Abstract

The emerging transdiscipline of Computational Archival Science (CAS) links frameworks such as Brown Dog and repository software such as Digital Repository At Scale To Invite Computation (DRAS-TIC) to yield an understanding of working with digital collections at scale for cultural data. The DRAS-TIC and Brown Dog projects here serve as the basis for an expandable distributed storage/service architecture with on-demand, horizontally scalable integrated digital preservation and analysis services.

Keywords: JCDL workshop proceedings;data repositories;parallel processing;machine learning