Category Archives: Funding

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

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.

FULL-TEXT at http://dx.doi.org/10.1371/journal.pone.0154509

Author(s): Ying Huang, Yi Zhang, Jan Youtie, Alan L. Porter, Xuefeng Wang
Organization(s): Beijing Institute of Technology; Georgia Institute of Technology
Source: PLoS ONE
Year: 2016

Funding Data from Publication Acknowledgements: Coverage, Uses and Limitations

This article contributes to the development of methods for analysing research funding systems by exploring the robustness and comparability of emerging approaches to generate funding landscapes useful for policy making. We use a novel dataset of manually extracted and coded data on the funding acknowledgements of 7,510 publications representing UK cancer research in the year 2011 and compare these ‘reference data’ with funding data provided by Web of Science (WoS) and MEDLINE/PubMed. Findings show high recall (about 93%) of WoS funding data. By contrast, MEDLINE/PubMed data retrieved less than half of the UK cancer publications acknowledging at least one funder. Conversely, both databases have high precision (+90%): i.e. few cases of publications with no acknowledgement to funders are identified as having funding data. Nonetheless, funders acknowledged in UK cancer publications were not correctly listed by MEDLINE/PubMed and WoS in about 75% and 32% of the cases, respectively. ‘Reference data’ on the UK cancer research funding system are then used as a case-study to demonstrate the utility of funding data for strategic intelligence applications (e.g. mapping of funding landscape, comparison of funders’ research portfolios).

FULL-TEXT at http://arxiv.org/pdf/1604.04896.pdf

Author(s): Nicola Grassano, Daniele Rotolo, Joshua Hutton, Frederique Lang, and Michael M. Hopkins
Organization(s): Science Policy Research Unit (SPRU), University of Sussex
Source: Journal of the Association for Information Science and Technology
Year: 2016

Topic analysis and forecasting for science, technology and innovation: Methodology with a case study focusing on big data research

Highlights

  • Data-driven clustering approach to group topics with high accuracy
  • Similarity measure approach to trace the interaction between topics in time series
  • Analyzing changes of TFIDF values of related topics to predict future trends
  • Technology Roadmapping to blend historical analysis and expert-based forecasting

The number and extent of current Science, Technology & Innovation topics are changing all the time, and their induced accumulative innovation, or even disruptive revolution, will heavily influence the whole of society in the near future. By addressing and predicting these changes, this paper proposes an analytic method to (1) cluster associated terms and phrases to constitute meaningful technological topics and their interactions, and (2) identify changing topical emphases. Our results are carried forward to present mechanisms that forecast prospective developments using Technology Roadmapping, combining qualitative and quantitative methodologies. An empirical case study of Awards data from the United States National Science Foundation, Division of Computer and Communication Foundation, is performed to demonstrate the proposed method. The resulting knowledge may hold interest for R&D management and science policy in practice.

http://www.sciencedirect.com/science/article/pii/S0040162516000160

Author(s): Yi Zhang, Guangquan Zhang, Hongshu Chen, Alan L. Porter, Donghua Zhu, Jie Lu
Organization(s): University of Technology Sydney, Georgia Institute of Technology, Beijing Institute of Technology
Source: Technological Forecasting and Social Change
Year: 2016

The Impact of Research Funding on Scientific Outputs: Evidence from Six Smaller European Countries

We investigate the relationships between the citation impacts of scientific papers and the sources of funding which are acknowledged as having supported those publications. We examine several relationships potentially associated with funding including first citation, total citations and the chances of becoming highly cited. Furthermore, we explore evidence on the links between citations and types of funding by organization and also with combined measures of funding. In particular, we examine the relationship between funding intensity and funding variety and citation. Our empirical work focuses on six small advanced European economies, applying a zero inflated negative binomial model to a set of more than 240,000 papers authored by researchers from these countries. We find that funding is not related to the first citation but is significantly related to the number of citations and top percentile citation impact. Additionally, we find that citation impact is positively related to funding variety and negatively related with funding intensity. Finally there is an inverse relationship between the relative frequency of funding and citation impact. The results presented in the paper raise insights for the design of research programs and the structure of research funding and for the behavior and strategies of researchers and sponsoring organizations.

Open Access escholar

Author(s): Abdullah Gök, John Rigby, Philip Shapira
Organization(s): MIoIR Manchester University
Source: Journal of the American Society for Information Science and Technology
Year: 2014

Upgrading the Quality of Science: Does Funding Source Matter?

Extended Abstract – MINING NOVEL DATA SOURCES session at “1st Global TechMining Conference” 2011

Author(s): Abdullah Gök and Philip Shapira (University of Manchester)

This paper examines the effect of differential and multiple funding on the quality of science in the Czech Republic. We explore several propositions. Firstly, we investigate whether European Union research sponsorship is changing the field orientation of Czech science, compared with the structural long-term trend of change since 1980. Secondly, we ask whether the European Union research sponsorship has had a positive influence on the quality of Czech scientific papers compared with other national and international funding sources. Our measures of quality include accrued citations and journal impact factors. Continue reading Upgrading the Quality of Science: Does Funding Source Matter?

Funding Acknowledgement Analysis – An Enhanced Tool to Investigate Research Sponsorship Impacts

Extended Abstract – MINING NOVEL DATA SOURCES   session at “1st Global TechMining Conference” 2011

Author(s): Jue Wang (Florida International University) and Philip Shapira (University of Manchester)

There is increasing interest in assessing how sponsored research funding influences the development and trajectory of science and technology. Traditionally, linkages between research funding and subsequent results are hard to track, often requiring access to separate funding or performance reports released by researchers or sponsors. Tracing research sponsorship and output linkages is even more challenging when researchers receive multiple funding awards and collaborate with a variety of differentially-sponsored research colleagues. Continue reading Funding Acknowledgement Analysis – An Enhanced Tool to Investigate Research Sponsorship Impacts