Journal of Informetrics最新文献_第9页

International mobility matters: Research collaboration and scientific productivity 国际流动很重要：研究合作与科学生产力

IF 3.7 2区管理学

Journal of Informetrics Pub Date : 2024-03-13 DOI: 10.1016/j.joi.2024.101522

Jiangwei Gu, Xuelian Pan, Shuxin Zhang, Jiaoyu Chen

{"title":"International mobility matters: Research collaboration and scientific productivity","authors":"Jiangwei Gu, Xuelian Pan, Shuxin Zhang, Jiaoyu Chen","doi":"10.1016/j.joi.2024.101522","DOIUrl":"https://doi.org/10.1016/j.joi.2024.101522","url":null,"abstract":"<div><p>In this study, we examine the impact of government-sponsored international mobility on researchers’ scientific collaboration and productivity. To identify causal effects, we use a longitudinal dataset covering internationally mobile doctoral students sponsored by the China Scholarships Council for non-degree studies and non-mobile doctoral students while implementing a combined propensity-score matching and difference-in-differences approach. We find that international mobility has a significantly positive impact on researchers’ scientific collaboration and research output. Our findings suggest that international mobility influences individuals’ research output by increasing the size of collaboration teams. We further find that the effects of international mobility are heterogeneous, that they vary significantly across gender, prestige of doctoral institution, mobility time and destination: male researchers gain more benefits from international mobility in the numbers of collaborators and papers; mobility in early years are more beneficial in increasing collaborators; mobility to Asia and Oceania is most beneficial in improving research quality. These findings provide a deeper understanding of how international mobility shapes researchers’ academic performance and have implications for the policy formulation on government-sponsored international mobility.</p></div>","PeriodicalId":48662,"journal":{"name":"Journal of Informetrics","volume":"18 2","pages":"Article 101522"},"PeriodicalIF":3.7,"publicationDate":"2024-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140113825","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Identifying knowledge evolution in computer science from the perspective of academic genealogy 从学术谱系的角度识别计算机科学的知识演变

IF 3.7 2区管理学

Journal of Informetrics Pub Date : 2024-03-10 DOI: 10.1016/j.joi.2024.101523

Zhongmeng Fu , Yuan Cao , Yong Zhao

{"title":"Identifying knowledge evolution in computer science from the perspective of academic genealogy","authors":"Zhongmeng Fu , Yuan Cao , Yong Zhao","doi":"10.1016/j.joi.2024.101523","DOIUrl":"https://doi.org/10.1016/j.joi.2024.101523","url":null,"abstract":"<div><p>Academic genealogy (AG) provides valuable insights into the transmission of knowledge from mentors to mentees, revealing the evolution of knowledge within the academic community. This study explores the intricate dynamics of knowledge evolution within academic genealogies, utilizing on a dataset comprising 16,852 computer science researchers, 613,277 papers, and 11,988 mentorship relationships. By focusing on small-scale knowledge units, our analysis aims to uncover patterns of knowledge inheritance and mutation across different subfields of computer science and highlights several aspects of knowledge evolution in computer science. Firstly, computer science is characterized by strong mentorship ties, indicating the significance of knowledge transmission within the field. Additionally, there is a mix of foundational and developing areas, suggesting a field that is growing and diversifying rather than declining, as indicated by linear regression outcomes. Secondly, our research reveals a surge in collaborative knowledge exchange in computer science since 2000, with fields such as Computer-Communication Networks and Software Engineering leading in terms of output and impact. Furthermore, areas like Computer Graphics and Artificial Intelligence stand out for their depth and novelty. Thirdly, we categorize researchers into three types: roots, branches, and leaves, reflecting their role in knowledge transmission. Branch researchers tend to innovate, while leaf researchers show a combination of traditional knowledge uptake and new contributions, illustrating the dynamic flow of ideas within the field. Future research endeavors are encouraged to embrace larger datasets and further fortify our understanding of the topic.</p></div>","PeriodicalId":48662,"journal":{"name":"Journal of Informetrics","volume":"18 2","pages":"Article 101523"},"PeriodicalIF":3.7,"publicationDate":"2024-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140069346","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A complement to the novel disruption indicator based on knowledge entities 对基于知识实体的新型干扰指标的补充

