mlsanityData to 14 Oct 2026

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

arXiv 2409.09058 ↗First posted 1 Sep 2024cs.DC cs.AI cs.LGcited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 4 of its 18 references that are in the map. First posted on arXiv 1 Sep 2024.

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References · 4

  1. 2024Credit Card Fraud Detection Using Advanced Transformer Modelcited by 26
  2. 2024CU-Net: a U-Net architecture for efficient brain-tumor segmentation on BraTS 2019 datasetcited by 24
  3. 2024Advanced User Credit Risk Prediction Model using LightGBM, XGBoost and Tabnet with SMOTEENNcited by 10
  4. 2024Advanced Payment Security System:XGBoost, LightGBM and SMOTE Integratedcited by 8

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