Data-Centric Design: Introducing An Informatics Domain Model And Core Data Ontology For Computational Systems

TL;DR

This paper presents a novel data-centric framework with a core ontology and domain model that enhances security, interoperability, and scalability in computational systems by categorizing data into objects, events, concepts, and actions.

Contribution

It introduces the Core Data Ontology and Informatics Domain Model, shifting system design towards a data-centric approach with a quadrimodal data categorization scheme.

Findings

Improves data security, provenance, and auditability

Supports AI development and multimodal data management

Facilitates scalable and interoperable data ecosystems

Abstract

The Core Data Ontology (CDO) and the Informatics Domain Model represent a transformative approach to computational systems, shifting from traditional node-centric designs to a data-centric paradigm. This paper introduces a framework where data is categorized into four modalities: objects, events, concepts, and actions. This quadrimodal structure enhances data security, semantic interoperability, and scalability across distributed data ecosystems. The CDO offers a comprehensive ontology that supports AI development, role-based access control, and multimodal data management. By focusing on the intrinsic value of data, the Informatics Domain Model redefines system architectures to prioritize data security, provenance, and auditability, addressing vulnerabilities in current models. The paper outlines the methodology for developing the CDO, explores its practical applications in fields such as AI, robotics, and legal compliance, and discusses future directions for scalable, decentralized, and interoperable data ecosystems.