Personal Research Database

Full Text: 2010\Scientometrics82, 413.pdf

Abstract: The Hirsch index is a number that synthesizes a researcher’s output. It is defined as the maximum number h such that the researcher has h papers with at least h citations each. Woeginger (Math Soc Sci 56: 224-232, 2008a, J Informetr 2: 298-303, 2008b) suggests two axiomatic characterizations of the Hirsch index using monotonicity as one of the axioms. This note suggests three characterizations without adopting the monotonicity axiom.

Keywords: Axiomatic Characterization, Citations, Hirsch Index, Publications, Research Quality

? Puuska, H.M. (2010), Effects of scholar’s gender and professional position on publishing productivity in different publication types. Analysis of a Finnish university. Scientometrics, 82 (2), 419-437.

Full Text: 2010\Scientometrics82, 419.pdf

Abstract: This paper examines the effects of a scholar’s position and gender on publishing productivity in several types of scientific publications: monographs, articles in journals, articles in edited books, and articles in conference proceedings. The data consist of 1,367 scholars who worked at the University of Helsinki, Finland, during the period 2002-2004. The analysis shows that professors are the most productive, PhDs publish more than non-PhDs, and men perform better than women, also when other scholarly characteristics are controlled for. These differences are greater for monographs and articles in edited books than for articles in journals. In terms of conference proceedings, no remarkable productivity differences were found.

Keywords: Academic Position, Age, Articles, Books, Collaboration, Faculty, Faculty Rank, Fields, Gender, Journals, Performance, Publication, Publications, Publishing, Publishing Productivity, Science, Scientific Productivity, Scientific Publications, Women

? Veugelers, R. (2010), Towards a multipolar science world: Trends and impact. Scientometrics, 82 (2), 439-456.

Full Text: 2010\Scientometrics82, 439.pdf

Abstract: This paper brings together recent statistical evidence on international (co-)publications and (foreign) PhD-students and scholars to document shifts in geographic sources of scientific production and the impact this has on flows of scientific talent and partnering for scientific collaboration. The evidence demonstrates that despite the continued dominance of the US and the increasing importance of the EU, the TRIAD is in relative decline. Other geographic sources of science outside the TRIAD are rising, both in quantity, but also, although still to a lesser extent, in quality. Especially China drives this non-TRIAD growth. This catching-up of non-TRIAD countries drives a slow but real process of global convergence. It nevertheless leaves a less equal non-TRIAD science community, as the growth of China, is not matched by other non-TRIAD countries. Despite the rise of China’s own scientific production, and the increasing return flows of overseas students and scholars, the outward flows of Asian talents have not diminished over time. The data suggest a high correlation between the patterns of international mobility of scientists and the patterns of international collaborations. The large and stable flow of Chinese human capital into the US forms the basis on which stable international US-Chinese scientific networks are built. With the EU lacking this Chinese human capital circulation, it is more difficult to build up similar strong and stable networks.

Keywords: China, Co-Authorship, Collaboration, Convergence, EU, Globalisation, Impact, International Co-Publications, International Mobility, Non-Triad, Science, Scientific Networks, Scientific Production, Trends

? Gorraiz, J., Moed, H. and Schiebel, E. (2010), Preface. Scientometrics, 82 (3), 459-460.

Full Text: 2010\Scientometrics82, 459.pdf

? Vinkler, P. (2010), The pi(v)-index: a new indicator to characterize the impact of journals. Scientometrics, 82 (3), 461-475.

Full Text: 2010\Scientometrics82, 461.pdf

Abstract: For determining the eminence of scientific journals, a new indicator stressing the importance of papers in the “elite set” (i.e., highly cited papers) is suggested. The number of papers in the elite set (P (pi v)) is calculated with the equation: (10 log P) - 10, where P is the total number of papers in the set. The one-hundredth of citations (C) obtained by P (pi v) papers is regarded as the pi(v)-index which is field and time dependent. The pi(v)-index is closely correlated with the citedness (C/P) of P (pi v) papers, and it is also correlated with the Hirsch-index. Three types of Hirsch-sets are distinguished, depending on the relation of the number of citations received by the Hirsch-paper (ranked as h) and the paper next in rank (h + 1) by citation. The h-index of an Anomalous Hirsch-set (AH) may be increased by a single citation to a paper outside the Hirsch-core. (A set of papers may be regarded as AH, where the number of citations to the Hirsch-paper is higher than the h-index and the next paper in rank shows as many citations as the value of the h-index.).

