The Typed Graph Model -- a Supermodel for Model Management and Data Integration

TL;DR

This paper introduces a schema-bound Typed Graph Model that enhances data quality and analysis by using hyper-nodes and hyper-edges, serving as a supermodel for various data models in management and integration.

Contribution

The paper proposes a new schema-bound Typed Graph Model with hyper-structures, improving data quality and analysis, and demonstrating its expressive power and superiority over existing models.

Findings

Model is at least as expressive as popular data models

Enhances data quality and analysis capabilities

Supermodel for model management and data integration

Abstract

In recent years, the Graph Model has become increasingly popular, especially in the application domain of social networks. The model has been semantically augmented with properties and labels attached to the graph elements. It is difficult to ensure data quality for the properties and the data structure because the model does not need a schema. In this paper, we propose a schema bound Typed Graph Model with properties and labels. These enhancements improve not only data quality but also the quality of graph analysis. The power of this model is provided by using hyper-nodes and hyper-edges, which allows to present data structures on different abstraction levels. We prove that the model is at least equivalent in expressive power to most popular data models. Therefore, it can be used as a supermodel for model management and data integration. We illustrate by example the superiority of this model over the property graph data model of Hidders and other prevalent data models, namely the relational, object-oriented, XML model, and RDF Schema.