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Cleaning Collections Data Using OpenRefine

机译:使用OpenRefine清洁集合数据

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Collection maintenance, including weeding, is a key component of my position as an academic science librarian. In an ideal world we receive perfect data that are clean and ready to use. But unfortunately, that is not always the case. In large deselection projects you might receive holdings and circulation records in separate files which, once combined, may contain many undesired duplicated line items. I will demonstrate how you can effectively and quickly use the facet row feature in OpenRefine to deduplicate data. The benefit of this method is that you select which of the duplicated items will be kept and which will be deleted. Once OpenRefine is downloaded and opened, you work in a web user interface to upload your data, clean and transform the data, and then download from the browser to a CSV file in Excel. With practice, I have found that this only takes a few minutes for thousands of line items, and ensures I am able to select the data I want.
机译:收集维护(包括除草)是我作为学术科学馆员职位的关键组成部分。 在理想的世界中,我们收到完美的数据,清洁并准备使用。 但不幸的是,情况并非如此。 在大型取消选择项目中,您可能会在单独的文件中收到控股和循环记录,这可能包含许多不期望的重复行项目。 我将演示如何有效,快速使用OpenRefine中的Facet行功能以重复数据删除数据。 此方法的好处是您选择将保留哪些重复项并将被删除。 一旦下载了OpenRefine并打开,您就在Web用户界面中工作以上载数据,清除和转换数据,然后从浏览器下载到Excel中的CSV文件。 通过练习,我发现这只需几分钟即可为数千个线项,并确保我能够选择我想要的数据。

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