A FAIR Data Ecosystem for Science of Science.

A FAIR Data Ecosystem for Science of Science.
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科学科学的公平数据生态系统。

DOI:
10.1002/pra2.960
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发表时间:
2023
期刊:
Proceedings of the Association for Information Science and Technology. Association for Information Science and Technology
影响因子:
--
通讯作者:
Liu,Qiaoyi
Liu,Qiaoyi
中科院分区:
--
文献类型:
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作者:
Qin,Jian;Bratt,Sarah;Hemsley,Jeff;Smith,Alexander;Liu,Qiaoyi

文献摘要

相似文献

这张海报在科学研究科学的公平数据生态系统的背景下讨论了自动化研究工作流(ARW)。我们提供了一个概念性的讨论,从信息科学和技术的角度来看,使用几个案例的“数据问题”在科学研究的科学,说明的特点和期望的设计者和开发者的公平的数据生态系统。从一个开发GenBank元数据工作流程的10年数据科学项目中汲取经验,我们将ARW的想法纳入FAIR数据生态系统讨论,以建立更广泛的背景并提高可推广性。研究人员可以将这些作为他们的数据科学项目的指南,以自动化科学领域及其他领域的研究工作流程。
This poster discusses Automated Research Workflows (ARWs) in the context of a FAIR data ecosystem for the science of science research. We offer a conceptual discussion from the point of view of information science and technology using several cases of “data problems” in the science of science research to illustrate the characteristics and expectations for designers and developers of a FAIR data ecosystem. Drawing from a 10‐year data science project developing GenBank metadata workflows, we incorporate the ideas of ARWs into the FAIR data ecosystem discussion to set a broader context and increase generalizability. Researchers can use these as a guide for their data science projects to automate research workflows in the science of science domain and beyond.