An Integrated Architecture for Inclusive Big Data Analytics Ecosystems: Bridging Technological Infrastructure, Participatory Governance, and Policy Coherence

سال انتشار: 1405
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 17

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ITNAF01_1158

تاریخ نمایه سازی: 14 آبان 1405

چکیده مقاله:

The rapid proliferation of big data analytics and artificial intelligence (AI) has created powerful ecosystems that increasingly shape societal outcomes. However, existing architectures predominantly prioritize technical performance and economic value, often marginalizing social equity, democratic participation, and policy coherence. This paper proposes a novel, multi-layered integrated architecture for inclusive big data analytics ecosystems that systematically interconnects three previously siloed pillars: (۱) scalable and ethical technological infrastructure, (۲) participatory and polycentric governance mechanisms, and (۳) adaptive policy coherence frameworks. Drawing on socio-technical systems theory, polycentric governance scholarship, and recent advances in responsible AI, we introduce the Inclusive Big Data Analytics Ecosystem Architecture (IBDA-EA). The architecture consists of five interdependent layers: (i) Inclusive Data Layer, (ii) Ethical AI & Analytics Layer, (iii) Participatory Governance Layer, (iv) Policy Coherence Layer, and (v) Continuous Feedback & Adaptation Layer. Each layer incorporates innovative components such as "Community Data Trusts", "Deliberative Analytics Sandboxes", and "Dynamic Policy Alignment Protocols". Through conceptual modeling, illustrative diagrams, and comparative analysis with existing frameworks (e.g., Lambda/Kappa architectures, EU AI Act governance models), we demonstrate how IBDA-EA enables marginalized communities to co-shape analytics outcomes while maintaining scalability and trustworthiness. The architecture is designed to serve as both a theoretical contribution and a practical blueprint for policymakers, platform operators, and civil-society organizations. Directions for future empirical validation in diverse geopolitical contexts are discussed.

نویسندگان

Majid Shabani

PhD student in artificial intelligence and robotics, Faculty of artificial intelligence and cognitive sciences, Imam Hossein Comprehensive University, Tehran, Iran

Hossein Saberi

Assistant Professor, Faculty of artificial intelligence and cognitive sciences, Imam Hossein Comprehensive University, Tehran, Iran