
TL;DR
This paper introduces a schema-bound Typed Graph Model with properties and labels, enhancing data quality and analysis capabilities by using hyper-nodes and hyper-edges for multi-level abstraction, outperforming existing models.
Contribution
The paper proposes a new schema-bound Typed Graph Model with hyper-nodes and hyper-edges, improving data quality and analysis over existing graph and data models.
Findings
Demonstrates superiority over property graph, relational, object-oriented, and XML models.
Shows improved data quality and analysis capabilities.
Uses hyper-nodes and hyper-edges for multi-level data abstraction.
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 a data structure on different abstraction levels. We demonstrate 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, and XML model.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsGraph Theory and Algorithms · Semantic Web and Ontologies · Advanced Database Systems and Queries
