English

Redefining Data-Centric Design: A New Approach with a Domain Model and Core Data Ontology for Computational Systems

Distributed, Parallel, and Cluster Computing 2024-09-17 v1 Artificial Intelligence Machine Learning

Abstract

This paper presents an innovative data-centric paradigm for designing computational systems by introducing a new informatics domain model. The proposed model moves away from the conventional node-centric framework and focuses on data-centric categorization, using a multimodal approach that incorporates objects, events, concepts, and actions. By drawing on interdisciplinary research and establishing a foundational ontology based on these core elements, the model promotes semantic consistency and secure data handling across distributed ecosystems. We also explore the implementation of this model as an OWL 2 ontology, discuss its potential applications, and outline its scalability and future directions for research. This work aims to serve as a foundational guide for system designers and data architects in developing more secure, interoperable, and scalable data systems.

Keywords

Cite

@article{arxiv.2409.09058,
  title  = {Redefining Data-Centric Design: A New Approach with a Domain Model and Core Data Ontology for Computational Systems},
  author = {William Johnson and James Davis and Tara Kelly},
  journal= {arXiv preprint arXiv:2409.09058},
  year   = {2024}
}
R2 v1 2026-06-28T18:44:06.363Z