Funding the Frontier: Visualizing the Broad Impact of Science and Science Funding

📅 2025-09-19
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🤖 AI Summary
How can the broad societal impact of scientific funding be quantified and visualized to inform funding decisions? This study develops the first end-to-end visual analytics system integrating heterogeneous data—including 7 million funded projects, 140 million scholarly publications, and 160 million patents—to enable multidimensional impact analysis. The method combines citation-based relational network modeling, downstream impact prediction, and collaborative interactive visualization. It establishes, for the first time, a traceable causal chain linking research funding → scientific outputs → societal impact. By bridging science of science and visual analytics, this work pioneers a novel interdisciplinary methodology. Validated through multiple real-world case studies and expert evaluation, the system demonstrably enhances funders’ ability to assess both the return on research investment and its broader societal value.

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📝 Abstract
Understanding the broad impact of science and science funding is critical to ensuring that science investments and policies align with societal needs. Existing research links science funding to the output of scientific publications but largely leaves out the downstream uses of science and the myriad ways in which investing in science may impact human society. As funders seek to allocate scarce funding resources across a complex research landscape, there is an urgent need for informative and transparent tools that allow for comprehensive assessments and visualization of the impact of funding. Here we present Funding the Frontier (FtF), a visual analysis system for researchers, funders, policymakers, university leaders, and the broad public to analyze multidimensional impacts of funding and make informed decisions regarding research investments and opportunities. The system is built on a massive data collection that connects 7M research grants to 140M scientific publications, 160M patents, 10.9M policy documents, 800K clinical trials, and 5.8M newsfeeds, with 1.8B citation linkages among these entities, systematically linking science funding to its downstream impacts. As such, Funding the Frontier is distinguished by its multifaceted impact analysis framework. The system incorporates diverse impact metrics and predictive models that forecast future investment opportunities into an array of coordinated views, allowing for easy exploration of funding and its outcomes. We evaluate the effectiveness and usability of the system using case studies and expert interviews. Feedback suggests that our system not only fulfills the primary analysis needs of its target users, but the rich datasets of the complex science ecosystem and the proposed analysis framework also open new avenues for both visualization and the science of science research.
Problem

Research questions and friction points this paper is trying to address.

Visualizing broad societal impacts of science funding beyond publications
Creating transparent tools for comprehensive funding impact assessment
Connecting research grants to downstream outputs like patents and policies
Innovation

Methods, ideas, or system contributions that make the work stand out.

Visual analysis system for multidimensional funding impact assessment
Massive dataset connecting grants to publications, patents, and policies
Predictive models and diverse metrics in coordinated visualization framework
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Yifan Qian
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Research Assistant Professor, Kellogg School of Management, Northwestern University
Science of ScienceInnovationComputational Social ScienceNetwork ScienceMachine Learning
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Xiaoyu Qi
Intelligent Big Data Visualization Lab, Tongji University, Shanghai, China
Y
Yian Yin
Department of Information Science, Cornell University, Ithaca, NY , USA
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Shengqi Dang
Intelligent Big Data Visualization Lab, Tongji University, Shanghai, China
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Ziqing Qian
Intelligent Big Data Visualization Lab, Tongji University, Shanghai, China
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Benjamin F. Jones
Center for Science of Science and Innovation, Northwestern University, Evanston, IL, USA
Nan Cao
Nan Cao
Professor, Intelligent Big Data Visualization Lab @ Tongji University
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Dashun Wang
Dashun Wang
Kellogg Chair of Technology, Kellogg School of Management, Northwestern University
Science of ScienceInnovationComputational Social ScienceNetwork ScienceComplex Systems