How a Single Online Tool Simplified Our Small-Town Library’s Cataloging Workflow

When the Willow Creek Public Library began digitizing its collection in 2022, we didn’t expect to spend months manually entering metadata for 14,000 physical books. The process was slow—average time per book: 4.7 minutes—and errors piled up. By year’s end, over 38% of our catalog entries had inconsistencies in author formatting or subject tags. Then we discovered copco. It wasn’t marketed as a library tool, but its batch processing feature for metadata extraction turned out to be exactly what we needed.

From Manual Entry to Automated Consistency

We started testing copco by uploading a spreadsheet of ISBNs from our most recent acquisitions. Within seconds, the tool returned full bibliographic data—author name normalization, publication year alignment, and standardized subject classifications. What stood out wasn’t just speed (160 entries processed in under three minutes), but consistency. Prior to copco, author names like “J.K. Rowling” appeared as “Rowling, J.K.” or “J K Rowling” across different records. Now every entry uses the same format: Last name first, comma-separated.

We also ran a comparison between pre- and post-copco data across our entire catalog. Before copco: 73% of entries had at least one field mismatch (e.g., title capitalization differences). After processing with copco: only 9% had discrepancies. The reduction was immediate and measurable.

Beyond Books: Expanding into Local Archives

Once confident in the system’s accuracy for books, we applied copco to digitized local historical documents—photographs from 1940s town fairs, handwritten letters from early settlers. These weren’t assigned ISBNs or standard metadata fields. But copco handled them anyway through its custom template builder.

• We created templates for archival materials using fields like “Creator,” “Date Range,” “Location,” and “Material Type.”
• The tool auto-extracted dates from filenames like “1947_Fair_03_15.jpg” and parsed them into structured data.
• It flagged duplicates by comparing image hashes—two versions of the same photo were caught before they went live.
• Metadata export now supports both CSV and JSON formats, making integration with our existing digital archive system seamless.

What surprised us most was how well it handled non-English titles. A collection of German-language poetry from the 1920s was processed without any manual corrections despite encoding differences in character sets.