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Using the ESO Telescope Bibliography database telbib, we have investigated the percentage of ESO data papers that were submitted to the arXiv/astro-ph e-print server and that are therefore free to read. Our study revealed an availability of up to 96% of telbib papers on arXiv over the years 2010 to 2017. We also compared the citation counts of arXiv vs. non-arXiv papers and found that on average, papers submitted to arXiv are cited 2.8 times more often than those not on arXiv. While simulations suggest that these findings are statistically significant, we cannot yet draw firm conclusions as to the main cause of these differences.
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One of the classic ways to measure the success of a scientific facility is the publication return, which is defined as the number of refereed papers produced per unit of allocated resources (for example, telescope time or proposals). The recent studies by Sterzik et al. (2015, 2016) have shown that 30-50 % of the programmes allocated time at ESO do not produce a refereed publication. While this may be inherent to the scientific process, this finding prompted further investigation. For this purpose, ESO conducted a Survey of Non-Publishing Programmes (SNPP) within the activities of the Time Allocation Working Group, similar to the monitoring campaign that was recently implemented at ALMA (Stoehr et al. 2016). The SNPP targeted 1278 programmes scheduled between ESO Periods 78 and 90 (October 2006 to March 2013) that had not published a refereed paper as of April 2016. The poll was launched on 6 May 2016, remained open for four weeks, and returned 965 valid responses. This article summarises and discusses the results of this survey, the first of its kind at ESO.
If someone is looking for a certain publication in the field of computer science, the searching person is likely to use the DBLP to find the desired publication. The DBLP data set is continuously extended with new publications, or rather their metadata, for example the names of involved authors, the title and the publication date. While the size of the data set is already remarkable, specific areas can still be improved. The DBLP offers a huge collection of English papers because most papers concerning computer science are published in English. Nevertheless, there are official publications in other languages which are supposed to be added to the data set. One kind of these are Japanese papers. This diploma thesis will show a way to automatically process publication lists of Japanese papers and to make them ready for an import into the DBLP data set. Especially important are the problems along the way of processing, such as transcription handling and Personal Name Matching with Japanese names.
The ESO telescope bibliography (telbib) dates back to 1996. During the 20+ years of its existence, it has undergone many changes. Most importantly, the telbib system has been enhanced to cater to new use cases and demands from its stakeholders. Based on achievements of the past, we will show how a system like telbib can not only stay relevant through the decades, but gain importance, and provide an essential tool for the observatorys management and the wider user community alike.
In this paper we describe the way the Astro-WISE information system (or simply Astro-WISE) supports the data from a wide range of in- struments and combines multiple surveys and their catalogues. Astro-WISE allows ingesting of data from any optical instrument, survey or catalogue, pro- cessing of this data to create new catalogues and bringing in data from different surveys into a single catalogue, keeping all dependencies back to the original data. Full data lineage is kept on each step of compiling a new catalogue with an ability to add a new data source recursively. With these features, Astro- WISE allows not only combining and retrieving data from multiple surveys, but performing scientific data reduction and data mining down to the rawest data in the data processing chain within a single environment.
We demonstrate a comprehensive framework that accounts for citation dynamics of scientific papers and for the age distribution of references. We show that citation dynamics of scientific papers is nonlinear and this nonlinearity has far-reaching consequences, such as diverging citation distributions and runaway papers. We propose a nonlinear stochastic dynamic model of citation dynamics based on link copying/redirection mechanism. The model is fully calibrated by empirical data and does not contain free parameters. This model can be a basis for quantitative probabilistic prediction of citation dynamics of individual papers and of the journal impact factor.
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