A Visual Analytic Observatory of Scientific Knowledge

科学知识的可视化分析观测站

• 批准号: 1633286
• 负责人: Chaomei Chen
• 金额: $ 38.18万
• 依托单位: Drexel University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-01 至 2020-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1633286&HistoricalAwards=false
• 关键词: Visual; Analytic; Observatory; Scientific; Knowledge

This project increase the accessibility of scientific knowledge by creating a cross-referenced repository of scientific assertions, metrics and indicators of research impact and trends, and tools for accessing and exploring scientific knowledge. The project expands the scope of the study of scientific knowledge by directly addressing the integral role of uncertainties and discrepancies in understanding and communicating scientific knowledge. The observatory tracks how a scientific assertion evolves over time in the scientific literature. The project advances the capabilities of the study of scientific knowledge by providing references so that researchers can routinely and systematically compare and evaluate metrics and algorithms designed to capture the impact of scientific contributions. The increased accessibility of scientific knowledge improves research productivity as well as the understanding of science and relevant policies.The project represents scientific knowledge as a semantically organized and adaptive network of scientific assertions, structures of reasoning and argumentation, and relevant evidence extracted from the growing body of scientific literature. Extracted concepts, semantic relations, and argumentative structures are synthesized across scientific publications using techniques from machine learning, computational linguistics, quantitative studies of science, and visual analytics. In addition, uncertainties and discrepancies associated with scientific assertions and their impacts are identified and cross-referenced in the repository so as to keep track of their evolution over time. Existing and newly developed metrics and indicators of research impact are linked directly to assertion-level evidence and patterns. The observatory serves as a sustainable platform for researchers and tool developers to access scientific knowledge and relevant resources for conducting their own studies and evaluating the quality of new metrics and algorithms in the broad context of the science of science and innovation policy research.

该项目通过创建一个交叉引用的科学断言、研究影响和趋势的度量和指标以及获取和探索科学知识的工具库，增加了科学知识的可获取性。该项目通过直接探讨不确定性和差异在理解和传播科学知识方面的整体作用，扩大了科学知识研究的范围。天文台跟踪科学文献中科学论断如何随时间演变。该项目通过提供参考资料提高了科学知识研究的能力，使研究人员能够经常和系统地比较和评估旨在捕捉科学贡献影响的指标和算法。科学知识的普及提高了研究生产力，也提高了对科学和相关政策的理解，该项目将科学知识描述为科学断言、推理和论证结构以及从越来越多的科学文献中提取的相关证据的语义组织和适应性网络。提取的概念，语义关系和论证结构是使用机器学习，计算语言学，科学的定量研究和可视化分析技术在科学出版物中合成的。此外，与科学断言及其影响相关的不确定性和差异也在知识库中得到确认和交叉引用，以便跟踪其随时间的演变。现有的和新开发的研究影响的度量和指标直接与断言级证据和模式相关联。 该观测站是研究人员和工具开发人员获取科学知识和相关资源的可持续平台，以便在科学学和创新政策研究的广泛背景下开展自己的研究并评估新指标和算法的质量。

项目成果

Cascading Citation Expansion

• DOI: 10.1633/jistap.2018.6.2.1
• 发表时间: 2018-05
• 期刊: ArXiv
• 作者: Chaomei Chen

A scalable and adaptive method for finding semantically equivalent cue words of uncertainty

• DOI: 10.1016/j.joi.2017.12.004
• 发表时间: 2018-02-01
• 期刊: JOURNAL OF INFORMETRICS
• 影响因子: 3.7
• 作者: Chen, Chaomei;Song, Min;Heo, Go Eun
• 通讯作者: Heo, Go Eun

LitStoryTeller+: an interactive system for multi-level scientific paper visual storytelling with a supportive text mining toolbox

LitStoryTeller：一个用于多层次科学论文视觉叙事的交互式系统，具有支持性文本挖掘工具箱

• DOI: 10.1007/s11192-018-2803-x
• 发表时间: 2018
• 期刊: Scientometrics
• 影响因子: 3.9
• 作者: Ping, Qing;Chen, Chaomei
• 通讯作者: Chen, Chaomei

Visualizing a field of research: A methodology of systematic scientometric reviews

• DOI: 10.1371/journal.pone.0223994
• 发表时间: 2019-10-31
• 期刊: PLOS ONE
• 影响因子: 3.7
• 作者: Chen, Chaomei;Song, Min
• 通讯作者: Song, Min

PaperPoles: Facilitating adaptive visual exploration of scientific publications by citation links

• DOI: 10.1002/asi.24171
• 发表时间: 2019-02
• 期刊: Journal of the Association for Information Science and Technology
• 影响因子: 3.5
• 作者: Jiangen He;Q. Ping;Wen Lou;Chaomei Chen