Practical research proposal and publication profiling

Porter, Alan L.; Schoeneck, David J.; Roessner, David; Garner, Jon

doi:10.3152/095820210x492512

Cited by 16 publications

(3 citation statements)

References 19 publications

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“…In this paper, we apply tech mining [i.e., text mining of science, technology & innovation (ST&I) information to generate useful intelligence] [ 39 ], network analysis, and interdisciplinary assessment methods to understand how NSF and NSFC have ramped-up their funding awards to address the rapid rise of Big Data research. Our particular focus is on research awards rather than scientific articles [ 40 – 43 ]. Our research addresses the following questions about how NSF and NSFC support research in rapidly emerging areas, based on a case study of the emergence of Big Data research:…”

Section: Introductionmentioning

confidence: 99%

How Does National Scientific Funding Support Emerging Interdisciplinary Research: A Comparison Study of Big Data Research in the US and China

et al. 2016

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How do funding agencies ramp-up their capabilities to support research in a rapidly emerging area? This paper addresses this question through a comparison of research proposals awarded by the US National Science Foundation (NSF) and the National Natural Science Foundation of China (NSFC) in the field of Big Data. Big data is characterized by its size and difficulties in capturing, curating, managing and processing it in reasonable periods of time. Although Big Data has its legacy in longstanding information technology research, the field grew very rapidly over a short period. We find that the extent of interdisciplinarity is a key aspect in how these funding agencies address the rise of Big Data. Our results show that both agencies have been able to marshal funding to support Big Data research in multiple areas, but the NSF relies to a greater extent on multi-program funding from different fields. We discuss how these interdisciplinary approaches reflect the research hot-spots and innovation pathways in these two countries.

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Section: Introductionmentioning

confidence: 99%

How Does National Scientific Funding Support Emerging Interdisciplinary Research: A Comparison Study of Big Data Research in the US and China

et al. 2016

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“…Hence, MDS is specifically designed to graphically represent relationships between objects in multidimensional space. Objects are represented on a plot with the new variables as axes, and the relationship between the objects on the plot should represent their underlying dissimilarity (Kodama et al, 2012;Porter et al, 2010).…”

Section: Discussionmentioning

confidence: 99%

Intellectual structure of trust in business and management: a co-citation analysis

Yang

2016

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Purpose In the past few decades, there has been a lot of literature about trust research for business and management. However, few authors have applied co-citation analysis. Design/methodology/approach Trust is one of the most discussed issues in management, as it has proved to have an essential role in business operations. In this study, all citation documents are included in Thomson Reuters ISI Web of Knowledge database from 1992 to 2010. Findings By using statistics analysis including factor analysis, cluster analysis and multidimensional scaling, researchers identified four domains, including organizational behaviour, strategic alliance, marketing and social capital. Directions for future research are discussed. Originality/value This study is the first to apply co-citation techniques in the fields of trust. Therefore, the major contribution of this study is to provide an intellectual structure and trends within the field of trust from an objective and quantitative perspective.

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“…In the past, we and others have cast a variety of analytical and visualization tools to help analyze research attributes (Porter et al, 2010). Such measurement tools fall generally in the category of bibliometrics (De Bellis, 2009), with special note of:…”

Section: Introductionmentioning

confidence: 99%

Measuring and Visualizing Research Collaboration and Productivity

Garner

Porter

Leidolf

et al. 2018

Journal of Data and Information Science

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Purpose This paper presents findings of a quasi-experimental assessment to gauge the research productivity and degree of interdisciplinarity of research center outputs. Of special interest, we share an enriched visualization of research co-authoring patterns. Design/methodology/approach We compile publications by 45 researchers in each of 1) the iUTAH project, which we consider here to be analogous to a “research center,” 2) CG1— a comparison group of participants in two other Utah environmental research centers, and 3) CG2—a comparison group of Utah university environmental researchers not associated with a research center. We draw bibliometric data from Web of Science and from Google Scholar. We gather publications for a period before iUTAH had been established (2010–2012) and a period after (2014–2016). We compare these research outputs in terms of publications and citations thereto. We also measure interdisciplinarity using Integration scoring and generate science overlay maps to locate the research publications across disciplines. Findings We find that participation in the iUTAH project appears to increase research outputs (publications in the After period) and increase research citation rates relative to the comparison group researchers (although CG1 research remains most cited, as it was in the Before period). Most notably, participation in iUTAH markedly increases co-authoring among researchers—in general; and for junior, as well as senior, faculty; for men and women: across organizations; and across disciplines. Research limitations The quasi-experimental design necessarily generates suggestive, not definitively causal, findings because of the imperfect controls. Practical implications This study demonstrates a viable approach for research assessment of a center or program for which random assignment of control groups is not possible. It illustrates use of bibliometric indicators to inform R&D program management. Originality/value New visualizations of researcher collaboration provide compelling comparisons of the extent and nature of social networking among target cohorts.

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Practical research proposal and publication profiling

Cited by 16 publications

References 19 publications

How Does National Scientific Funding Support Emerging Interdisciplinary Research: A Comparison Study of Big Data Research in the US and China

How Does National Scientific Funding Support Emerging Interdisciplinary Research: A Comparison Study of Big Data Research in the US and China

Intellectual structure of trust in business and management: a co-citation analysis

Measuring and Visualizing Research Collaboration and Productivity

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