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首页> 外文期刊>Journal of eScience Librarianship >An Analysis of Datasets within Illinois Digital Environment for Access to Learning and Scholarship (IDEALS), the University of Illinois Urbana-Champaign Repository
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An Analysis of Datasets within Illinois Digital Environment for Access to Learning and Scholarship (IDEALS), the University of Illinois Urbana-Champaign Repository

机译：伊利诺伊大学厄本那-香槟分校资料库在伊利诺伊州数字环境中获取学习和奖学金（IDEALS）的数据集的分析

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Objectives: The objective of this study is to identify: (1) how many datasets are within Illinois Digital Environment for Access to Learning and Scholarship (IDEALS); (2) which types of files are deposited in the repository; (3) which research methodologies are associated with these datasets; and (4) which research discipline or research communities are associated with these datasets within IDEALS. Methods: Datasets collected in this study were found using the University of Illinois repository IDEALS website link https://www.ideals.illinois.edu. The keywords used were data or dataset. In order to facilitate analysis, datasets were analyzed using MS-Excel spreadsheets. They were coded by title, issue date, research methodology, research discipline, and community to explore patterns of use and the relationship to data management and research data services. Results: There are 507 datasets in IDEALS dating from 1905-2015. Text files are the most frequently deposited file type; bibliographies represent 34% of the datasets; and, farming inventory lists are 26% of the datasets. Various research disciplines represent 18% of the datasets and research communities are associated with 78% of the datasets. 7% of the datasets are sponsored by NSF, NIH, IMLS and DOE funding agencies. Conclusion: Understanding the file types, research methodologies, research disciplines and research communities within a university’s current infrastructure, will provide a representation of the datasets and research supported within the university repository. It will enhance academic librarians and repository managers’ data management conversations with researchers and provide information needed to needed to improve workflow deposit and batch loading. It will enhance research data services, meet researcher’s needs, assess short-term preservation, and determine long-term preservation needs.
机译：目标：本研究的目的是确定：（1）在伊利诺伊州获得学习和奖学金的数字环境（IDEALS）中有多少个数据集; （2）哪些类型的文件存放在存储库中; （3）哪些研究方法与这些数据集相关; （4）哪些研究学科或研究社区与IDEALS中的这些数据集相关联。方法：本研究收集的数据集是通过伊利诺伊大学IDEIDE网站上的链接https://www.ideals.illinois.edu找到的。使用的关键字是数据或数据集。为了便于分析，使用MS-Excel电子表格对数据集进行了分析。它们按标题，发布日期，研究方法，研究学科和社区进行编码，以探讨使用模式以及与数据管理和研究数据服务的关系。结果：IDEALS中的507个数据集可追溯到1905-2015年。文本文件是最常存放的文件类型。参考书目占数据集的34％;而且，农业库存清单占数据集的26％。各种研究学科代表18％的数据集，而研究社区与78％的数据集相关。 7％的数据集由NSF，NIH，IMLS和DOE资助机构赞助。结论：了解大学当前基础架构中的文件类型，研究方法，研究学科和研究社区，将代表大学存储库中支持的数据集和研究。它将增强学术图书馆员和存储库经理与研究人员的数据管理对话，并提供改善工作流存储和批量加载所需的信息。它将增强研究数据服务，满足研究人员的需求，评估短期保存并确定长期保存需求。

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