Electronic publishing developments and new information technology in general will affect the main functions of scientific communication. Most changes however will be primarily technological but not conceptual. Publication via journals of high reputation is in most fields of science crucial to receive professional recognition. That will remain so in the ihelectronic erale. A much more revolutionary change in science will be the increasing availability and sharing of research data.
We present a model in which scientists compete with each other in order to acquire status fortheir publications in a two-step-process: first, to get their work published in better journals, andsecond, to get this work cited in these journals. On the basis of two Maxwell-Boltzmann typedistribution functions of source publications we derive a distribution function of citingpublications over source publications. This distribution function corresponds very well to theempirical data. In contrast to all observations so far, we conclude that this distribution of citationsover publications, which is a crucial phenomenon in scientometrics, is not a power law, but amodified Bessel-function.
On the basis of the measured time-dependent distribution of references in recent scientific publications, we formulate a novel model on the ageing of recent scientific literature. The framework of this model is given by a basic set of mathematical expressions that allows us to understand and describe large-scale growth and ageing processes in science over a long period of time. In addition, a further and striking consequence results in a self- consistent way from our model. After the Scientific Revolution in 16th century Europe, the 'Scientific Evolution' begins, and the driving processes growth and ageing unavoidably lead - just as in our biological evolution - to a fractal differentiation of science. A fractal structure means a system build up with sub-systems characterised by a power-law size distribution. Such a distribution implies that there is no preference of size or scale. Often this phenomenon is regarded as a fingerprint of self-organisation. These findings are in agreement with earlier empirical findings concerning the clustering of scientific literature. Our observations reinforce the idea of science as a complex, largely self-organising 'cognitive eco-system'. They also refute Kuhn's paradigm model of scientific development.
In this paper we present a compilation of journal impact properties in relation to other bibliometric indicators as found in our earlier studies together with new results. We argue that journal impact, even calculated in a sufficiently advanced way, becomes important in evaluation practices based on bibliometric analysis only at an aggregate level. In the relation between average journal impact and actual citation impact of groups, the influence of research performance is substantial. Top-performance as well as lower performance groups publish in more or less the same range of journal impact values, but top-performance groups are, on average, more successful in the entire range of journal impact. We find that for the high field citation-density groups a larger size implies a lower average journal impact. For groups in the low field citation-density regions however a larger size implies a considerably higher average journal impact. Finally, we found that top-performance groups have relatively less self-citations than the lower performance groups and this fraction is decreasing with journal impact.
A 'Sleeping Beauty in Science' is a publication that goes unnoticed ('sleeps') for a long time and then, almost suddenly, attracts a lot of attention ('is awakened by a prince'). We here report the -to our knowledge- first extensive measurement of the occurrence of Sleeping Beauties in the science literature. We derived from the measurements an 'awakening' probability function and identified the 'most extreme Sleeping Beauty so far'.
this paper we present characteristics of the statistical correlation between
the Hirsch (h-) index and several standard bibliometric indicators, as well as
with the results of peer review judgment. We use the results of a large
evaluation study of 147 university chemistry research groups in the Netherlands
covering the work of about 700 senior researchers during the period 1991-2000.
Thus, we deal with research groups rather than individual scientists, as we
consider the research group as the most important work floor unit in research,
particularly in the natural sciences.
Furthermore, we restrict the citation period to a three-year window
instead of 'life time counts' in order to focus on the impact of recent work
and thus on current research performance. Results show that the h-index and our
bibliometric 'crown indicator' both relate in a quite comparable way with peer
judgments. But for smaller groups in fields with 'less heavy citation traffic'
the crown indicator appears to be a more appropriate measure of research
Summary In this paper we report first results of our study on network characteristics of a reference-based, bibliographically coupled (BC) publication network structure. We find that this network of clustered publications shows different statistical properties depending on the age of the references used for building the network. A remarkable finding is that only the network based on all references within publications is characterized by a degree distribution with a power-law dependence. This structure, which is typical for scale-free networks, disappears when selecting references of a specific age for the clustering process. Changing the publication network as a function of reference age, allows 'tuning through the episodic memory' of the nodes of the network. We find that the older the references, the more the network tends to change its structure towards a more exponential degree distribution.