Keywords: Citation, Citations, Elite Set, Eminence of Journals, h Index, h-Index, Highly Cited Papers, Hirsch Index, Hirsch-Index, Impact, Index, Information, Journals, Performance, Pi-Index, Science, Scientific Journals, Scientometric Indicators, Scientometric Indicators

? Aguillo, I.F., Ortega, J.L., Fernandez, M. and Utrilla, A.M. (2010), Indicators for a webometric ranking of open access repositories. Scientometrics, 82 (3), 477-486.

Full Text: 2010\Scientometrics82, 477.pdf

Abstract: The Ranking Web of World Repositories (http://repositories.webometrics.info) is introduced. The objective is to promote Open access initiatives (OAI) supporting the use of repositories for scientific evaluation purposes. A set of metrics based on web presence, impact and usage is discussed. The Ranking is built on indicators obtained from web search engines following a model close to the Impact Factor one. The activity accounts for a 50% of the index, including number of pages, pdf files and items in Google Scholar database, while the visibility takes into account the external inlinks received by the repository (the other 50%). The Ranking provides the Top 300 repositories from a total of 592 worldwide, with a strong presence of US, German and British institutional repositories and the leadership of the large subject repositories. Results suggest the need to take into consideration other file formats and the usage information, an option is not feasible today.

Keywords: Articles, Citation Advantage, Communication, Database, Evaluation, Google Scholar, Impact, Impact Factor, Indicators, Information, Institutional Repositories, Leadership, Metrics, Model, Open Access, Ranking, Repositories, Science, US, Usage, Visibility, Web, Webometrics

? Asemi, A. (2010), A citation analysis of Iranian journals to open access (OA) articles and journals. Scientometrics, 82 (3), 487-494.

Full Text: 2010\Scientometrics82, 487.pdf

Abstract: This study was survey on citation research of Open Access (OA) journals in English papers of Iranian universities journals during year 2007. The main purposes of this paper were: to examine the state of English papers in Iranian journals in Thomson Scientific Master Journal List (TSMJL), and to analyze their visibility through citations to OA journals in DOAJ database. In fact, the researcher has used of citation analysis technique of bibliometric and large-scale sociometric analyses on about 16,219 citations. The method followed in the first part of this study is obtaining data from e-journal articles which indexed in TSMJL, conducting descriptive analyses, and reporting the findings in tables and figures. In the second part of the study, DOAJ database is used to behaviour cited reference searches and other citation analyses. It found that there are 960 Iranian print-based journals and only 37 Iranian Journals was indexed in TSMJL. Sixteen English Journals in TSMJL of eight Iranian universities. Throughout sixteen journals only one journal didn’t publish during 2007 and there were 704 articles all over the fifteen journals. Using large-scale sociometric analyses on about 16,219 citations all over 15 journals, it is notable that number of journals without citation to DOAJ was 3,101 (99.7%) and the number of journals with citation to DOAJ was 9 (0.3%). It shows that there was huge difference between the journals which had citing to DOAJ and without citing to DOAJ.

Keywords: Age, Articles, Bibliometric, Citation, Citation Analysis, Citations, Database, DOAJ, Free Access, Iran, Journal, Journals, Open Access (OA) Journals, Referred Journals, Research, Sociometric Analysis, State, Thomson Scientific, Universities, Visibility

? Bar-Ilan, J. (2010), Citations to the “Introduction to informetrics” indexed by WOS, Scopus and Google Scholar. Scientometrics, 82 (3), 495-506.

Full Text: 2010\Scientometrics82, 495.pdf

Abstract: Google Scholar and Scopus are recent rivals to Web of Science. In this paper we examined these three citation databases through the citations of the book “Introduction to informetrics” by Leo Egghe and Ronald Rousseau. Scopus citations are comparable to Web of Science citations when limiting the citation period to 1996 and onwards (the citation coverage of Scopus)-each database covered about 90% of the citations located by the other. Google Scholar missed about 30% of the citations covered by Scopus and Web of Science (90 citations), but another 108 citations located by Google Scholar were not covered either by Scopus or by Web of Science. Google Scholar performed considerably better than reported in previous studies, however Google Scholar is not very “user-friendly” as a bibliometric data collection tool at this point in time. Such “microscopic” analysis of the citing documents retrieved by each of the citation databases allows us a deeper understanding of the similarities and the differences between the databases.

