Data Reasoning Across Heterogeneous and Large-Scale Computational Ecosystems
Keywords:
Data reasoning, heterogeneous systems, federated inference, large-scale computing, semantic interoperability, distributed intelligence, ontology-based reasoningAbstract
As computational ecosystems grow increasingly complex and heterogeneous, data reasoning emerges as a critical capability for ensuring seamless interoperability, intelligent processing, and system-wide optimization. This paper explores the mechanisms by which data reasoning frameworks adapt to large-scale, distributed, and diverse computing infrastructures. Emphasis is placed on semantic interoperability, ontological reasoning, federated knowledge bases, and scalable inference engines capable of functioning across cloud, edge, and high-performance computing nodes.
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