Emergence d’une spécialité scientifique dans l’espace - La réparation de l’ADN

International audienceIn the study of science, the specialty is seen as the ideal level of analysis to understand the genesis and development of scientific communities. This article uses bibliometric data to analyze the emergence of DNA repair by testing a hybrid method to identify the specialty’s appearance in geographical space by focusing on the geographical trajectories of the pioneers in this field. We try to identify the professional mobility of researchers using these bibliometric data, and if possible to highlight the structural networks of places during the emergence stage of the specialty. These networks determine places as much as they are built by individual trajectories. In this way, we try to make a place for the geography of science in the field of social studies of science.Dans l’étude des sciences, la spécialité est perçue comme le niveau d’analyse idéal pour comprendre la genèse et le développement des collectifs scientifiques. Cet article utilise des données bibliométriques pour analyser l’émergence de la Réparation de l’ADN en expérimentant une méthode mixte pour repérer son apparition dans l’espace géographique. En nous concentrant sur les trajectoires géographiques de pionniers dans cedomaine, nous tâchons de repérer leur mobilité professionnelle à l’aide de données bibliométriques dans la perspective de mettre en évidence les réseaux de lieux structurants dans la phase d’émergence de la spécialité. Ces réseaux de lieux déterminent autant qu’ils sont construits par les trajectoires individuelles. Nous essayons ainsi de faire une place à la géographie des sciences dans le domaine des études sociales des sciences

Characterizing Interdisciplinarity of Researchers and Research Topics Using Web Search Engines

Researchers' networks have been subject to active modeling and analysis. Earlier literature mostly focused on citation or co-authorship networks reconstructed from annotated scientific publication databases, which have several limitations. Recently, general-purpose web search engines have also been utilized to collect information about social networks. Here we reconstructed, using web search engines, a network representing the relatedness of researchers to their peers as well as to various research topics. Relatedness between researchers and research topics was characterized by visibility boost-increase of a researcher's visibility by focusing on a particular topic. It was observed that researchers who had high visibility boosts by the same research topic tended to be close to each other in their network. We calculated correlations between visibility boosts by research topics and researchers' interdisciplinarity at individual level (diversity of topics related to the researcher) and at social level (his/her centrality in the researchers' network). We found that visibility boosts by certain research topics were positively correlated with researchers' individual-level interdisciplinarity despite their negative correlations with the general popularity of researchers. It was also found that visibility boosts by network-related topics had positive correlations with researchers' social-level interdisciplinarity. Research topics' correlations with researchers' individual- and social-level interdisciplinarities were found to be nearly independent from each other. These findings suggest that the notion of "interdisciplinarity" of a researcher should be understood as a multi-dimensional concept that should be evaluated using multiple assessment means.Comment: 20 pages, 7 figures. Accepted for publication in PLoS On

A reverse engineering approach to the suppression of citation biases reveals universal properties of citation distributions

The large amount of information contained in bibliographic databases has recently boosted the use of citations, and other indicators based on citation numbers, as tools for the quantitative assessment of scientific research. Citations counts are often interpreted as proxies for the scientific influence of papers, journals, scholars, and institutions. However, a rigorous and scientifically grounded methodology for a correct use of citation counts is still missing. In particular, cross-disciplinary comparisons in terms of raw citation counts systematically favors scientific disciplines with higher citation and publication rates. Here we perform an exhaustive study of the citation patterns of millions of papers, and derive a simple transformation of citation counts able to suppress the disproportionate citation counts among scientific domains. We find that the transformation is well described by a power-law function, and that the parameter values of the transformation are typical features of each scientific discipline. Universal properties of citation patterns descend therefore from the fact that citation distributions for papers in a specific field are all part of the same family of univariate distributions.Comment: 9 pages, 6 figures. Supporting information files available at http://filrad.homelinux.or

Who is the best player ever? A complex network analysis of the history of professional tennis

We consider all matches played by professional tennis players between 1968 and 2010, and, on the basis of this data set, construct a directed and weighted network of contacts. The resulting graph shows complex features, typical of many real networked systems studied in literature. We develop a diffusion algorithm and apply it to the tennis contact network in order to rank professional players. Jimmy Connors is identified as the best player of the history of tennis according to our ranking procedure. We perform a complete analysis by determining the best players on specific playing surfaces as well as the best ones in each of the years covered by the data set. The results of our technique are compared to those of two other well established methods. In general, we observe that our ranking method performs better: it has a higher predictive power and does not require the arbitrary introduction of external criteria for the correct assessment of the quality of players. The present work provides a novel evidence of the utility of tools and methods of network theory in real applications.Comment: 10 pages, 4 figures, 4 table

