Modeling and exploring semantic view metadata in knowledge graphs with VoSV

A Knowledge Graph (KG) provides a semantic framework for integrating and managing diverse data organizations. This paper introduces VoSV (Vocabulary of Semantic View), a domain-independent vocabulary designed to annotate metadata in semantic views based on a structured Data Design Pattern (DDP). The DDP organizes data into a four-level hierarchical model, supporting scalable maintenance and context-aware exploration. At the core is the Metadata Graph, built using VoSV, which captures detailed, machine-readable metadata about structure, provenance, and quality. These semantic annotations enhance key governance functions such as data lineage, quality evaluation, and usability. The paper also presents an interactive tool for exploring metadata, allowing users to visually inspect metadata elements across multiple levels of the semantic view metadata graph. Together, the DDP, VoSV, and exploration tool promote transparency, accountability, and trust by offering a structured, semantic approach to documenting and managing data within KGs.