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Batch processing metadata for electronic resources means working with records of varying quality. Common issues include titles in all sorts of cases, missing information such as publication, URLs, or fixed field data, lack of information needed for local best practices, or inconsistent vendor and/or OCLC numbers. These issues can be daunting and involve a significant amount of cleanup that can slow the batch processing down or make it ineffective. To help process title sets of records, I have begun using a suite of tools that include MarcEdit, OpenRefine, Excel, and Python. These tools help me address common issues and implement local practices in batch. The results are better quality metadata records that facilitate access and discovery. My presentation will highlight how I use these tools with examples. My hope is that attendees can learn from these examples and use these tools in their own batch processing.


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Creative Commons Attribution-Noncommercial 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 4.0 License.



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