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Data Analysis and Knowledge Discovery  2023, Vol. 7 Issue (5): 10-20    DOI: 10.11925/infotech.2096-3467.2022.0627
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Analyzing Evolution of Basic Research Funding Orientation: Case Study of NSF
Wei Huanan,Lei Ming,Wang Xuefeng(),Yu Yin
School of Management and Economics, Beijing Institute of Technology, Beijing 100081, China
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Abstract  

[Objective] This paper identifies and analyzes the funding orientation of basic research projects funded in the United States, aiming to provide suggestions for improving the funding layout of science funds in China. [Methods] Based on the literature review, we established a feature system for identifying funding orientation from four dimensions: basic information, collaborative characteristics, project characteristics, and output characteristics. Then, we constructed a recognition model with the help of machine learning. Finally, we conducted the corresponding evolution analysis. [Results] The SVM model with an RBF kernel had a better identification effect. The case analysis of synthetic biology showed that the NSF balanced “free exploration” and “demand-oriented”. The basic research of “free exploration” was consistent throughout. In contrast, the basic research of “demand-oriented” was relatively scarce in the early stages, gradually increasing with the development of the field. Changes in the two funding orientations are closely related to the development stage of the discipline and the national strategic policies. [Limitations] We only chose one field for case analysis, which lacked representativeness. We only included NSF project data and did not include NIH, FDA, and other data, so the comprehensiveness of the data source needs to be strengthened. [Conclusions] This study is a valuable exploration of identifying basic research funding orientation. By identifying and analyzing the funding orientation of NSF projects in synthetic biology, this study can provide suggestions for the funding layout of NSFC in China and promote the coordinated development of basic research in China.
Key words： Basic Research      Funding-Oriented Identification      Machine Learning      Synthetic Biology      NSF     
Received: 17 June 2022      Published: 04 July 2023
ZTFLH:  TP393  
  G250  
Corresponding Authors: Wang Xuefeng，ORCID：0000-0002-4857-6944，E-mail：wxf5122@bit.edu.cn。   
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Huanan Wei
Ming Lei
Xuefeng Wang
Yin Yu

Cite this article:

Wei Huanan, Lei Ming, Wang Xuefeng, Yu Yin. Analyzing Evolution of Basic Research Funding Orientation: Case Study of NSF. Data Analysis and Knowledge Discovery, 2023, 7(5): 10-20.

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https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.2096-3467.2022.0627     OR     https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2023/V7/I5/10

The Tree Diagram of Characterization Study
Analysis of Cooperative Characteristics
The Process of Model Building
术语 示例
社会问题 全球甲烷排放量过高导致气候的变化，对该问题进行解决或缓解等
重大事件 应对新型冠状病毒危机研究检测和治疗方法、发生原油泄露事件后研究应对策略等
大型仪器 开发医学检测仪器等
基础平台 建立药物输送平台、建立基因元件库、开发微分平台等
重大设备 开发新的图像分析和纳米级机械设备等
治疗疾病 开发治疗特定癌症的药物或技术等
商业化应用 降低药物成本、优化药物生产流程、提高环境友好型包装材料产量等
公众传播 让高中生和教师了解并扩大对合成生物学在个人、健康和食品生产环境中、在生物工程中的作用的理解和看法，提高他们的兴趣，从而参与合成生物学活动等
研究培训 在2012-2014年夏季为8名学生提供为期10周的研究培训
Terminology and Related Examples
序号 特征信息 字段名称 字段类型 备注
1 基本信息 项目持续时间 有序数据 以月份为单位
2 基本信息 项目资助金额 有序数据 将金额分为10个等级
3 合作特征 Co-PI数量 有序数据 0， 1， 2， …
4 合作特征 是否为合作项目 分类数据 0/1
5 项目特征 项目所属学部 分类数据 BIO、CISE、HER、ENG、GEO、MPS、OD、SBE
6 项目特征 计划数量 有序数据 1， 2， 3， …
7 项目特征 主要计划 分类数据 资助计划中的第一个计划
8 项目特征 计划信息 高维稀疏向量 272维
9 项目特征 依托单位类型 分类数据 高校、科研院所、医院、企业、会议、学会、国家科学院、其它
10 项目特征 项目资助类型 分类数据 Standard Grant、Continuing Grant、Cooperative Agreement、Fellowship
11 产出特征 项目产出论文数量 有序数据 需要和已执行年度联合起来看
12 产出特征 项目已执行年份 有序数据 1， 2， 3， …
Input Field Information
序号 字段 重要
性值		 序号 字段 重要
性值
1 主要计划（No.1） 1.000 9 是否合作研究 0.965
2 资助金额 1.000 10 产出论文数量 0.930
3 持续时间（月） 1.000 11 $F-因子-2 0.891
4 NSF学部 1.000 12 $F-因子-3 0.745
5 已执行年度 1.000 13 计划数量 0.663
6 机构类型 1.000 14 $F-因子-1 0.596
7 资助类型 1.000 15 $F-因子-4 0.578
8 Co-PI数量 0.991 16 $F-因子-5 0.375
Characteristic Fields of Model Input
字段范围 训练集准确率/% 测试集准确率/%
重要程度大于0.5 82.49 81.19
重要程度大于0.6 82.81 83.06
重要程度大于0.7 82.53 82.86
重要程度大于0.8 82.37 81.96
重要程度大于0.9 81.37 81.33
Model Accuracy under Different Field
模型 算法 训练集 测试集 验证集
正确率/
%		 AUC 正确率/
%		 AUC 正确率/
%		 AUC
SVM 线性 82.81 0.894 83.06 0.882 80.78 0.885
RBF 83.92 0.909 85.13 0.913 80.37 0.887
多项式 83.90 0.851 84.05 0.874 83.33 0.835
C5.0 Boosting 82.34 0.876 83.82 0.884 86.22 0.894
Comparison of Four Model Algorithms
资助导向 项目数量
自由探索 649
需求导向 977
Funding-Oriented Distribution
Annual Trends of Basic Research Projects of Two Funding-Oriented
Evolution of Basic Research Projects of Two Funding-Oriented
Distribution of Basic Research Projects of Two Funding-Oriented
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