DATCloud: A Model-Driven Framework for Multi-Layered Data-Intensive Architectures

2025-01-30

AI Summary

To address the inflexibility in multi-layer system modeling and inefficient cross-role collaboration in data-intensive domains such as healthcare and smart cities, this paper proposes a model-driven framework grounded in the ISO/IEC/IEEE 42010 standard. The framework innovatively integrates structural and behavioral semantics to define a graphical domain-specific language (DSL) metamodel, enabling architectural modeling, formal verification, and iterative refinement. Evaluated on the VASARI cultural heritage system at the Uffizi Gallery, the framework reduced modeling effort by 40% and improved architectural flexibility by 32%. It also incorporates extensible interfaces for code generation and simulation, establishing a reusable, verifiable, and evolvable modeling infrastructure for complex systems across diverse application domains.

Technology Category

• Cognitive Modeling & Cognitive Systems: Agent Architectures
• Knowledge Representation and Reasoning: Description Logics
• Constraint Satisfaction and Optimization: Satisfiability Modulo Theories

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Web applications in cross-disciplinary domains and verticals such as mixed reality, smart cities, and digital health
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems

Abstract

The complexity of multi-layered, data-intensive systems demands frameworks that ensure flexibility, scalability, and efficiency. DATCloud is a model-driven framework designed to facilitate the modeling, validation, and refinement of multi-layered architectures, addressing scalability, modularity, and real-world requirements. By adhering to ISO/IEC/IEEE 42010 standards, DATCloud leverages structural and behavioral meta-models and graphical domain-specific languages (DSLs) to enhance reusability and stakeholder communication. Initial validation through the VASARI system at the Uffizi Gallery demonstrates a 40% reduction in modeling time and a 32% improvement in flexibility compared to manual methods. While effective, DATCloud is a work in progress, with plans to integrate advanced code generation, simulation tools, and domain-specific extensions to further enhance its capabilities for applications in healthcare, smart cities, and other data-intensive domains.

Problem

• Data-intensive Systems
• Flexible Data Processing
• Complex System Design

Innovation

• Modular Hierarchical Design
• Standardized Modeling
• Automated Code Generation