Special Collections Asset Management System
The Special Collections Asset Management System (SCAMS) is a web application for managing descriptive metadata for the Special Collections Research Center digital collections. The application is particularly atuned to managing the lifecycle of metadata.
SCAMS started as an Access datebase, before I came to NCSU Libraries. It became clear quickly that further automation would be more difficult than it needed to be if we continued to use Access. We needed something better, but needed to continue to create metadata. The first step was a migration from using an Access database to using MySQL while continuing to use the Access front end. This allowed us to continue operations as I developed a new web application on top of the same database.
Initial development for the SCAMS web application was for the creation of stub records for batches of digitized images. This would allow us to publish new materials more quickly rather than waiting for metadata enhancement. It would also save time as some repeated values like rights and classification could be applied to all records in the batch.
After metadata editing functionality was further built out we moved to using the web application instead of the Access database. Quick ways to move through resources that need editing and keyboard shortcuts where added to improve efficiency. Since then flexible batch editing functionality has been added. Validations were added to improve data integrity and catch issues before they could get to a quality control stage.
The name was chosen to distinguish it from other digital asset managment needs within the library. SCAMS tries to optimize for the digitized (and born digital) collections workflow. It is not intended to be a digital asset management system for all purposes.
SCAMS is also responsible for indexing resources to Solr. Other applications can then reuse the Solr index for various discovery interfaces. SCAMS also provides some web APIs to more simply expose the metadata to other developers. We also mapped the database to MODS so that we could contribute records to the RDA test.
I am currently the sole developer of SCAMS. It continues to undergo development as new needs and opportunities are identified. Iterative development allows us to continue to improve the tool in new directions. Technologies used include Ruby, Rails, Solr, MySQL, and Blacklight.