13 research outputs found
The use of bibliometrics for assessing research : possibilities, limitations and adverse effects
Researchers are used to being evaluated: publications, hiring, tenure and funding decisions are all based on the evaluation of research. Traditionally, this evaluation relied on judgement of peers but, in the light of limited resources and increased bureaucratization of science, peer review is getting more and more replaced or complemented with bibliometric methods. Central to the introduction of bibliometrics in research evaluation was the creation of the Science Citation Index (SCI)in the 1960s, a citation database initially developed for the retrieval of scientific information. Embedded in this database was the Impact Factor, first used as a tool for the selection of journals to cover in the SCI, which then became a synonym for journal quality and academic prestige. Over the last 10 years, this indicator became powerful enough to influence researchers’ publication patterns in so far as it became one of the most important criteria to select a publication venue. Regardless of its many flaws as a journal metric and its inadequacy as a predictor of citations on the paper level, it became the go-to indicator of research quality and was used and misused by authors, editors, publishers and research policy makers alike. The h-index, introduced as an indicator of both output and impact combined in one simple number, has experienced a similar fate, mainly due to simplicity and availability. Despite their massive use, these measures are too simple to capture the complexity and multiple dimensions of research output and impact. This chapter provides an overview of bibliometric methods, from the development of citation indexing as a tool for information retrieval to its application in research evaluation, and discusses their misuse and effects on researchers’ scholarly communication behavior
Evolution of scaling emergence in large-scale spatial epidemic spreading
Background: Zipf's law and Heaps' law are two representatives of the scaling
concepts, which play a significant role in the study of complexity science. The
coexistence of the Zipf's law and the Heaps' law motivates different
understandings on the dependence between these two scalings, which is still
hardly been clarified.
Methodology/Principal Findings: In this article, we observe an evolution
process of the scalings: the Zipf's law and the Heaps' law are naturally shaped
to coexist at the initial time, while the crossover comes with the emergence of
their inconsistency at the larger time before reaching a stable state, where
the Heaps' law still exists with the disappearance of strict Zipf's law. Such
findings are illustrated with a scenario of large-scale spatial epidemic
spreading, and the empirical results of pandemic disease support a universal
analysis of the relation between the two laws regardless of the biological
details of disease. Employing the United States(U.S.) domestic air
transportation and demographic data to construct a metapopulation model for
simulating the pandemic spread at the U.S. country level, we uncover that the
broad heterogeneity of the infrastructure plays a key role in the evolution of
scaling emergence.
Conclusions/Significance: The analyses of large-scale spatial epidemic
spreading help understand the temporal evolution of scalings, indicating the
coexistence of the Zipf's law and the Heaps' law depends on the collective
dynamics of epidemic processes, and the heterogeneity of epidemic spread
indicates the significance of performing targeted containment strategies at the
early time of a pandemic disease.Comment: 24pages, 7figures, accepted by PLoS ON
In vitro studies on interaction of 4-hydroperoxyifosfamide and 2-mercaptoethanesulphonate in malignant gliomas
Development of a Scale to Measure the Quality of Mobile Location-Based Services
Mobile location-based service (m-LBS) presents attractive business opportunities for various companies. Recent improvements of technologies have resulted in a dramatic growth of m-LBSs. However, development of scales for evaluating the m-LBS quality has scarcely been addressed. This study aims to develop a new scale applicable to evaluating m-LBS quality. The scale was qualitatively designed at first, and the designed scale was assessed with a total number of 281 responded survey data. As a result, an m-LBS quality scale was developed, which consists of 9 quality dimensions and 29 measurement items. The distinctive characteristic of m-LBS is captured by a newly defined dimension called “localization” and its three measurement items (namely organization, update, and inclusiveness). The proposed scale was shown to be statistically reliable and valid. The results of this study would significantly contribute to providing a valid scale for use in measuring the m-LBS quality.11Nssciscopu