Shadow Theory, data model design for data integration

TL;DR

Shadow Theory offers a philosophical foundation for data integration by modeling semantic heterogeneity through shadows and cognitive structures, supported by principles and algebra for practical operations.

Contribution

Introduces Shadow Theory as a novel philosophical approach to address semantic heterogeneity in data integration, with specific design principles and algebraic support.

Findings

Proposes six design principles for data integration.

Develops an algebra to support operations on shadows.

Demonstrates application with enterprise customer data example.

Abstract

For data integration in information ecosystems, semantic heterogeneity is a known difficulty. In this paper, we propose Shadow Theory as the philosophical foundation to address this issue. It is based on the notion of shadows in Plato's Allegory of the Cave. What we can observe are just shadows, and meanings of shadows are mental entities that only exist in viewers' cognitive structures. With enterprise customer data integration example, we proposed six design principles and algebra to support required operations.