Abstract
In this paper, we present the virtual knowledge graph (VKG) paradigm for data integration and access, also known in the literature as Ontology-based Data Access. Instead of structuring the integration layer as a collection of relational tables, the VKG paradigm replaces the rigid structure of tables with the flexibility of graphs that are kept virtual and embed domain knowledge. We explain the main notions of this paradigm, its tooling ecosystem and significant use cases in a wide range of applications. Finally, we discuss future research directions.
Highlights
Most medium-sized and large organizations face the problem of having to deal with large and complex collections of data
In this paper, we present the virtual knowledge graph (VKG) paradigm for data integration and access, known in the literature as Ontology-based Data Access
We present here a paradigm for data integration that inherently exploits data virtualization, and that in addition overcomes the difficulties of traditional approaches based on the relational model
Summary
Most medium-sized and large organizations face the problem of having to deal with large and complex collections of data. Such high-level representation is formulated in a vocabulary that end-users are familiar with, and the information content of its concepts is defined by means of suitable views over the sources These integration views are typically not materialized, but are kept virtual, and this makes it possible to query the data without paying a price in terms of storage and time for the data to be made accessible. The logics of this family are lightweight, in the sense that they combine a restricted (but carefully tuned) expressive power with good computational properties They have been designed so that inference (and query answering) taking into account the domain knowledge is especially efficient with respect to large amounts of data [14, 15], which is a crucial property in any data integration scenario.
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