IF 3.7 2区管理学

Journal of Informetrics Pub Date : 2024-03-08 DOI: 10.1016/j.joi.2024.101524

Tong Tong , Wanru Wang , Fred Y. Ye

{"title":"A complement to the novel disruption indicator based on knowledge entities","authors":"Tong Tong , Wanru Wang , Fred Y. Ye","doi":"10.1016/j.joi.2024.101524","DOIUrl":"https://doi.org/10.1016/j.joi.2024.101524","url":null,"abstract":"<div><p>Following the proposal of disruption index (<em>DI</em>) for detecting scientific breakthroughs based on citation patterns, a recently introduced knowledge entity-based disruption (<em>ED</em>) index incorporates both citation patterns and knowledge elements. In this study, we investigate the applications and limitations of the <em>ED</em> series indicators by employing two datasets from different fields within the Web of Science database, providing some insights that complement the use of <em>ED</em> series indicators. For the genome editing dataset, we validate the consistency across the <em>ED</em> series indicators based on different knowledge entities, specifically MeSH terms and KeyWords Plus. In the case of the h-set dataset, where no MeSH terms were matched, our focus is on comparing the performance of the <em>ED</em> series indicators based on KeyWords Plus with other representative disruption indicators in small datasets. When considering the two datasets of the “stem” and “seed” papers obtained by the seed algorithm as reference objects and calculating their <em>DI</em> and <em>ED</em> series indicators, the results indicate that the values of <em>DI</em> series indicators of “seed” papers exhibit higher values compared to the <em>ED</em> series indicators. From a statistics perspective, there are no significant differences in the <em>ED</em> series indicators when employing different knowledge entities, despite variations in their rankings. Based on the results and discussions of this study, we provide guidance on application of <em>ED</em> series indicators and potential refinements in subsequent studies.</p></div>","PeriodicalId":48662,"journal":{"name":"Journal of Informetrics","volume":"18 2","pages":"Article 101524"},"PeriodicalIF":3.7,"publicationDate":"2024-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140067027","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The internal dynamics of journals’ h-cores over time 期刊 h-cores 的内部动态随时间变化

IF 3.7 2区管理学

Journal of Informetrics Pub Date : 2024-03-07 DOI: 10.1016/j.joi.2024.101518

Yves Fassin

{"title":"The internal dynamics of journals’ h-cores over time","authors":"Yves Fassin","doi":"10.1016/j.joi.2024.101518","DOIUrl":"https://doi.org/10.1016/j.joi.2024.101518","url":null,"abstract":"<div><p>The objective of this article is to study, empirically, the evolution of the h-indexes of academic journals and the internal dynamics of their h-core and h²-core over time. The h-indexes describe a situation at a given moment in time; they are dynamic indicators.</p><p>As citations grow over time, the h-index and the h-core grow.</p><p>In this paper, the composition of the h-core over time is analyzed with an example of practical application, based on data from the Journal of Business Ethics, and complemented with three other journals. The results show how the composition of the h-core varies over time. As the h-index yearly expands, new additional articles enter the h-core, while other articles disappear to make room for newcomers. Only those articles remain that sustain a citation growth rate with an average around the average growth rate of the h-index. In a mature journal, as in our example, it takes a few years to enter the h-core, generally about ten years.</p><p>A similar entry and exit phenomenon also appears at the level of the h²-core and h³- core, which remain more stable.</p><p>The ha-core also has a dynamic evolution where new entrants arrive more quickly, which confirms the advantage of the ha-index that acknowledges potential papers earlier</p></div>","PeriodicalId":48662,"journal":{"name":"Journal of Informetrics","volume":"18 2","pages":"Article 101518"},"PeriodicalIF":3.7,"publicationDate":"2024-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140061934","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Early identification of breakthrough research from sleeping beauties using machine learning 利用机器学习从睡美人中及早发现突破性研究成果

