Using Automation And Batch Processing To Remediate Duplicate Series Data In A Shared Bibliographic Catalog

The application of divergent local practices in a shared bibliographic database can result in unexpected display issues that adversely affect user experience. This is especially problematic when merging databases from multiple institutions accustomed to adopting local practices for their own constituents. The authors describe their experience with the application of automation tools, such as MarcEdit, Excel, and Python, during a large-scale remediation project. They used these tools to analyze, compare, and batch process bibliographic records to remediate obsolete and redundant series data in their shared bibliographic database.