Identifying single influential publications in a research field: New analysis opportunities of the CRExplorer

Reference Publication Year Spectroscopy (RPYS) has been developed for identifying the cited references (CRs) with the greatest influence in a given paper set (mostly sets of papers on certain topics or fields). The program CRExplorer (see www.crexplorer.net) was specifically developed by Thor, Marx, Leydesdorff, and Bornmann (2016a, 2016b) for applying RPYS to publication sets downloaded from Scopus or Web of Science. In this study, we present some advanced methods which have been newly developed for CRExplorer. These methods are able to identify and characterize the CRs which have been influential across a longer period (many citing years). The new methods are demonstrated in this study using all the papers published in Scientometrics between 1978 and 2016. The indicators N_TOP50, N_TOP25, and N_TOP10 can be used to identify those CRs which belong to the 50%, 25%, or 10% most frequently cited publications (CRs) over many citing publication years. In the Scientometrics dataset, for example, Lotka's (1926) paper on the distribution of scientific productivity belongs to the top 10% publications (CRs) in 36 citing years. Furthermore, the new version of CRExplorer analyzes the impact sequence of CRs across citing years. CRs can have below average (-), average (0), or above average (+) impact in citing years (whereby average is meant in the sense of expected values). The sequence (e.g. 00++---0--00) is used by the program to identify papers with typical impact distributions. For example, CRs can have early, but not late impact ("hot papers", e.g. +++---) or vice versa ("sleeping beauties", e.g. ---0000---++)

Computational Models for Transplant Biomarker Discovery.

Translational medicine offers a rich promise for improved diagnostics and drug discovery for biomedical research in the field of transplantation, where continued unmet diagnostic and therapeutic needs persist. Current advent of genomics and proteomics profiling called "omics" provides new resources to develop novel biomarkers for clinical routine. Establishing such a marker system heavily depends on appropriate applications of computational algorithms and software, which are basically based on mathematical theories and models. Understanding these theories would help to apply appropriate algorithms to ensure biomarker systems successful. Here, we review the key advances in theories and mathematical models relevant to transplant biomarker developments. Advantages and limitations inherent inside these models are discussed. The principles of key -computational approaches for selecting efficiently the best subset of biomarkers from high--dimensional omics data are highlighted. Prediction models are also introduced, and the integration of multi-microarray data is also discussed. Appreciating these key advances would help to accelerate the development of clinically reliable biomarker systems

Rank analysis of most cited publications, a new approach for research assessments

Citation metrics are the best tools for research assessments. However, current metrics are misleading in research systems that pursue simultaneously different goals, such as the advance of science and incremental innovations, because their publications have different citation distributions. We estimate the contribution to the progress of knowledge by studying only a limited number of the most cited papers, which are dominated by publications pursuing this progress. To field-normalize the metrics, we substitute the number of citations by the rank position of papers from one country in the global list of papers. Using synthetic series of lognormally distributed numbers, we developed the Rk-index, which is calculated from the global ranks of the 10 highest numbers in each series, and demonstrate its equivalence to the number of papers in top percentiles, P top 0.1% and P top 0.01% . In real cases, the Rk-index is simple and easy to calculate, and evaluates the contribution to the progress of knowledge much better than commonly used metrics. Although further research is needed, rank analysis of the most cited papers is a promising approach for research evaluation. It is also demonstrated that, for this purpose, domestic and collaborative papers should be studied independently.Comment: One PDF file, including figures and tables (31 pages

Like-for-like bibliometric substitutes for peer review: Advantages and limits of indicators calculated from the e(p) index

The use of bibliometric indicators would simplify research assessments. The 2014 Research Excellence Framework (REF) is a peer review assessment of UK universities, whose results can be taken as benchmarks for bibliometric indicators. In this study, we use the REF results to investigate whether the e(p) index and a top percentile of most cited papers could substitute for peer review. The probability that a random university's paper reaches a certain top percentile in the global distribution of papers is a power of the e(p) index, which can be calculated from the citation-based distribution of university's papers in global top percentiles. Making use of the e(p) index in each university and research area, we calculated the ratios between the percentage of 4-star-rated outputs in REF and the percentages of papers in global top percentiles. Then, we fixed the assessment percentile so that the mean ratio between these two indicators across universities is 1.0. This method was applied to four units of assessment in REF: Chemistry, Economics and Econometrics joined to Business and Management Studies, and Physics. Some relevant deviations from the 1.0 ratio could be explained by the evaluation procedure in REF or by the characteristics of the research field; other deviations need specific studies by experts in the research area. These results indicate that in many research areas the substitution of a top percentile indicator for peer review is possible. However, this substitution cannot be made straightforwardly; more research is needed to establish the conditions of the bibliometric assessment

Instruments on large optical telescopes -- A case study

In the distant past, telescopes were known, first and foremost, for the sizes of their apertures. Advances in technology are now enabling astronomers to build extremely powerful instruments to the extent that instruments have now achieved importance comparable or even exceeding the usual importance accorded to the apertures of the telescopes. However, the cost of successive generations of instruments has risen at a rate noticeably above that of the rate of inflation. Here, given the vast sums of money now being expended on optical telescopes and their instrumentation, I argue that astronomers must undertake "cost-benefit" analysis for future planning. I use the scientific output of the first two decades of the W. M. Keck Observatory as a laboratory for this purpose. I find, in the absence of upgrades, that the time to reach peak paper production for an instrument is about six years. The prime lifetime of instruments (sans upgrades), as measured by citations returns, is about a decade. Well thought out and timely upgrades increase and sometimes even double the useful lifetime. I investigate how well instrument builders are rewarded. I find acknowledgements ranging from almost 100% to as low as 60%. Next, given the increasing cost of operating optical telescopes, the management of existing observatories continue to seek new partnerships. This naturally raises the question "What is the cost of a single night of telescope time". I provide a rational basis to compute this quantity. I then end the paper with some thoughts on the future of large ground-based optical telescopes, bearing in mind the explosion of synoptic precision photometric, astrometric and imaging surveys across the electromagnetic spectrum, the increasing cost of instrumentation and the rise of mega instruments.Comment: Revised from previous submission (typos fixed, table 6 was garbled). Submitted to PAS

Interdisciplinarity in Translation Medicine: A Bibliometric Case Study.

Ph.D. Thesis. University of Hawaiʻi at Mānoa 2017