A Knowledge-Oriented Approach to Enhance Integration and Communicability in the Polkadot Ecosystem
August 01, 2023 Β· Declared Dead Β· π arXiv.org
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Authors
Marcio Ferreira Moreno, Rafael Rossi de Mello BrandΓ£o
arXiv ID
2308.00735
Category
cs.AI: Artificial Intelligence
Cross-listed
cs.DC,
cs.IR,
cs.NI
Citations
0
Venue
arXiv.org
Last Checked
4 months ago
Abstract
The Polkadot ecosystem is a disruptive and highly complex multi-chain architecture that poses challenges in terms of data analysis and communicability. Currently, there is a lack of standardized and holistic approaches to retrieve and analyze data across parachains and applications, making it difficult for general users and developers to access ecosystem data consistently. This paper proposes a conceptual framework that includes a domain ontology called POnto (a Polkadot Ontology) to address these challenges. POnto provides a structured representation of the ecosystem's concepts and relationships, enabling a formal understanding of the platform. The proposed knowledge-oriented approach enhances integration and communicability, enabling a wider range of users to participate in the ecosystem and facilitating the development of AI-based applications. The paper presents a case study methodology to validate the proposed framework, which includes expert feedback and insights from the Polkadot community. The POnto ontology and the roadmap for a query engine based on a Controlled Natural Language using the ontology, provide valuable contributions to the growth and adoption of the Polkadot ecosystem in heterogeneous socio-technical environments.
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