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Units of Evidence for Analyzing Subdisciplinary Difference in Data Practice Studies

机译:分析数据实践研究中的子学科差异的证据单位

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Digital libraries (DLs) are adapting to accommodate research data and related services. The complexities of this new content spans the elements of DL development, and there are questions concerning data selection, service development, and how best to align these with local, institutional initiatives for cyberinfrastructure, data-intensive research, and data stewardship. Small science disciplines are of particular relevance due to the prevalence of this mode of research in the academy, and the anticipated magnitude of data production. To support data acquisition into DLs - and subsequent data reuse - there is a need for new knowledge on the range and complexities inherent in practice-data-curation arrangements for small science research. We present a flexible methodological approach crafted to generate data units to analyze these relationships and facilitate cross-disciplinary comparisons.
机译:数字图书馆(DLS)正在调整以适应研究数据和相关服务。这种新内容的复杂性跨越DL开发的要素,有些关于数据选择,服务开发的问题,以及如何将这些与纽约州赛马博物馆,数据密集型研究和数据管理有关的本地机构举措。由于在学院的研究模式和预期的数据生产的预期,小学学科是特别相关的。为了支持DLS的数据获取和随后的数据重用 - 需要了解小型科学研究的实践数据策划安排中固有的范围和复杂性的新知识。我们展示了一种灵活的方法方法,用于生成数据单元来分析这些关系并促进交叉学科比较。

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