EAGER: Using the ORCID ID and Emergence Scoring to Study Frontier Researchers

EAGER：使用 ORCID ID 和新兴评分来研究前沿研究人员

• 批准号: 1645237
• 负责人: Alan Porter
• 金额: $ 14.99万
• 依托单位: Search Technology Inc
• 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: 2016-10-01 至 2019-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1645237&HistoricalAwards=false
• 关键词: EAGER; Using; ORCID; ID; Emergence

This project examines the usefulness of the Open Researcher & Contributor ID (ORCID) as a method for identifying journal article authors, and as a basis for detecting emerging scientific topics studied by these authors. Authors of scientific works may use non-standard ways of reporting their names and affiliations in journal articles and other publications, change affiliations over their careers, or have names that are similar to those of other authors. Such variations can make it difficult to correctly match authors with their publications and institutional affiliations. Against an assortment of government or publisher registration methods and machine learning approaches to deal with these problems, ORCID stands out for its potential to extend across methods and nations with its open source approach. Improved capabilities for identifying authors are vital in studying scientific mobility, networks, the contribution of authors to the emergence of new scientific topics, and other subjects in the Science of Science and Innovation Policy domain. More needs to be understood about the strengths and weaknesses in ORCID coverage by country, field, and other areas for it to be useful in Science of Science and Innovation Policy studies.The project uses two bibliometric methods to examine ORCID usage over time and by author characteristics. First, the project uses comparative sampling by disciplinary area, and considers ORCID coverage within country, organization, and citation distribution categories in these disciplinary areas. Second, the project investigates the potential of ORCID in identifying emerging science-driven technologies by employing it in the development of an emergence indicator based on a semi-automated numerical scoring system. The emergence indicator is designed to take topical terms with recent, sharp increases in publication and/or patent activity and examine them in the context of identified scholars to potentially highlight concentrations of research and development activity on emergent fields of science and technology. The resulting intelligence is intended to be useful in informing government, commercial, and academic analyses of leading-edge players and other contributors to rising science and technology domains.

该项目研究了开放研究员贡献者ID（ORCID）作为识别期刊文章作者的方法的有用性，并作为检测这些作者研究的新兴科学主题的基础。 科学作品的作者可能会在期刊文章和其他出版物中使用非标准的方式报告他们的姓名和隶属关系，在职业生涯中改变隶属关系，或者使用与其他作者相似的姓名。 这种差异可能会使作者很难与他们的出版物和机构联系正确匹配。 针对各种政府或出版商注册方法和机器学习方法来处理这些问题，ORCID凭借其开源方法在跨方法和国家扩展的潜力脱颖而出。 提高识别作者的能力对于研究科学流动性、网络、作者对新科学主题的贡献以及科学学和创新政策领域的其他主题至关重要。 需要更多地了解ORCID覆盖的国家，领域和其他领域的优势和劣势，以便在科学和创新政策研究中发挥作用。该项目使用两种文献计量学方法来检查ORCID随时间推移的使用情况和作者特征。 首先，该项目采用学科领域的比较抽样，并考虑在这些学科领域的国家，组织和引文分布类别内的ORCID覆盖率。第二，该项目调查ORCID在确定新兴的科学驱动的技术，采用它在一个半自动化的数字评分系统的基础上的新兴指标的发展潜力。 新兴指标的目的是获取最近出版物和/或专利活动急剧增加的主题术语，并在已确定的学者的背景下对其进行审查，以潜在地突出新兴科学和技术领域的研究和开发活动。 由此产生的情报旨在为政府、商业和学术分析提供有用的信息，这些分析是对新兴科学技术领域的前沿参与者和其他贡献者的分析。

项目成果

Tracking researchers and their outputs: new insights from ORCIDs

跟踪研究人员及其成果：ORCID 的新见解

• DOI: 10.1007/s11192-017-2473-0
• 发表时间: 2017
• 期刊: Scientometrics
• 影响因子: 3.9
• 作者: Youtie, Jan;Carley, Stephen;Porter, Alan L.;Shapira, Philip
• 通讯作者: Shapira, Philip

Emergence scoring to identify frontier R&D topics and key players

• DOI: 10.1016/j.techfore.2018.04.016
• 发表时间: 2019-09-01
• 期刊: TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE
• 影响因子: 12
• 作者: Porter, Alan L.;Garner, Jon;Newman, Nils C.
• 通讯作者: Newman, Nils C.

Insights into relationships between disruptive technology/innovation and emerging technology: A bibliometric perspective

洞察颠覆性技术/创新与新兴技术之间的关系：文献计量视角

• DOI: 10.1016/j.techfore.2017.09.032
• 发表时间: 2017-11
• 期刊: Technological Forecasting and Social Change
• 影响因子: 12
• 作者: Li Munan;Porter Alan L;Suominen Arho
• 通讯作者: Suominen Arho

A Multi-match Approach to the Author Uncertainty Problem

解决作者不确定性问题的多重匹配方法

• DOI: 10.2478/jdis-2019-0006
• 发表时间: 2019
• 期刊: Journal of Data and Information Science
• 影响因子: 1.5
• 作者: Carley, Stephen F.;Porter, Alan L.;Youtie, Jan L.
• 通讯作者: Youtie, Jan L.

A measure of staying power: Is the persistence of emergent concepts more significantly influenced by technical domain or scale?

• DOI: 10.1007/s11192-017-2342-x
• 发表时间: 2017-06
• 期刊: Scientometrics
• 影响因子: 3.9
• 作者: S. Carley;Nils C. Newman;A. Porter;Jon Garner