Differences in Impact Factor Across Fields and Over Time

The bibliometric measure impact factor is a leading indicator of journal influence, and impact factors are routinely used in making decisions ranging from selecting journal subscriptions to allocating research funding to deciding tenure cases. Yet journal impact factors have increased gradually over time, and moreover impact factors vary widely across academic disciplines. Here we quantify inflation over time and differences across fields in impact factor scores and determine the sources of these differences. We find that the average number of citations in reference lists has increased gradually, and this is the predominant factor responsible for the inflation of impact factor scores over time. Field-specific variation in the fraction of citations to literature indexed by Thomson Scientific's Journal Citation Reports is the single greatest contributor to differences among the impact factors of journals in different fields. The growth rate of the scientific literature as a whole, and cross-field differences in net size and growth rate of individual fields, have had very little influence on impact factor inflation or on cross-field differences in impact factor.Comment: 9 pages, 3 figure

The strike rate index: a new index for journal quality based on journal size and the h-index of citations

Quantifying the impact of scientific research is almost always controversial, and there is a need for a uniform method that can be applied across all fields. Increasingly, however, the quantification has been summed up in the impact factor of the journal in which the work is published, which is known to show differences between fields. Here the h-index, a way to summarize an individual's highly cited work, was calculated for journals over a twenty year time span and compared to the size of the journal in four fields, Agriculture, Condensed Matter Physics, Genetics and Heredity and Mathematical Physics. There is a linear log-log relationship between the h-index and the size of the journal: the larger the journal, the more likely it is to have a high h-index. The four fields cannot be separated from each other suggesting that this relationship applies to all fields. A strike rate index (SRI) based on the log relationship of the h-index and the size of the journal shows a similar distribution in the four fields, with similar thresholds for quality, allowing journals across diverse fields to be compared to each other. The SRI explains more than four times the variation in citation counts compared to the impact factor

Acknowledgement Lag and Impact: Domain Differences in Published Research Supported by the National Science Foundation

This research combined archives of grant awards with a five-year period of bibliographic data from Web of Science in order to conduct an input-output study of research supported by the National Science Foundation. Acknowledgement lag is proposed as a new bibliometric term, defined as the time elapsed between when a grant is awarded and when a document is published which acknowledges that award. Acknowledgement lag was computed for the dataset, and domain differences in lag times were analyzed. Some areas, such as Plant & Animal Science or Social Science, were found to be more likely than other categories to acknowledge a grant seven or more years later, while other categories, such as Physics, were most likely to publish a grant acknowledgement in two years or less. In addition, rank-normalized impact factors were computed for journals in which these articles were published, as a measure of journal impact that is comparable across categories of research. The overall distribution of ranknormalized journal impact factors for research articles acknowledging support by the National Science Foundation was analyzed. Category-level analysis was also performed, and it was found that there were differences in the journal impact factor trends for publications from different domains in the dataset. Research in Materials Science was substantially more likely than other categories to publish in the most elite journals of its respective domain. Social Sciences research was also found to be one of the strongest research areas in terms of impact factor, despite being one of the smaller categories in terms of publication counts. However, other categories were found to be disproportionately more likely to have been published in lower impact factor journals for their respective fields, such as Mathematics and Computer Science. The methodology developed in this project demonstrates a workflow that could be implemented by the NSF or other agencies. The findings demonstrate that systematically linking grants to publications can yield information of strategic value, allowing agencies to better understand field differences in outcomes and providing a means for tracking changes in publication-related metrics over time

A review of the characteristics of 108 author-level bibliometric indicators

An increasing demand for bibliometric assessment of individuals has led to a growth of new bibliometric indicators as well as new variants or combinations of established ones. The aim of this review is to contribute with objective facts about the usefulness of bibliometric indicators of the effects of publication activity at the individual level. This paper reviews 108 indicators that can potentially be used to measure performance on the individual author level, and examines the complexity of their calculations in relation to what they are supposed to reflect and ease of end-user application.Comment: to be published in Scientometrics, 201

The Effect of Gender in the Publication Patterns in Mathematics

Despite the increasing number of women graduating in mathematics, a systemic gender imbalance persists and is signified by a pronounced gender gap in the distribution of active researchers and professors. Especially at the level of university faculty, women mathematicians continue being drastically underrepresented, decades after the first affirmative action measures have been put into place. A solid publication record is of paramount importance for securing permanent positions. Thus, the question arises whether the publication patterns of men and women mathematicians differ in a significant way. Making use of the zbMATH database, one of the most comprehensive metadata sources on mathematical publications, we analyze the scholarly output of ~150,000 mathematicians from the past four decades whose gender we algorithmically inferred. We focus on development over time, collaboration through coautorships, presumed journal quality and distribution of research topics -- factors known to have a strong impact on job perspectives. We report significant differences between genders which may put women at a disadvantage when pursuing an academic career in mathematics.Comment: 24 pages, 12 figure

Advanced InSAR atmospheric correction: MERIS/MODIS combination and stacked water vapour models

A major source of error for repeat-pass Interferometric Synthetic Aperture Radar (InSAR) is the phase delay in radio signal propagation through the atmosphere (especially the part due to tropospheric water vapour). Based on experience with the Global Positioning System (GPS)/Moderate Resolution Imaging Spectroradiometer (MODIS) integrated model and the Medium Resolution Imaging Spectrometer (MERIS) correction model, two new advanced InSAR water vapour correction models are demonstrated using both MERIS and MODIS data: (1) the MERIS/MODIS combination correction model (MMCC); and (2) the MERIS/MODIS stacked correction model (MMSC). The applications of both the MMCC and MMSC models to ENVISAT Advanced Synthetic Aperture Radar (ASAR) data over the Southern California Integrated GPS Network (SCIGN) region showed a significant reduction in water vapour effects on ASAR interferograms, with the root mean square (RMS) differences between GPS- and InSAR-derived range changes in the line-of-sight (LOS) direction decreasing from ,10mm before correction to ,5mm after correction, which is similar to the GPS/MODIS integrated and MERIS correction models. It is expected that these two advanced water vapour correction models can expand the application of MERIS and MODIS data for InSAR atmospheric correction. A simple but effective approach has been developed to destripe Terra MODIS images contaminated by radiometric calibration errors. Another two limiting factors on the MMCC and MMSC models have also been investigated in this paper: (1) the impact of the time difference between MODIS and SAR data; and (2) the frequency of cloud-free conditions at the global scale