Search (6 results, page 1 of 1)

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Abstract

National exercises for the evaluation of research activity by universities are becoming regular practice in ever more countries. These exercises have mainly been conducted through the application of peer-review methods. Bibliometrics has not been able to offer a valid large-scale alternative because of almost overwhelming difficulties in identifying the true author of each publication. We will address this problem by presenting a heuristic approach to author name disambiguation in bibliometric datasets for large-scale research assessments. The application proposed concerns the Italian university system, comprising 80 universities and a research staff of over 60,000 scientists. The key advantage of the proposed approach is the ease of implementation. The algorithms are of practical application and have considerably better scalability and expandability properties than state-of-the-art unsupervised approaches. Moreover, the performance in terms of precision and recall, which can be further improved, seems thoroughly adequate for the typical needs of large-scale bibliometric research assessments.

Date

22. 1.2011 13:06:52

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Abstract

The 2004-2010 VQR (Research Quality Evaluation), completed in July 2013, was Italy's second national research assessment exercise. The VQR performance evaluation followed a pattern also seen in other nations, as it was based on a selected subset of products. In this work, we identify the exercise's methodological weaknesses and measure the distortions that result from them in the university performance rankings. First, we create a scenario in which we assume the efficient selection of the products to be submitted by the universities and, from this, simulate a set of rankings applying the precise VQR rating criteria. Next, we compare these "VQR rankings" with those that would derive from the application of more-appropriate bibliometrics. Finally, we extend the comparison to university rankings based on the entire scientific production for the period, as indexed in the Web of Science.

Series

Advances in information science

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Abstract

The growing complexity of challenges involved in scientific progress demands ever more frequent application of competencies and knowledge from different scientific fields. The present work analyzes the degree of collaboration among scientists from different disciplines to identify the most frequent "combinations of knowledge" in research activity. The methodology adopts an innovative bibliometric approach based on the disciplinary affiliation of publication coauthors. The field of observation includes all publications (167,179) indexed in the Science Citation Index Expanded for the years 2004-2008, authored by all scientists in the hard sciences (43,223) at Italian universities (68). The analysis examines 205 research fields grouped in 9 disciplines. Identifying the fields with the highest potential of interdisciplinary collaboration is useful to inform research polices at the national and regional levels, as well as management strategies at the institutional level.

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Abstract

Bibliometric indicators are increasingly used in support of decisions about recruitment, career advancement, rewards, and selective funding for scientists. Given the importance of the applications, bibliometricians are obligated to carry out empirical testing of the robustness of the indicators, in simulations of real contexts. In this work, we compare the results of national-scale research assessments at the individual level, based on the following three different indexes: the h-index, the g-index, and "fractional scientific strength" (FSS), an indicator previously proposed by the authors. For each index, we construct and compare rankings lists of all Italian academic researchers working in the hard sciences during the period 2001-2005. The analysis quantifies the shifts in ranks that occur when researchers' productivity rankings by simple indicators such as the h- or g-indexes are compared with those by more accurate FSS.

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Abstract

The current work applies a method for mapping the supply of new knowledge from public research organizations, in this case from Italian institutions at the level of regions and provinces (NUTS2 and NUTS3). Through the analysis of scientific production indexed in the Web of Science for the years 2006-2010, the new knowledge is classified in subject categories and mapped according to an algorithm for the reconciliation of authors' affiliations. Unlike other studies in the literature based on simple counting of publications, the present study adopts an indicator, Scientific Strength, which takes account of both the quantity of scientific production and its impact on the advancement of knowledge. The differences in the results that arise from the 2 approaches are examined. The results of works of this kind can inform public research policies, at national and local levels, as well as the localization strategies of research-based companies.

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Abstract

The use of Hirsch's h-index as a joint proxy of the impact and productivity of a scientist's research work continues to gain ground, accompanied by the efforts of bibliometrists to resolve some of its critical issues through the application of a number of more or less sophisticated variants. However, the literature does not reveal any appreciable attempt to overcome the objective problems of measuring h-indexes on a large scale for purposes of comparative evaluation. Scientists may succeed in calculating their own h-indexes but, being unable to compare them to those of their peers, they are unable to obtain truly useful indications of their individual research performance. This study proposes to overcome this gap, measuring the h- and Egghe's g-indexes of all Italian university researchers in the hard sciences over a 5-year window. Descriptive statistics are provided concerning all of the 165 subject fields examined, offering robust benchmarks for those who wish to compare their individual performance to those of their colleagues in the same subject field.