Ontological View-based Semantic Integration Framework in Decentralized Environments
Abstract
In the realm of decentralized, epistemic environments, the interpretation of reality is inherently diverse and complex. This diversity stems from the multitude of autonomous entities, each with its unique set of beliefs and perspectives, leading to a wide array of ontological views. Such environments challenge the conventional ontology frameworks and their representation, which are predominantly designed from a singular, centralized observer’s viewpoint. These traditional approaches prove inadequate in addressing the nuances and multiplicity of interpretations that decentralized systems present.
This thesis explores the challenge of achieving semantic interoperability in decentralized systems, where diverse and autonomous systems operate without a unified framework. An Ontological View-Based Semantic Integration Framework (OVSIF) is introduced, aiming to enhance collaboration and information exchange across disparate systems through a novel approach to semantic integration.
Grounded in a thorough literature review, the work identifies significant gaps in existing semantic integration strategies. Building on this, a novel classification of environments— closed, decentralized, or open—is proposed. This classification aids in applying semantic strategies tailored to the specific challenges characteristic of each environment type. Following this, a new conceptualization structure is developed to align with the epistemic nature of decentralized systems, utilizing modal logic as the representation language to support precise semantic mappings. This setup promotes a hybrid approach that accommodates both intensional and extensional semantics.
The proposed framework for Semantic Integration in this research introduces an approach for integrating diverse ontological views without the necessity for a global consensus. This approach allows for adaptable and context-specific solutions. The practical applicability of the framework is demonstrated through logical analysis, theorem proving, and specific applications in the healthcare application domain, which illustrates its potential pertinence to improve operational efficiency and semantic coherence.