Keywords: Bibliometric, Bibliometric Data, Citation, Citations, Counts, Coverage, Data Collection, Database, Databases, Google Scholar, h-Index, Impact, Introduction to Informetrics, Science, Scopus, Web of Science, Web-of-Science

? Basu, A. (2010), Does a country’s scientific ‘productivity’ depend critically on the number of country journals indexed? Scientometrics, 82 (3), 507-516.

Full Text: 2010\Scientometrics82, 507.pdf

Abstract: In this paper, we examine the question whether it is meaningful to talk about the scientific productivity of nations based on indexes like the Science Citation Index or Scopus, when the journal set covered by them keeps changing with time. We hypothesize from the illustrative case of India’s declining productivity in the 1980s which correlated with a fall in its journals indexed, that an apparent increase/decrease in productivity for any country, based on observed change in its share of papers could, in fact, be an effect resulting from the inclusion of more/less journals from the country. To verify our hypothesis we have used SCIMAGO data. We found that for a set of 90 countries, the share of journals regressed on the share of papers gave a linear relationship that explained 80% of the variance. However, we also show that in the case of China’s unusual rise in world scientific productivity (to second rank crossing several other countries), there is yet another factor that needs to be taken into account. We define a new indicator-the JOURNAL PACKING DENSITY (JPD) or average number of papers in journals from a given country. We show that the packing density of Chinese journals has steadily increased over the last few years. Currently, Chinese journals have the highest ‘packing density’ in the world, almost twice the world average which is about 100 papers per journal per annum. The deviation of the JPD from the world average is another indicator which will affect so called ‘national productivities’ in addition to the number of national journals indexed. We conclude that in the context of a five fold increase in the number of journals indexed over 20 years, the simplistic notion of ‘scientific productivity’ as equivalent to papers indexed needs to be re-examined.

Keywords: Bibliometrics, China, China, Chinese Journals, Citation, Country Share, Density, India, India, Journal, Journals, Productivity, Publications, Science, Science Citation Index, Scientific Productivity, SCIMAGO, Scopus, Web of Science

? Costas, R., van Leeuwen, T.N. and Bordons, M. (2010), Self-citations at the meso and individual levels: Effects of different calculation methods. Scientometrics, 82 (3), 517-537.

Full Text: 2010\Scientometrics82, 517.pdf

Abstract: This paper focuses on the study of self-citations at the meso and micro (individual) levels, on the basis of an analysis of the production (1994-2004) of individual researchers working at the Spanish CSIC in the areas of Biology and Biomedicine and Material Sciences. Two different types of self-citations are described: author self-citations (citations received from the author him/herself) and co-author self-citations (citations received from the researchers’ co-authors but without his/her participation). Self-citations do not play a decisive role in the high citation scores of documents either at the individual or at the meso level, which are mainly due to external citations. At micro-level, the percentage of self-citations does not change by professional rank or age, but differences in the relative weight of author and co-author self-citations have been found. The percentage of co-author self-citations tends to decrease with age and professional rank while the percentage of author self-citations shows the opposite trend. Suppressing author self-citations from citation counts to prevent overblown self-citation practices may result in a higher reduction of citation numbers of old scientists and, particularly, of those in the highest categories. Author and co-author self-citations provide valuable information on the scientific communication process, but external citations are the most relevant for evaluative purposes. As a final recommendation, studies considering self-citations at the individual level should make clear whether author or total self-citations are used as these can affect researchers differently.

Keywords: Bibliometric Indicators, Bibliometric Tools, Citation, Citation Analysis, Citation Counts, Citations, Co-Author, Collaboration, Disciplines, Impact, Index, Indicators, Individual Scientists, Macro, Meso-Level, Methods, Micro-Level, Output, Pay, Professional, Reduction, Researchers, Science Policy, Scientific Communication, Self-Citation, Self-Citations

? Klavans, R. and Boyack, K.W. (2010), Toward an objective, reliable and accurate method for measuring research leadership. Scientometrics, 82 (3), 539-553.

