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Title, Description, and Subject are the Most Important Metadata Fields for Keyword Discoverability

机译：标题，描述和主题是关键字可发现性最重要的元数据字段

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A Review of: Yang, L. (2016). Metadata effectiveness in internet discovery: An analysis of digital collection metadata elements and internet search engine keywords. College & Research Libraries, 77(1), 7-19. http://doi.org/10.5860/crl.77.1.7 Objective – To determine which metadata elements best facilitate discovery of digital collections. Design – Case study. Setting – A public research university serving over 32,000 graduate and undergraduate students in the Southwestern United States of America. Subjects – A sample of 22,559 keyword searches leading to the institution’s digital repository between August 1, 2013, and July 31, 2014. Methods – The author used Google Analytics to analyze 73,341 visits to the institution’s digital repository. He determined that 22,559 of these visits were due to keyword searches. Using Random Integer Generator, the author identified a random sample of 378 keyword searches. The author then matched the keywords with the Dublin Core and VRA Core metadata elements on the landing page in the digital repository to determine which metadata field had drawn the keyword searcher to that particular page. Many of these keywords matched to more than one metadata field, so the author also analyzed the metadata elements that generated unique keyword hits and those fields that were frequently matched together. Main Results – Title was the most matched metadata field with 279 matched keywords from searches. Description and Subject were also significant fields with 208 and 79 matches respectively. Slightly more than half of the results, 195 keywords, matched the institutional repository in one field only. Both Title and Description had significant match rates both independently and in conjunction with other elements, but Subject keywords were the sole match in only three of the sampled cases. Conclusion – The Dublin Core elements of Title, Description, and Subject were the most frequently matched fields in keyword searches. Academic librarians should focus on these elements when creating records in digital repositories to optimize traffic to their site from search engines.
机译：评述：Yang L.（2016）。 Internet发现中的元数据有效性：对数字集合元数据元素和Internet搜索引擎关键字的分析。高校研究图书馆，77（1），7-19。 http://doi.org/10.5860/crl.77.1.7目标–确定最能促进发现数字馆藏的元数据元素。设计–案例研究。设置-一所公立研究型大学，为美国西南部的32,000多名研究生和本科生提供服务。主题–在2013年8月1日至2014年7月31日之间进行了22559次关键字搜索的样本，从而获得了该机构的数字存储库。他确定其中22,559次访问是由于关键字搜索引起的。使用随机整数生成器，作者确定了378个关键字搜索的随机样本。然后，作者将关键字与数字存储库登录页面上的Dublin Core和VRA Core元数据元素进行匹配，以确定哪个元数据字段将关键字搜索器吸引到了该特定页面。这些关键字中的许多关键字都与一个以上的元数据字段匹配，因此作者还分析了生成唯一关键字匹配的元数据元素以及那些经常匹配在一起的字段。主要结果–标题是最匹配的元数据字段，来自搜索的279个匹配关键字。说明和主题也是重要的字段，分别具有208和79个匹配项。 195个关键字仅略高于一半的结果与机构存储库仅在一个字段中匹配。标题和描述都具有独立或与其他元素一起显着的匹配率，但是在三个示例中，主题关键字是唯一的匹配项。结论–标题，描述和主题的都柏林核心元素是关键字搜索中最经常匹配的字段。当在数字存储库中创建记录以优化从搜索引擎到其站点的访问量时，大学图书馆员应将重点放在这些元素上。

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