The University of Florida (UF) George A. Smathers Libraries have been involved in a wide range of partnered digital collection projects throughout the years with a focus on collaborating with institutions across the Caribbean region. One of the countries that we have a number of digitization projects within is Cuba. One of these partnerships is with the library of the Temple Beth Shalom (Gran Sinagoga Bet Shalom) in Havana, Cuba. As part of this partnership, we have sent personnel over to Cuba to do onsite scanning and digitization of selected materials found within the institution. The digitized content from this project was brought back to UF and loaded into our University of Florida Digital Collections (UFDC) system. Because internet availability and low bandwidth are issues in Cuba, the Synagogue’s ability to access the full-text digitized content residing on UFDC was an issue. The Synagogue also did not have a local digital library system to load the newly digitized content. To respond to this need we focused on providing a minimalist technology solution that was highly portable to meet their desire to conduct full-text searches within their library on their digitized content. This article will explore the solution that was developed using a USB flash drive loaded with a PortableApps version of Zotero loaded with multilingual OCR’s documents.

In modern library systems, access to the digital content is heavily dependent on effective metadata. The University of Florida (UF) Digital Collections (UFDC) are an actively growing, open access, digital library comprising over 500,000 records. As with any large-scale digital library project, a well-known challenge is the varying quality and quantity of legacy metadata available for each title. Inconsistent metadata makes digitized materials harder to find. If users cannot find the content they are looking for, a great deal of human effort has been wasted and the investment in digital collections is not being realized. Subject terms can be one of the most efficient methods for accessing desired materials, and subject terms created from controlled vocabularies deliver the most consistent results. To date, applying and editing subject metadata has been a record-by-record, labor-intensive process, making the prospect of retrospective projects cost-prohibitive. The UF team is investigating the capacity of research library staff to implement a Machine Assisted Indexing (MAI) system to automate the process of selecting and applying subject terms, based on the use of a rule set combined with controlled vocabularies, to the metadata of a body of already digitized content. To execute the project, the Smathers Libraries team at UF is collaborating with Access Innovations (AI) consultants to implement a machine-assisted indexing system to mitigate the challenges discussed above. Two collections in the UFDC were selected to test the MAI process on and then assessments were developed to determine if the process was functional and if it met the stated need to improve access. The first pilot focused on enhancing subject metadata across the Electronic Thesis and Dissertations (ETDs) collection. A second pilot assessment effort focused on a long run of a journal with strong historical ties to agriculture in Florida. Random issues of the title were selected for machine assisted indexing and the use of those issues will be measures against the use of the other issues in the series.