How Knowledge Graph technology is evolving part1(Artificial Intelligence)

Abstract: In recent years, there have been valuable efforts and contributions to make the process of RDF knowledge graph creation traceable and transparent; extending and applying declarative mapping languages is an example. One challenging step is the traceability of procedures that aim to overcome interoperability issues, a.k.a. In most pipelines, data integration is performed by ad-hoc programs, preventing traceability and reusability. However, formal frameworks provided by function-based declarative mapping languages such as FunUL and RML FnO empower expressiveness. Data-level integration can be defined as functions and integrated as part of the mappings performing schema-level integration.