Demonstrating Online Schema Alignment in Decentralized Knowledge Graphs Querying

Abstract

Decentralized Knowledge Graphs querying enables integrating distributed data without centralization, but is highly sensitive to vocabulary heterogeneity. Query issuers cannot realistically anticipate all vocabulary mismatches, especially when alignment rules are local, scoped, or discovered at runtime. We present an online schema alignment approach for Link Traversal Query Processing (LTQP) that discovers, scopes, and applies alignment rules dynamically during query execution while preserving traversal behavior. This demo paper demonstrates the approach on a decentralized social-media scenario through a web interface built on a Comunica-based LTQP engine. Source code, a CLI, and a reusable library are publicly available. The demonstration shows that online schema alignment recovers complete query results with low overhead, providing a practical foundation for web-scale reasoning in LTQP systems.