Look And Learn History Archive
Heptic spearheaded a massive digitization and metadata optimization initiative for Look and Learn. Our team harvested hundreds of thousands of high-resolution historical images from global museums and galleries. The goal was to transform the archive into the world’s leading destination for free, public-domain educational assets. By refining metadata and streamlining the catalog, we ensured these cultural treasures are accessible to researchers, educators, and the creative community worldwide.
The Challenge
The primary obstacle was the sheer volume and fragmented nature of the source data. Diverse museum archives utilized non-standardized formats, making automated collection and synchronization difficult. We faced significant technical hurdles in downloading hundreds of thousands of TIFF and JPEG files while maintaining data integrity. Furthermore, inconsistent legacy metadata made the archive difficult to search, requiring a sophisticated approach to categorize and enrich the data for modern web standards.
The Solution
We engineered a custom, high-concurrency ETL pipeline using Python to automate the extraction and validation process. Our solution utilized Amazon S3 for secure, scalable storage and implemented advanced image annotation to improve SEO and accessibility. By programmatically enhancing alt tags and descriptive metadata, we converted a raw data dump into a structured, searchable digital library. This automated workflow now ensures the archive remains a consistent and premium resource.
Project Gallery
Project Details
2026-01-01
Need a similar solution for your business?
Contact Us