Documenting Data Integration Using Knowledge Graphs

Abstract

With the increasing volume of data on the Web and the proliferation of published knowledge graphs, there is a growing need for improved data management and information extraction. However, heterogeneity issues across the data sources, i.e., various formats and systems, negatively impact efficient access, manage, reuse, and analyze the data. A data integration system (DIS) provides uniform access to heterogeneous data sources and their relationships; it offers a unified and comprehensive view of the data. DISs resort to mapping rules, expressed in declarative languages like RML, to align data from various sources to classes and properties defined in an ontology. This work defines a knowledge graph where data integration systems are represented as factual statements. The aim of this work is to provide the basis for integrated analysis of data collected from heterogeneous data silos. The proposed knowledge graph is also specified as a data integration system, that integrates all data integration systems. The proposed solution includes a unified schema, which defines and explains the relationships between all elements in the data integration system DIS=⟨G, S, M, F⟩. The results suggest that factual statements from the proposed knowledge graph, improve the understanding of the features that characterize knowledge graphs declaratively defined like data integration systems.