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Assessing Metadata Quality and Terminology Coverage of a Federally Sponsored Health Data Repository.

机译:评估联邦政府赞助的健康数据存储库的元数据质量和术语覆盖率。

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摘要

The Open Government Initiative began an era of information sharing by publishing data that is accessible to the public. HealthData.gov is a data portal that was developed by the U.S. Federal Government to publish metadata to disseminate information about healthcare datasets to the American people. Despite the growth in the number of datasets published, there has been limited public participation in the use of the data, which has been attributed to the currently implemented methods for data storage and retrieval. An automated assessment of the HealthData.gov metadata was conducted to assess completeness, accuracy, and consistency of metadata published from 2012 to 2014. Also, a method for indexing the datasets using Medical Subject Headings (MeSH) was evaluated using a term coverage study. The results of these studies demonstrated that metadata published in earlier years were less complete, lower quality, and less consistent. Also, metadata that underwent modifications following their original creation were of higher quality. MeSH offered adequate coverage of the metadata concepts, thereby lending support for the adoption of the terminology for indexing purposes. The results suggested that greater standardization is needed when publishing metadata. This research contributed to the development of automated metrics for assessing metadata quality, design recommendations for a framework to supports high quality metadata, and recommendations for expanding MeSH to offer greater coverage of concepts from HealthData.gov.
机译:开放政府倡议通过发布公众可以访问的数据开始了信息共享的时代。 HealthData.gov是由美国联邦政府开发的数据门户,用于发布元数据以将有关医疗数据集的信息传播给美国人。尽管已发布的数据集数量有所增加,但是公众对数据使用的参与有限,这归因于当前实施的数据存储和检索方法。对HealthData.gov元数据进行了自动评估,以评估2012年至2014年发布的元数据的完整性,准确性和一致性。此外,还使用术语覆盖率研究评估了使用医学主题词(MeSH)为数据集建立索引的方法。这些研究的结果表明,早些年发布的元数据不够完整,质量较低且一致性较低。同样,元数据在其原始创建之后进行了修改,因此具有更高的质量。 MeSH提供了对元数据概念的充分覆盖,从而为采用该术语建立索引提供了支持。结果表明,发布元数据时需要更大的标准化。这项研究有助于开发用于评估元数据质量的自动化指标,为支持高质量元数据的框架设计建议,以及为扩展MeSH以从HealthData.gov提供更多概念覆盖范围而提出的建议。

著录项

  • 作者

    Marc, David Terrence.;

  • 作者单位

    University of Minnesota.;

  • 授予单位 University of Minnesota.;
  • 学科 Health care management.;Library science.
  • 学位 Ph.D.
  • 年度 2016
  • 页码 142 p.
  • 总页数 142
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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