IF 3.7 2区管理学

Journal of Informetrics Pub Date : 2024-02-26 DOI: 10.1016/j.joi.2024.101517

Xin Li, Xiaodi Ma, Ye Feng

{"title":"Early identification of breakthrough research from sleeping beauties using machine learning","authors":"Xin Li, Xiaodi Ma, Ye Feng","doi":"10.1016/j.joi.2024.101517","DOIUrl":"https://doi.org/10.1016/j.joi.2024.101517","url":null,"abstract":"<div><p>Breakthrough research is groundbreaking and transformative scientific research that can lead to new frontiers and even trigger substantial changes in the scientific paradigm. Early identification of breakthrough research is crucial for scientists, R&D experts, and policymakers. \"Sleeping Beauty in Science\" is a category of papers characterized as \"delayed recognition\", which is considered as the crucial carriers of breakthrough research. Machine learning methods can extract and learn high-quality information from a priori knowledge to predict future trends. In this paper, to address the shortcomings of existing studies on the early identification of breakthrough research, we propose a framework for identifying breakthrough research from sleeping beauties using machine learning. In this framework, we first construct machine learning models to obtain the relationship patterns between historical sleeping beauties and their citation trends. Then, we use these relational patterns to identify potential sleeping beauties. Secondly, we construct a breakthrough index based on the essential features of breakthrough research, then we apply it to identify breakthrough research among potential sleeping beauties, enabling the early identification of breakthrough research. Finally, an empirical study is conducted in the chemistry research field to verify the validity and flexibility of this framework. The results show that the framework can effectively identify breakthrough research from sleeping beauties. This paper contributes to the early identification of breakthrough research, evaluating academic results, and exploring research frontiers. Additionally, it will also provide methodological support for the decision-making of R&D experts and policymakers.</p></div>","PeriodicalId":48662,"journal":{"name":"Journal of Informetrics","volume":"18 2","pages":"Article 101517"},"PeriodicalIF":3.7,"publicationDate":"2024-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139985750","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Modeling citation concentration through a mixture of Leimkuhler curves 通过莱姆库勒曲线混合物模拟引文浓度

IF 3.7 2区管理学

Journal of Informetrics Pub Date : 2024-02-23 DOI: 10.1016/j.joi.2024.101519

Emilio Gómez-Déniz, Pablo Dorta-González

{"title":"Modeling citation concentration through a mixture of Leimkuhler curves","authors":"Emilio Gómez-Déniz, Pablo Dorta-González","doi":"10.1016/j.joi.2024.101519","DOIUrl":"https://doi.org/10.1016/j.joi.2024.101519","url":null,"abstract":"<div><p>When a graphical representation of the cumulative percentage of total citations to articles, ordered from most cited to least cited, is plotted against the cumulative percentage of articles, we obtain a Leimkuhler curve. In this study, we noticed that standard Leimkuhler functions may not be sufficient to provide accurate fits to various empirical informetrics data. Therefore, we introduce a new approach to Leimkuhler curves by fitting a known probability density function to the initial Leimkuhler curve, taking into account the presence of a heterogeneity factor. As a significant contribution to the existing literature, we introduce a pair of mixture distributions (called PG and PIG) to bibliometrics. In addition, we present closed-form expressions for Leimkuhler curves. Some measures of citation concentration are examined empirically for the basic models (based on the Power and Pareto distributions) and the mixed models derived from these. An application to two sources of informetric data was conducted to see how the mixing models outperform the standard basic models. The different models were fitted using non-linear least squares estimation.</p></div>","PeriodicalId":48662,"journal":{"name":"Journal of Informetrics","volume":"18 2","pages":"Article 101519"},"PeriodicalIF":3.7,"publicationDate":"2024-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1751157724000324/pdfft?md5=3287b52cd680b5eba7e54f634c4c46cc&pid=1-s2.0-S1751157724000324-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139941681","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Impact of gender composition of academic teams on disruptive output 学术团队的性别构成对破坏性产出的影响

IF 3.7 2区管理学

Journal of Informetrics Pub Date : 2024-02-22 DOI: 10.1016/j.joi.2024.101520

Ming-Ze Zhang , Tang-Rong Wang , Peng-Hui Lyu , Qi-Mei Chen , Ze-Xia Li , Eric W.T. Ngai

