我们可以更好地利用ORCID:五个观察到的错误应用

Q2 Computer Science Data Science Journal Pub Date : 2021-01-01 DOI:10.5334/dsj-2021-038
Miriam Baglioni, P. Manghi, A. Mannocci, A. Bardi
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引用次数: 9

摘要

自2012年以来,“开放研究人员和贡献者ID”组织(ORCID)已经成功地运行了一个全球注册表,其目的是“为从事研究、奖学金和创新活动的个人提供一个唯一的、持久的标识符”。学术交流生态系统中的任何服务(例如,出版商、存储库、CRIS系统等)都可以通过在元数据存储过程中包含对ORCID注册表中id的引用来贡献一个无歧义的学术记录。OpenAIRE研究图谱是一个学术知识图谱,汇集了来自ORCID注册表的记录和来自世界各地出版商和存储库的ORCID引用的出版记录,以产生研究影响监测和开放科学统计数据。图数据分析揭示了由于ORCID注册表“误用”造成的“异常”,这是由错误的ORCID转介和对ORCID注册表的误用造成的。尽管这些问题只影响到ORCID的一小部分记录,但它们不可避免地影响了ORCID基础设施的质量,并可能引发对该服务的诋毁和怀疑。在本文中,我们对这些错误应用进行了分类和定性记录,确定了五个ORCID注册者相关和ORCID转介相关的异常,以提高ORCID用户的意识。我们描述了ORCID目前采取的对策,并在适用的情况下提供建议。最后,我们详细阐述了社区引导的开放科学基础设施的重要性,以及这种方法已经和可能给ORCID带来的好处。2 Baglioni等人在本文的后页可以找到作者的从属关系。数据科学杂志DOI: 10.5334/dsj-2021038
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We Can Make a Better Use of ORCID: Five Observed Misapplications
Since 2012, the “Open Researcher and Contributor ID” organisation (ORCID) has been successfully running a worldwide registry, with the aim of “providing a unique, persistent identifier for individuals to use as they engage in research, scholarship, and innovation activities”. Any service in the scholarly communication ecosystem (e.g., publishers, repositories, CRIS systems, etc.) can contribute to a non-ambiguous scholarly record by including, during metadata deposition, referrals to iDs in the ORCID registry. The OpenAIRE Research Graph is a scholarly knowledge graph that aggregates both records from the ORCID registry and publication records with ORCID referrals from publishers and repositories worldwide to yield research impact monitoring and Open Science statistics. Graph data analytics revealed “anomalies” due to ORCID registry “misapplications”, caused by wrong ORCID referrals and misexploitation of the ORCID registry. Albeit these affect just a minority of ORCID records, they inevitably affect the quality of the ORCID infrastructure and may fuel the rise of detractors and scepticism about the service. In this paper, we classify and qualitatively document such misapplications, identifying five ORCID registrant-related and ORCID referral-related anomalies to raise awareness among ORCID users. We describe the current countermeasures taken by ORCID and, where applicable, provide recommendations. Finally, we elaborate on the importance of a community-steered Open Science infrastructure and the benefits this approach has brought and may bring to ORCID. *Author affiliations can be found in the back matter of this article 2 Baglioni et al. Data Science Journal DOI: 10.5334/dsj-2021038
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来源期刊
Data Science Journal
Data Science Journal Computer Science-Computer Science (miscellaneous)
CiteScore
5.40
自引率
0.00%
发文量
17
审稿时长
10 weeks
期刊介绍: The Data Science Journal is a peer-reviewed electronic journal publishing papers on the management of data and databases in Science and Technology. Details can be found in the prospectus. The scope of the journal includes descriptions of data systems, their publication on the internet, applications and legal issues. All of the Sciences are covered, including the Physical Sciences, Engineering, the Geosciences and the Biosciences, along with Agriculture and the Medical Science. The journal publishes papers about data and data systems; it does not publish data or data compilations. However it may publish papers about methods of data compilation or analysis.
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