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We present a bibliographic analysis of Chandra, Hubble, and Spitzer publications. We find (a) archival data are used in >60% of the publication output and (b) archives for these missions enable a much broader set of institutions and countries to scientifically use data from these missions. Specifically, we find that authors from institutions that have published few papers from a given mission publish 2/3 archival publications, while those with many publications typically have 1/3 archival publications. We also show that countries with lower GDP per capita overwhelmingly produce archival publications, while countries with higher GDP per capital produce guest observer and archival publications in equal amounts. We argue that robust archives are thus not only critical for the scientific productivity of mission data, but also the scientific accessibility of mission data. We argue that the astronomical community should support archives to maximize the overall scientific societal impact of astronomy, and represent an excellent investment in astronomys future.
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The recently released Chandra Transmission Grating Catalog and Archive, TGCat, presents a fully dynamic on-line catalog allowing users to browse and categorize Chandra gratings observations quickly and easily, generate custom plots of resulting response corrected spectra on-line without the need for special software and to download analysis ready products from multiple observations in one convenient operation. TGCat has been registered as a VO resource with the NVO providing direct access to the catalogs interface. The catalog is supported by a back-end designed to automatically fetch newly public data, process, archive and catalog them, At the same time utilizing an advanced queue system integrated into the archives MySQL database allowing large processing projects to take advantage of an unlimited number of CPUs across a network for rapid completion. A unique feature of the catalog is that all of the high level functions used to retrieve inputs from the Chandra archive and to generate the final data products are available to the user in an ISIS written library with detailed documentation. Here we present a structural overview of the Systems, Design, and Accessibility features of the catalog and archive.
We propose a new performance indicator to evaluate the productivity of research institutions by their disseminated scientific papers. The new quality measure includes two principle components: the normalized impact factor of the journal in which paper was published, and the number of citations received per year since it was published. In both components, the scientific impacts are weighted by the contribution of authors from the evaluated institution. As a whole, our new metric, namely, the institutional performance score takes into account both journal based impact and articles specific impacts. We apply this new scheme to evaluate research output performance of Turkish institutions specialized in astronomy and astrophysics in the period of 1998-2012. We discuss the implications of the new metric, and emphasize the benefits of it along with comparison to other proposed institutional performance indicators.
The rapid development of modern science and technology has spawned rich scientific topics to research and endless production of literature in them. Just like X-ray imaging in medicine, can we intuitively identify the development limit and internal evolution pattern of scientific topic from the relationship of massive knowledge? To answer this question, we collect 71431 seminal articles of topics that cover 16 disciplines and their citation data, and extracts the idea tree of each topic to restore the structure of the development of 71431 topic networks from scratch. We define the Knowledge Entropy (KE) metric, and the contribution of high knowledge entropy nodes to increase the depth of the idea tree is regarded as the basis for topic development. By observing X-ray images of topics, We find two interesting phenomena: (1) Even though the scale of topics may increase unlimitedly, there is an insurmountable cap of topic development: the depth of the idea tree does not exceed 6 jumps, which coincides with the classical Six Degrees of Separation! (2) It is difficult for a single article to contribute more than 3 jumps to the depth of its topic, to this end, the continuing increase in the depth of the idea tree needs to be motivated by the influence relay of multiple high knowledge entropy nodes. Through substantial statistical fits, we derive a unified quantitative relationship between the change in topic depth ${Delta D}^t(v)$ and the change in knowledge entropy over time ${KE}^tleft(vright)$ of the article $v$ driving the increase in depth in the topic: ${Delta D}^t(v) approx log frac{KE^{t}(v)}{left(t-t_{0}right)^{1.8803}}$ , which can effectively portray evolution patterns of topics and predict their development potential. The various phenomena found by scientific x-ray may provide a new paradigm for explaining and understanding the evolution of science and technology.
The Geant4 reference paper published in Nuclear Instruments and Methods A in 2003 has become the most cited publication in the whole Nuclear Science and Technology category of Thomson-Reuters Journal Citation Reports. It is currently the second most cited article among the publications authored by two major research institutes, CERN and INFN. An overview of Geant4 presence (and absence) in scholarly literature is presented; the patterns of Geant4 citations are quantitatively examined and discussed.
Scientific journals are the repositories of the gradually accumulating knowledge of mankind about the world surrounding us. Just as our knowledge is organised into classes ranging from major disciplines, subjects and fields to increasingly specific topics, journals can also be categorised into groups using various metrics. In addition to the set of topics characteristic for a journal, they can also be ranked regarding their relevance from the point of overall influence. One widespread measure is impact factor, but in the present paper we intend to reconstruct a much more detailed description by studying the hierarchical relations between the journals based on citation data. We use a measure related to the notion of m-reaching centrality and find a network which shows the level of influence of a journal from the point of the direction and efficiency with which information spreads through the network. We can also obtain an alternative network using a suitably modified nested hierarchy extraction method applied to the same data. The results are weakly methodology-dependent and reveal non-trivial relations among journals. The two alternative hierarchies show large similarity with some striking differences, providing together a complex picture of the intricate relations between scientific journals.
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