Effectiveness of Journal Ranking Schemes as a Tool for Locating Information

BACKGROUND: The rise of electronic publishing, preprint archives, blogs, and wikis is raising concerns among publishers, editors, and scientists about the present day relevance of academic journals and traditional peer review. These concerns are especially fuelled by the ability of search engines to automatically identify and sort information. It appears that academic journals can only remain relevant if acceptance of research for publication within a journal allows readers to infer immediate, reliable information on the value of that research. METHODOLOGY/PRINCIPAL FINDINGS: Here, we systematically evaluate the effectiveness of journals, through the work of editors and reviewers, at evaluating unpublished research. We find that the distribution of the number of citations to a paper published in a given journal in a specific year converges to a steady state after a journal-specific transient time, and demonstrate that in the steady state the logarithm of the number of citations has a journal-specific typical value. We then develop a model for the asymptotic number of citations accrued by papers published in a journal that closely matches the data. CONCLUSIONS/SIGNIFICANCE: Our model enables us to quantify both the typical impact and the range of impacts of papers published in a journal. Finally, we propose a journal-ranking scheme that maximizes the efficiency of locating high impact research

Network Archaeology: Uncovering Ancient Networks from Present-day Interactions

Often questions arise about old or extinct networks. What proteins interacted in a long-extinct ancestor species of yeast? Who were the central players in the Last.fm social network 3 years ago? Our ability to answer such questions has been limited by the unavailability of past versions of networks. To overcome these limitations, we propose several algorithms for reconstructing a network's history of growth given only the network as it exists today and a generative model by which the network is believed to have evolved. Our likelihood-based method finds a probable previous state of the network by reversing the forward growth model. This approach retains node identities so that the history of individual nodes can be tracked. We apply these algorithms to uncover older, non-extant biological and social networks believed to have grown via several models, including duplication-mutation with complementarity, forest fire, and preferential attachment. Through experiments on both synthetic and real-world data, we find that our algorithms can estimate node arrival times, identify anchor nodes from which new nodes copy links, and can reveal significant features of networks that have long since disappeared.Comment: 16 pages, 10 figure

The Nobel Prize as a Reward Mechanism in the Genomics Era: Anonymous Researchers, Visible Managers and the Ethics of Excellence

The Human Genome Project (HGP) is regarded by many as one of the major scientific achievements in recent science history, a large-scale endeavour that is changing the way in which biomedical research is done and expected, moreover, to yield considerable benefit for society. Thus, since the completion of the human genome sequencing effort, a debate has emerged over the question whether this effort merits to be awarded a Nobel Prize and if so, who should be the one(s) to receive it, as (according to current procedures) no more than three individuals can be selected. In this article, the HGP is taken as a case study to consider the ethical question to what extent it is still possible, in an era of big science, of large-scale consortia and global team work, to acknowledge and reward individual contributions to important breakthroughs in biomedical fields. Is it still viable to single out individuals for their decisive contributions in order to reward them in a fair and convincing way? Whereas the concept of the Nobel prize as such seems to reflect an archetypical view of scientists as solitary researchers who, at a certain point in their careers, make their one decisive discovery, this vision has proven to be problematic from the very outset. Already during the first decade of the Nobel era, Ivan Pavlov was denied the Prize several times before finally receiving it, on the basis of the argument that he had been active as a research manager (a designer and supervisor of research projects) rather than as a researcher himself. The question then is whether, in the case of the HGP, a research effort that involved the contributions of hundreds or even thousands of researchers worldwide, it is still possible to “individualise” the Prize? The “HGP Nobel Prize problem” is regarded as an exemplary issue in current research ethics, highlighting a number of quandaries and trends involved in contemporary life science research practices more broadly

Lines of Descent: Kuhn and Beyond

yesThomas S. Kuhn is famous both for his work on the Copernican Revolution and his ‘paradigm’ view of scientific revolutions. But Kuhn later abandoned the notion of paradigm (and related notions) in favour of a more ‘evolutionary’ view of the history of science. Kuhn’s position therefore moved closer to ‘continuity’ models of scientific progress, for instance ‘chain-of-reasoning’ models, originally championed by D. Shapere. The purpose of this paper is to contribute to the debate around Kuhn’s new ‘developmental’ view and to evaluate these competing models with reference to some major innovations in the history of cosmology, from Copernicanism to modern cosmology. This evaluation is made possible through some unexpected overlap between Kuhn’s earlier discontinuity model and various versions of the later continuity models. It is the thesis of this paper that the ‘chain-of-reasoning’ model accounts better for the cosmological evidence than both Kuhn’s early paradigm model and his later developmental view of the history of science