{"title":"Impact of gender composition of academic teams on disruptive output","authors":"Ming-Ze Zhang , Tang-Rong Wang , Peng-Hui Lyu , Qi-Mei Chen , Ze-Xia Li , Eric W.T. Ngai","doi":"10.1016/j.joi.2024.101520","DOIUrl":"https://doi.org/10.1016/j.joi.2024.101520","url":null,"abstract":"<div><p>Intergender collaboration is becoming increasingly common in academia. However, the impact of team gender structures on innovation remains unknown. Using data from the American Physical Society, this study applies the disruption index to measure the relationship between gender composition and innovation performance. The results show that compared with single-gender teams, moderate inter-gender collaboration has a greater potential to produce disruptive knowledge and must be adopted by scientific teams. Specifically, the types of innovation in mixed-gender teams are affected by the gender composition. If the proportion of female scholars and their participation increase in a mixed-gender team, it can positively contribute to disruptive performance. If female scientists are placed on a male-dominated team, they may function as consolidation representatives. The robustness results indicate that the conclusions also apply to male scientists. The results suggest that males and females have no significant physiological differences in innovation and that the key is to find a gender balance in collaboration. Based on the theories of similarity-attraction and cognitive diversity, the reasons for the differences between female and male scientists may be team atmosphere and their roles in collaboration. This study can serve as a reference for policymakers and funders when building teams to achieve disruptive discoveries.</p></div>","PeriodicalId":48662,"journal":{"name":"Journal of Informetrics","volume":"18 2","pages":"Article 101520"},"PeriodicalIF":3.7,"publicationDate":"2024-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139936209","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

When career-boosting is on the line: Equity and inequality in grant evaluation, productivity, and the educational backgrounds of Marie Skłodowska-Curie Actions individual fellows in social sciences and humanities 当职业发展岌岌可危时：玛丽-斯克沃多夫斯卡-居里夫人社会科学与人文科学行动个人研究员在资助评估、生产率和教育背景方面的公平与不平等

IF 3.7 2区管理学

Journal of Informetrics Pub Date : 2024-02-14 DOI: 10.1016/j.joi.2024.101516

Tamás Tóth PhD (Assistant Professor) , Márton Demeter PhD (Full Professor) , Sándor Csuhai , Zsolt Balázs Major PhD (Associate Professor)

{"title":"When career-boosting is on the line: Equity and inequality in grant evaluation, productivity, and the educational backgrounds of Marie Skłodowska-Curie Actions individual fellows in social sciences and humanities","authors":"Tamás Tóth PhD (Assistant Professor) , Márton Demeter PhD (Full Professor) , Sándor Csuhai , Zsolt Balázs Major PhD (Associate Professor)","doi":"10.1016/j.joi.2024.101516","DOIUrl":"https://doi.org/10.1016/j.joi.2024.101516","url":null,"abstract":"<div><p>Prestigious academic scholarships are highly competitive, so using appropriate evaluation criteria is important. In this study, we analyzed 259 Marie Skłodowska-Curie Actions (MSCA) grantees in social sciences and humanities to see their composition in terms of productivity, educational background, mobility, and gender. Based on quantitative content analysis, linear regressions, and network analyses, the findings reveal that while most grantees significantly improved in their production after funding, there are many awardees with weak or even invisible publication records on Scopus both prior to and following their awards. Most of the scholars who had already been prolific prior to their grant continued to be productive after funding, while many awardees with weak past performances were even less productive after winning the scholarship. In terms of gender, we found no Matilda effect in the grant allocation process; while in terms of production, male scholars benefit more from the grant than females. The outcomes also show that Western countries dominate both the awardees’ education trajectories and their host institutions. Our conclusion is that the geographic diversity among the awardees should be developed and that the evaluation process should focus on pre-MSCA performance to support the most promising applicants.</p></div>","PeriodicalId":48662,"journal":{"name":"Journal of Informetrics","volume":"18 2","pages":"Article 101516"},"PeriodicalIF":3.7,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139738661","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A multiple k-means cluster ensemble framework for clustering citation trajectories 对引文轨迹进行聚类的多重均值聚类集合框架