Full Text: 2010\Scientometrics82, 539.pdf

Abstract: We compare a new method for measuring research leadership with the traditional method. Both methods are objective and reliable, utilize standard citation databases, and are easily replicated. The traditional method uses partitions of science based on journal categories, and has been extensively used to measure national leadership patterns in science, including those appearing in the NSF Science & Engineering Indicators Reports and in prominent journals such as Science and Nature. Our new method is based on co-citation techniques at the paper level. It was developed with the specific intent of measuring research leadership at a university, and was then extended to examine national patterns of research leadership. A comparison of these two methods provides compelling evidence that the traditional method grossly underestimates research leadership in most countries. The new method more accurately portrays the actual patterns of research leadership at the national level.

Keywords: Accuracy, Citation, Classification, Co-Citation, Co-Citation Analysis, Comparison, Competencies, Databases, Indicators, Journal, Journals, Leadership, Map of Science, Maps, Methods, National Leadership, Nations, Paradigms, Research, Research Leadership, Science, Science Map, Techniques, University, World

? Wan, J.K., Hua, P.H., Rousseau, R. and Sun, X.K. (2010), The journal download immediacy index (DII): experiences using a Chinese full-text database. Scientometrics, 82 (3), 555-566.

Full Text: 2010\Scientometrics82, 555.pdf

Abstract: Relationships between the journal download immediacy index (DII) and some citation indicators are studied. The Chinese full-text database CNKI is used for data collection. Results suggest that the DII can be considered as an independent indicator, but that it also has predictive value for other indicators, such as a journal’s h-index. In case a journal cannot yet have an impact factor-because its citation history within the database is too short-the DII can be used for a preliminary evaluation. The article provides results related to the CNKI database as a whole and additionally, some detailed information about agricultural and forestry journals.

Keywords: Agricultural And Forestry Journals, Citation, Data Collection, Database, Download Immediacy Index, Evaluation, Full-Text Databases, h Index, h-Index, History, Impact, Impact Factor, Indicators, Journal, Journal Evaluation Indicators, Journal Immediacy Index, Journals

? Schloegl, C. and Gorraiz, J. (2010), Comparison of citation and usage indicators: The case of oncology journals. Scientometrics, 82 (3), 567-580.

Full Text: 2010\Scientometrics82, 567.pdf

Abstract: It is the objective of this article to examine in which aspects journal usage data differ from citation data. This comparison is conducted both at journal level and on a paper by paper basis. At journal level, we define a so-called usage impact factor and a usage half-life in analogy to the corresponding Thomson’s citation indicators. The usage data were provided from Science Direct, subject category “oncology”. Citation indicators were obtained from JCR, article citations were retrieved from SCI and Scopus. Our study shows that downloads and citations have different obsolescence patterns. While the average cited half-life was 5.6 years, we computed a mean usage half-life of 1.7 years for the year 2006. We identified a strong correlation between the citation frequencies and the number of downloads for our journal sample. The relationship was lower when performing the analysis on a paper by paper basis because of existing variances in the citation-download-ratio among articles. Also the correlation between the usage impact factor and Thomson’s journal impact factor was “only” moderate because of different obsolescence patterns between downloads and citations.

Keywords: Articles, Citation, Citations, Cited Half-Life, Comparison, Impact, Impact Factor, Indicators, Journal, Journal Impact, Journal Impact Factor, Journal Metrics, Journals, Metrics, Obsolescence, Oncology, Sci, Science, Scopus, Usage Half-Life, Usage Impact Factor

? van Eck, N.J., Waltman, L., Noyons, E.C.M. and Buter, R.K. (2010), Automatic term identification for bibliometric mapping. Scientometrics, 82 (3), 581-596.

Full Text: 2010\Scientometrics82, 581.pdf

Abstract: A term map is a map that visualizes the structure of a scientific field by showing the relations between important terms in the field. The terms shown in a term map are usually selected manually with the help of domain experts. Manual term selection has the disadvantages of being subjective and labor-intensive. To overcome these disadvantages, we propose a methodology for automatic term identification and we use this methodology to select the terms to be included in a term map. To evaluate the proposed methodology, we use it to construct a term map of the field of operations research. The quality of the map is assessed by a number of operations research experts. It turns out that in general the proposed methodology performs quite well.

Keywords: Authorship, Automatic Term Identification, Bibliometric, Bibliometric Mapping, Citation Patterns, Mapping, Maps, Operational-Research, Operations Research, Probabilistic Latent Semantic Analysis, Research, Science, Term Map

? Zhou, P. and Glänzel, W. (2010), In-depth analysis on China’s international cooperation in science. Scientometrics, 82 (3), 597-612.

