Bibliometric profiles for British academic institutions: An experiment to develop research output indicators

Carpenter, Mark P.; Gibb, Forbes; Harris, Martyn; Irvine, John; Martin, Ben R.; Narin, Francis

doi:10.1007/bf02020076

Cited by 47 publications

(17 citation statements)

References 5 publications

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“…A detailed description of the CWTS data-system is given in MOED et al, (1995). Many researchers depend on corporate addresses in view of the increasing impact of studies about research that are centred on institutional domains (CARPENTER et al, 1988; MOED & VAN RAAN, 1988;SHRUM & MULLINS, 1988;DE BRUIN & MOED, 5 1993;RINIA et al, 1993;HERBERTZ & MÜLLER-HILL, 1995;MELIN & PERSSON, 1996;BOURKE & BUTLER, 1998; VAN DEN BERGHE et al, 1998;NOYONS et al, 1999;MÄHLCK & PERSSON, 2000;MOED, 2000;MOYA-ANEGÓN et al, 2004). Although manual processing will, to some extent, be inevitable for unifying and reformatting the institutional affiliations of authors, it is hoped that the new approach described here provides a means of overcoming the scattering of organization data, thereby facilitating data isolation and unification for later bibliometric analyses.…”

Section: Introductionmentioning

confidence: 99%

Standardizing formats of corporate source data

Gálvez

Anegón

2007

Scientometrics

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This paper describe an approach for improving the data quality of corporate sources when databases are used for bibliometric purposes. Research management relies on bibliographic databases and citation index systems as analytical tools, yet the raw resources for bibliometric studies are plagued by a lack of consistency in fied formatting for institution data. The present contribution puts forth a Natural Language Processing (NLP)-oriented method for the identification of the structures guiding corporate data and their mapping into a standardized format. The proposed unification process is based on the definition of address patterns and the ensuing application of Enhanced Finite-State Transducers (E-FST). Our procedure was tested on address formats downloaded from the INSPEC, MEDLINE and CAB Abstracts. The results demonstrate the helpfulness of the method as long as close control of errors is exercised as far as the formats to be unified. The computational efficacy of the model is noteworthy, due to the fact that it is firmly guided by the definition of data in the application domain.

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Section: Introductionmentioning

confidence: 99%

Standardizing formats of corporate source data

Gálvez

Anegón

2007

Scientometrics

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“…Evaluative scientometrics, a subarea of bibliometrics, has developed arrays of indicators that can be used to describe the research performance of the organizations at different levels of aggregation (CARPENTER et al, 1988;MOED & VAN RAAN, 1988). The assessment of organizations provides new possibilities for the utilization of the address field in a picture of the dynamic aspects of scientific research, such as the mapping of science and network analysis (SHRUM & MULLINS, 1988;NOYONS et al, 1999;MÄHLCK & PERSSON, 2000).…”

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confidence: 99%

The unification of institutional addresses applying parametrized finite-state graphs (P-FSG)

Gálvez

Anegón

2006

Scientometrics

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We propose a semi-automatic method based on finite-state techniques for the unification of corporate source data, with potential applications for bibliometric purposes. Bibliographic and citation databases have a well-known problem of inconsistency in the data at micro-level and meso-level, affecting the quality of bibliometric searches and the evaluation of research performance. The unification method applies parametrized finite-state graphs (P-FSG) and involves three stages: (1) breaking of corporate source data in independent units of analysis; (2) creation of binary matrices; and (3) drawing finite-state graphs. This procedure was tested on university departmental addresses, downloaded from the ISI Web of Science. Evaluation was in terms of an adaptation of the measures of precision and recall. The results demonstrate the usefulness of this approach, though it requires some human processing.

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“…Many studies can be found in the literature developing such techniques in order to classify academic institutions (Shin, 2009;Ortega et al, 2011), establish institutional profiles (Carpenter et al, 1988;Garcia et al, 2012a) or compare universities performance (Adams et al, 2007;Tijssen et al, 2009;Torres-Salinas et al, 2011a). For instance, (Adams et al, 2007) present a methodology for profiling universities according to their impact as an intuitive way to identify outstanding institutions when compared with the average research performance of a country, region, or any other given research unit.…”

Section: Introductionmentioning

confidence: 99%

“…In this paper, we propose applying dissimilarity techniques to universities research output in order to detect those which look alike according to their competitiveness defined as their capacity for publishing in top journals. We follow the line of thought proposed by (Carpenter et al, 1988) in which they state that journals' impact factor is a good proxy measure for large aggregations of data for research excellence.…”

Section: Introductionmentioning

confidence: 99%

Benchmarking research performance at the university level with information theoretic measures

et al. 2012

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This paper presents a new method for comparing universities based on information theoretic measures. The research output of each academic institution is represented statistically by an impact-factor histogram. To this aim, for each academic institution we compute the probability of occurrence of a publication with impact factor in different intervals. Assuming the probabilities associated with a pair of academic institutions our objective is to measure the Information

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Bibliometric profiles for British academic institutions: An experiment to develop research output indicators

Cited by 47 publications

References 5 publications

Standardizing formats of corporate source data

Standardizing formats of corporate source data

The unification of institutional addresses applying parametrized finite-state graphs (P-FSG)

Benchmarking research performance at the university level with information theoretic measures

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