum of 10), they vary widely in terms of the number of word occurrences in the underlying document sets. Centrality and density vary correspondingly. The contribution of the smallest cluster to the reduction of uncertainty in the prediction of the document structure is even smaller than that of 77 (other) single words. In the dynamic analysis, I found significant stability where LEXIMAPPE indicated major changes. However, like every clustering algorithm LEXIMAPPE is based on specific assumptions which may lead to specific results that cannot be simulated by using other methods. Researchers who base their results on LEXIMAPPE should be aware of the peculiarities specific to this system.
A method is described for the generation of journal-journal citation maps on the basis of the CD-ROM version of theScience Citation Index. Various sources of potential errors in using this data are discussed, and strategies are suggested to counteract these errors. A number of scientometric journal mappings are analyzed in relation to mappings from previous studies which have used tape data and/or data from ISI'sJournal Citation Reports. The quality of these mappings is compared with the quality of those for previous years in order to demonstrate usefulness of such mappings as indicators for dynamic developments in the sciences.