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This study examined the interdisciplinary circulation of knowledge in records management and archives research by analyzing knowledge inflow and outflow patterns at both macro and micro levels using citation and cited-reference data. At the macro level, a corpus of scholarly articles extracted from the Korea Citation Index (KCI) using the keywords “records management” and “archives” was assembled, along with their respective sets of citing and cited articles, and interdisciplinarity was quantified using normalized Shannon entropy. The resulting inflow and outflow indices of 0.536 and 0.557, respectively, confirm that records management and archives research are neither strongly concentrated in a small number of disciplines nor narrowly bounded, but rather constituted and disseminated within a pluralistic flow of knowledge. At the micro level, inflow and outflow diversity indices were calculated for 15 related disciplines, mapped onto a two-dimensional space, and subsequently classified into typological clusters. Disciplines falling within the high-inflow/high-outflow (HIHO) group, such as history, the humanities, and sociology, were found to interpret records in social and artistic contexts and to participate in reciprocal knowledge circulation. In contrast, the records management and archival preservation field, which belongs to the low-inflow/low-outflow (LILO) group, demonstrated strong internal cohesion through concentrated linkages with a small number of adjacent disciplines.

The electronic records management environment of the National Archives of Korea (NAK) is undergoing a structural transition toward an integrated management architecture based on a shared repository, with the transfer of records likewise being reorganized from physical transfer to a management authority transfer model. These developments necessitate comprehensive changes to both the operational modalities and the structure of NAK’s electronic records management functions. This study aims to examine the systemic transformation accompanying the introduction of the Records and Archives Management System (RAMS) and to propose directions for transforming electronic records management practices. A PESTEL analysis was conducted to identify shifts in the external environment surrounding the electronic records management framework, and a SWOT analysis was conducted to diagnose the strengths and limitations of NAK’s current electronic records management system. The development trajectory of the NAK’s electronic records management framework and the operational structure of the current Records and Archives Management Platform (RAMP) were also reviewed to elucidate structural changes in the internal environment. Expert consultations were subsequently conducted with internal practitioners, system specialists, and data experts at the NAK to gather perspectives on operational difficulties and improvement requirements, and to validate the proposed directions for electronic records management transformation. The findings indicate that the NAK must move beyond its existing passive management model―centered on transfer and inspection―toward a proactive management regime in which quality control is exercised from the point of records creation, and that the establishment of a continuous quality control–based monitoring system under a management authority transfer framework is required. In addition, an artificial intelligence (AI)–ready data management framework is suggested to support the intelligent transformation of archival services and the broader integration of AI. The significance of this study lies in proposing directions for transforming electronic records management practices in response to the rapidly evolving electronic records environment and system changes in the AI era, while also presenting practical operational directions for a shared repository-based electronic records management framework.

This study examines the entity structure of the foundational “unit task” as the structural cause of the current records retention schedule’s inability to represent business context and proposes its redesign as a graph model based on the Records in Contexts (RiC) standard. The unit task carries a “dual status,” simultaneously functioning as a unit of business classification and a unit for aggregating records and assigning retention periods, and consequently cannot be mapped exclusively to either Activity or RecordSet in RiC-CM 1.0; this duality results in the elimination of the core production relationship (documentedBy) between activities and record sets. This study separates the two entities and implements seven relationship types conforming to RiC-O 1.1 across three layers: JSON Schema, JSON-LD, and SHACL. Application to 12 unit tasks drawn from the ETRI records classification scheme (2024) yielded 12 production relationships and 19 contextual relationships that could not be represented in the current system, thereby confirming the structural validity and representational capacity of the entity-separation model.