IF 3.7 2区管理学

Journal of Informetrics Pub Date : 2024-02-13 DOI: 10.1016/j.joi.2024.101507

Joyita Chakraborty , Dinesh K. Pradhan , Subrata Nandi

{"title":"A multiple k-means cluster ensemble framework for clustering citation trajectories","authors":"Joyita Chakraborty , Dinesh K. Pradhan , Subrata Nandi","doi":"10.1016/j.joi.2024.101507","DOIUrl":"https://doi.org/10.1016/j.joi.2024.101507","url":null,"abstract":"<div><p>Citation maturity time varies for different articles. However, the impact of all articles is measured in a fixed window (2-5 years). Clustering their citation trajectories helps understand the knowledge diffusion process and reveals that not all articles gain immediate success after publication. Moreover, clustering trajectories is necessary for paper impact recommendation algorithms. It is a challenging problem because citation time series exhibit significant variability due to non-linear and non-stationary characteristics. Prior works propose a set of arbitrary thresholds and a fixed rule-based approach. All methods are primarily parameter-dependent. Consequently, it leads to inconsistencies while defining similar trajectories and ambiguities regarding their specific number. Most studies only capture extreme trajectories. Thus, a generalized clustering framework is required. This paper proposes a <em>feature-based multiple k-means cluster ensemble framework</em>. Multiple learners are trained for evaluating the credibility of class labels, unlike single clustering algorithms. 195,783 and 41,732 well-cited articles from the Microsoft Academic Graph data are considered for clustering short-term (10-year) and long-term (30-year) trajectories, respectively. It has linear run-time. Four distinct trajectories are obtained – <em>Early Rise-Rapid Decline (ER-RD)</em> (2.2%), <em>Early Rise-Slow Decline (ER-SD)</em> (45%), <em>Delayed Rise-Not yet Declined (DR-ND)</em> (53%), and <em>Delayed Rise-Slow Decline (DR-SD)</em> (0.8%). Individual trajectory differences for two different spans are studied. Most papers exhibit <em>ER-SD</em> and <em>DR-ND</em> patterns. The growth and decay times, cumulative citation distribution, and peak characteristics of individual trajectories' are re-defined empirically. A detailed comparative study reveals our proposed methodology can detect all distinct trajectory classes.</p></div>","PeriodicalId":48662,"journal":{"name":"Journal of Informetrics","volume":"18 2","pages":"Article 101507"},"PeriodicalIF":3.7,"publicationDate":"2024-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139731857","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Does open data have the potential to improve the response of science to public health emergencies? 开放数据是否具有改善科学应对公共卫生突发事件的潜力？

IF 3.7 2区管理学

Journal of Informetrics Pub Date : 2024-02-10 DOI: 10.1016/j.joi.2024.101505

Xiaowei Ma , Hong Jiao , Yang Zhao , Shan Huang , Bo Yang

{"title":"Does open data have the potential to improve the response of science to public health emergencies?","authors":"Xiaowei Ma , Hong Jiao , Yang Zhao , Shan Huang , Bo Yang","doi":"10.1016/j.joi.2024.101505","DOIUrl":"https://doi.org/10.1016/j.joi.2024.101505","url":null,"abstract":"<div><p>Open data was recognized as essential to prevent and treat pandemic infection through sharing, disseminating, and using relevant information. This study explores how and to what extent open data influenced the response of science to such emergencies from a quantitative perspective. Based on the genetic datasets for viruses associated with Ebola, SARS, MERS, and COVID-19, we analyze the efficiency of data sharing and dissemination from a knowledge flow perspective: \"datasets→papers\", \"datasets→patents\", and \"datasets→papers→patents\". The results showed: (1) From the early Ebola outbreak to the recent COVID-19 pandemic, data sharing has been increasingly open and timely. (2) Basic research and the developments of vaccine and medicine related to the pandemics have increasingly relied on open data, providing more data-driven alternatives. (3) From Ebola to COVID-19, the citation lags of highly cited datasets have decreased in both papers and patents, demonstrating that open data can accelerate the development of science and technology to address the epidemics. In conclusion, open data can potentially improve science's response to public health emergencies by saving precious time. Therefore, much greater efforts by the scientific community to open data are well deserved.</p></div>","PeriodicalId":48662,"journal":{"name":"Journal of Informetrics","volume":"18 2","pages":"Article 101505"},"PeriodicalIF":3.7,"publicationDate":"2024-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139719661","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0