Dataset Information

Determining scientific impact using a collaboration index.

ABSTRACT: Researchers collaborate on scientific projects that are often measured by both the quantity and the quality of the resultant peer-reviewed publications. However, not all collaborators contribute to these publications equally, making metrics such as the total number of publications and the H-index insufficient measurements of individual scientific impact. To remedy this, we use an axiomatic approach to assign relative credits to the coauthors of a given paper, referred to as the A-index for its axiomatic foundation. In this paper, we use the A-index to compute the weighted sums of peer-reviewed publications and journal impact factors, denoted as the C- and P-indexes for collaboration and productivity, respectively. We perform an in-depth analysis of bibliometric data for 186 biomedical engineering faculty members and from extensive simulation. It is found that these axiomatically weighted indexes better capture a researcher's scientific caliber than do the total number of publications and the H-index, allowing for fairer and sharper evaluation of researchers with diverse collaborative behaviors.

SUBMITTER: Stallings J

PROVIDER: S-EPMC3683734 | biostudies-literature | 2013 Jun

REPOSITORIES: biostudies-literature

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Determining scientific impact using a collaboration index.

Stallings Jonathan J Vance Eric E Yang Jiansheng J Vannier Michael W MW Liang Jimin J Pang Liaojun L Dai Liang L Ye Ivan I Wang Ge G

Proceedings of the National Academy of Sciences of the United States of America 20130529 24

Researchers collaborate on scientific projects that are often measured by both the quantity and the quality of the resultant peer-reviewed publications. However, not all collaborators contribute to these publications equally, making metrics such as the total number of publications and the H-index insufficient measurements of individual scientific impact. To remedy this, we use an axiomatic approach to assign relative credits to the coauthors of a given paper, referred to as the A-index for its a ...[more]

PMID: 23720314

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Project description:BACKGROUND:Alzheimer's disease neuroimaging initiative (ADNI) is a landmark imaging and omics study in AD. ADNI research literature has increased substantially over the past decade, which poses challenges for effectively communicating information about the results and impact of ADNI-related studies. In this work, we employed advanced information visualization techniques to perform a comprehensive and systematic mapping of the ADNI scientific growth and impact over a period of 12 years. METHODS:Citation information of ADNI-related publications from 01/01/2003 to 05/12/2015 were downloaded from the Scopus database. Five fields, including authors, years, affiliations, sources (journals), and keywords, were extracted and preprocessed. Statistical analyses were performed on basic publication data as well as journal and citations information. Science mapping workflows were conducted using the Science of Science (Sci2) Tool to generate geospatial, topical, and collaboration visualizations at the micro (individual) to macro (global) levels such as geospatial layouts of institutional collaboration networks, keyword co-occurrence networks, and author collaboration networks evolving over time. RESULTS:During the studied period, 996 ADNI manuscripts were published across 233 journals and conference proceedings. The number of publications grew linearly from 2008 to 2015, so did the number of involved institutions. ADNI publications received much more citations than typical papers from the same set of journals. Collaborations were visualized at multiple levels, including authors, institutions, and research areas. The evolution of key ADNI research topics was also plotted over the studied period. CONCLUSIONS:Both statistical and visualization results demonstrate the increasing attention of ADNI research, strong citation impact of ADNI publications, the expanding collaboration networks among researchers, institutions and ADNI core areas, and the dynamic evolution of ADNI research topics. The visualizations presented here can help improve daily decision making based on a deep understanding of existing patterns and trends using proven and replicable data analysis and visualization methods. They have great potential to provide new insights and actionable knowledge for helping translational research in AD.

Project description:Quantifying and comparing the scientific output of researchers has become critical for governments, funding agencies and universities. Comparison by reputation and direct assessment of contributions to the field is no longer possible, as the number of scientists increases and traditional definitions about scientific fields become blurred. The h-index is often used for comparing scientists, but has several well-documented shortcomings. In this paper, we introduce a new index for measuring and comparing the publication records of scientists: the pagerank-index (symbolised as π). The index uses a version of pagerank algorithm and the citation networks of papers in its computation, and is fundamentally different from the existing variants of h-index because it considers not only the number of citations but also the actual impact of each citation. We adapt two approaches to demonstrate the utility of the new index. Firstly, we use a simulation model of a community of authors, whereby we create various 'groups' of authors which are different from each other in inherent publication habits, to show that the pagerank-index is fairer than the existing indices in three distinct scenarios: (i) when authors try to 'massage' their index by publishing papers in low-quality outlets primarily to self-cite other papers (ii) when authors collaborate in large groups in order to obtain more authorships (iii) when authors spend most of their time in producing genuine but low quality publications that would massage their index. Secondly, we undertake two real world case studies: (i) the evolving author community of quantum game theory, as defined by Google Scholar (ii) a snapshot of the high energy physics (HEP) theory research community in arXiv. In both case studies, we find that the list of top authors vary very significantly when h-index and pagerank-index are used for comparison. We show that in both cases, authors who have collaborated in large groups and/or published less impactful papers tend to be comparatively favoured by the h-index, whereas the pagerank-index highlights authors who have made a relatively small number of definitive contributions, or written papers which served to highlight the link between diverse disciplines, or typically worked in smaller groups. Thus, we argue that the pagerank-index is an inherently fairer and more nuanced metric to quantify the publication records of scientists compared to existing measures.

Project description:BackgroundThe European & Developing Countries Clinical Trials Partnership (EDCTP), like many other research funders, requires its grantees to make papers available via open access (OA). This article investigates the effect of publishing in OA journals and international collaboration within and between European and sub-Saharan African countries on citation impact and likelihood of falling into the top 1% and top 10% most cited papers in poverty-related disease (PRD) research.MethodsDisease-specific research publications were identified in the Web of Science™ and MEDLINE using Medical Subject Heading (MeSH) terms. Data on the open accessibility of scientific literature were derived from 1science oaFindr. Publication data, including relative citation counts, were extracted for 2003-2015. Regression models were applied to quantify the relationship between relative citations and presence in the 1% and top 10% most cited papers versus OA and international collaboration.ResultsThe results show that since 2003 papers on PRDs have become increasingly available in OA. Among all PRD areas, malaria research is most frequently published in OA and in international collaboration. The adjusted regression analyses show that holding other factors constant, publishing research in OA and in international collaboration has a significant and meaningful citation advantage over non-OA or non-international collaborative research. Publishing papers as part of a European-wide or European- sub-Saharan African collaboration increases research impact. In contrast, such collaboration advantage is not observed for research output involving sub-Saharan Africa only which seems to decrease research impact.ConclusionsOur results indicate that there is a real, measurable citation advantage for publishing PRD research in OA and international collaboration. However, the international collaboration advantage seems to be region-specific with increased research impact for European-wide and European-sub-Saharan African collaborations but a decrease in research impact of collaborations confined to sub-Saharan African research institutions. Further research is required to further verify this finding and to understand the underlying factors related to this observed decrease in research impact. To target future research capacity building activities in sub-Saharan Africa it is important to assess whether the observed decreased impact reflects the scientific competencies and geographic distribution of individual researchers or institutional-, national- or funder-specific research requirements.

Dataset Information

Determining scientific impact using a collaboration index.

Publications

Determining scientific impact using a collaboration index.

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