Full Text: 2010\Scientometrics82, 597.pdf

Abstract: It has been about 30 years since China adopted an open-up and reform policy for global competition and collaboration. This opening-up policy is accompanied by a spectacular growth of the country’s economy as well as visibility in the world’s scientific literature. Also China’ competitiveness in scientific research has grown, and is mirroring the development of the country’s economy. On the other hand, international collaboration of most countries dramatically increased during the last two decades and accompanied the growth of science in emerging economies. Thus the question arises of whether growth of competitiveness in research is accompanied by an intensification of collaboration in China as well. In the present study we analyse the dynamics and the national characteristics of China’s co-operation in a global context. We also study research profile and citation impact of international collaboration with respect to the corresponding domestic ‘standards’.

Keywords: Brazil, Characteristics, China, Citation, Citation Impact, Co-Authorship, Collaboration, Competition, Global, Growth, Impact, International Collaboration, International Cooperation, Literature, Research, Research Profile, Science, Scientific Literature, Scientific Research, Standards, Subject Normalisation, Subject Profiles, Visibility, World

? Boell, S.K. and Wilson, C.S. (2010), Journal Impact Factors for evaluating scientific performance: Use of h-like indicators. Scientometrics, 82 (3), 613-626.

Full Text: 2010\Scientometrics82, 613.pdf

Abstract: This article introduces the Impact Factor squared or IF2-index, an h-like indicator of research performance. This indicator reflects the degree to which large entities such as countries and/or their states participate in top-level research in a field or subfield. The IF2-index uses the Journal Impact Factor (JIF) of research publications instead of the number of citations. This concept is applied to other h-type indexes and their results compared to the IF2-index. These JIF-based indexes are then used to assess the overall performance of cancer research in Australia and its states over 8 years from 1999 to 2006. The IF2-index has three advantages when evaluating larger research units: firstly, it provides a stable value that does not change over time, reflecting the degree to which a research unit participated in top-level research in a given year, secondly, it can be calculated closely approximating the publication date of yearly datasets, and finally, it provides an additional dimension when a full article-based citation analysis is not feasible. As the index reflects the degree of participation in top-level research it may favor larger units when units of different sizes are compared.

Keywords: A-Index, Australia, Bibliometric Indicators, Cancer, Cancer Research, Citation, Citation Analysis, Citations, h-Index, h-Like Indexes, H-Type Indexes, Hirsch-Type Indexes, IF2-Index, Impact, Impact Factor, Indicators, Journal Impact Factor, Level, Publication, Publications, Quality, R-Index, Research, Research Evaluation, Research Performance, Researchers, Scientific Performance, Scientometrics

? Jovanovic, M.M., John, M. and Reschke, S. (2010), Effects of civil war: Scientific cooperation in the republics of the former Yugoslavia and the province of Kosovo. Scientometrics, 82 (3), 627-645.

Full Text: 2010\Scientometrics82, 627.pdf

Abstract: In this study we investigate the scientific output of Yugoslavia and its successor republics viz. Serbia, Croatia, Slovenia, Bosnia & Herzegovina, Macedonia and Montenegro. Additionally, Kosovo was included as a separate entity, since it recently declared its independence. The publications and cooperation between the republics are analyzed for the years from 1970 until 2007. In contrast to similar studies, we examine a larger time window and take into consideration not only the three big republics (Serbia, Croatia, and Slovenia) but also include the smaller ones, namely Bosnia & Herzegovina, Macedonia and Montenegro. For our analysis we introduce two new indicators: the normalized cooperation score (R-i((cs)))and the dominance factor (D-i((c))), a measure of dominance within a weighted network. Furthermore, we develop and assess the reliability of various techniques for visualizing our findings. We found that the civil wars had a severe impact on the inner-Yugoslav cooperation network. Additionally it seems, as if with the ending of the conflicts a process of recovery started.

Keywords: Bibliometrics, Cooperation Analysis, Croatia, Dominance Factor, Impact, Impact of Social Crises, Indicators, Journals, Network Analysis, Publications, Recovery, Reliability, Science, Scientific Cooperation, Scientific Output, Techniques, Yugoslavia

? Laurens, P., Zitt, M. and Bassecoulard, E. (2010), Delineation of the genomics field by hybrid citation-lexical methods: interaction with experts and validation process. Scientometrics,