Full Papers

As research becomes increasingly data-driven and interdisciplinary, metadata interoperability has become essential for efficient data discovery and reuse. However, many domain-specific metadata schemas lack clear specifications and standardized structures, making cross-domain integration difficult. To address this issue, this study proposes a systematic three-phase workflow for cross-domain metadata mapping. The workflow consists of Phase (i) preliminary assessment of metadata schemas, Phase (ii) mapping relationship analysis, and Phase (iii) XSLT-based metadata transformation. To evaluate the effectiveness of the proposed workflow, a case study is conducted using a set of 125 metadata schemas. The results show that only 10 out of 125 schemas satisfy the requirements for mapping to the six mandatory DataCite properties, while the remaining schemas are limited by incomplete documentation or structural heterogeneity. In particular, challenges in representing properties such as ``Identifier'' and ``ResourceType'' highlight persistent semantic and structural mismatches across metadata standards. XSLT transformation files were developed and released, enabling practical implementation of the proposed mapping approach. This study contributes a systematic workflow for metadata mapping and provides empirical evidence on the limitations of current metadata standardization practices, supporting future efforts toward improved cross-domain metadata interoperability.

National web-scale discovery services (WSDS) depend on the sustained interoperability of institutional repositories to deliver reliable access to scholarly content. Existing evaluations predominantly assess interoperability through metadata completeness at registration, overlooking the operational dimensions that determine long-term integration. This paper introduces the Multidimensional Interoperability Readiness (MIR) framework, which integrates three analytically distinct dimensions: metadata completeness, harvesting sustainability, and metadata capacity. The framework is validated empirically through analysis of the Indonesia One Search (IOS) registry and OAI-PMH harvesting dataset comprising 29 registration fields across four functional categories. Findings reveal a structural decoupling between metadata completeness and harvesting sustainability: most repositories register adequate descriptive metadata but fail to sustain active harvesting over time. Journal repositories demonstrate substantially higher interoperability readiness than dataset and ETD repositories. The MIR framework offers a principled basis for evaluating national discovery infrastructure, with concrete governance implications for repository onboarding, monitoring, and differentiated intervention strategies. This study contributes to the DCMI 2026 theme of Data Integrity and Reliability, arguing that trustworthy discovery infrastructure requires verified, sustained metadata flow—not merely administrative registration.

Library of Congress Classification (LCC) and Dewey Decimal Classification (DDC) are two of the most widely used knowledge organization systems in libraries, yet empirical understanding of how they align and diverge in cataloging practice at scale remains limited. This paper examines co-assignment patterns between LCC and DDC classes using 4,042,962 dual-classified bibliographic records drawn from the Library of Congress's book catalog. Through descriptive quantitative analysis and bipartite network analysis, we identify areas of strong and weak structural correspondence between the two systems. Results reveal that well-defined humanities disciplines — including law, fine arts, religion, literature, and history — exhibit high one-to-one alignment, while broader and more applied domains such as social sciences, technology, and computer and information science show markedly dispersed cross-system mappings. A structural asymmetry is also evident: LCC classes tend to map more sharply to single DDC counterparts than vice versa. Network analysis identifies seven disciplinary communities and highlights Social Sciences and Technology as key interdisciplinary hubs, while second-level classes reveal contrasting topologies — a hub-centric star structure for LCC:G and a fragmented, multi-polar constellation for DDC:6XX. These findings carry practical implications for library reclassification projects, cataloging workflows, and the reuse of bibliographic metadata in emerging technological environments.