The purpose of this paper is to propose and evaluate a learning model for Japanese classical literature using digital archives. The model enhances text comprehension by repeatedly comparing pictorial materials with classical texts. Its effectiveness was tested in university classes. The results confirmed that the model can be applied to both The Tale of the Heike and The Tale of the Bamboo Cutter. Student feedback indicated that the model helps supplement information from pictorial materials, deepening text understanding. Furthermore, the study suggests that this approach can promote exploratory learning using the texts and pictorial materials.

This study examines issues in creating Archival Information Packages (AIP) for long-term digital preservation based on the reference model for an Open Archival Information System (OAIS), an international standard. Using the “Management System for Material Images' Digitalization” at the Historiographical Institute of the University of Tokyo as a case study, the system's metadata was mapped to AIP elements. As a result, three key challenges were identified: 1) describing and packaging technical metadata considering preservation plans, workflows, and interoperability; 2) clarifying contextual and historical information for authenticity; and 3) determining the manageable scope of related information. The significance of this study lies in verifying the abstract concept of AIPs through concrete examples and clarifying the challenges that arise in their creation.

Towards the construction of digital archives in libraries of small municipalities, a survey was conducted on the installation rates of digital archives in public libraries categorized by the size of the municipality, based on research by saveMLAK. Additionally, digital archives were classified from the perspective of public libraries as providers, revealing the relationship between this classification and the installation rates categorized by municipality size. As a result, digital archive installations were found to be fewer in small municipalities, with many of them resorting to utilizing municipal websites and similar platforms for introducing digital archives. Taking this into account, an analysis of previous cases in constructing digital archives in small municipalities was conducted, and future prospects were considered.

This study aimed to improve the efficiency of metadata creation in digital archive construction. Using actual data from the "Kenzaburo Oe Library Digital Manuscript Archive," we reproduced the process of associating data sets through multiple methods and evaluated the consistency with expert-generated results. We compared and verified several methods, including exact bibliographic matching, string similarity comparison, and approaches utilizing large language models (LLMs). The results indicated that the methods using LLMs and exact matching of publication dates demonstrated a high accuracy rate. On the other hand, the method using LLMs faced the challenge of longer processing times. Based on these findings, we demonstrated that combining multiple methods can improve the balance between accuracy and processing time.