A Knowledge-Oriented Approach to Enhance Integration and Communicability in the Polkadot Ecosystem

TL;DR

This paper introduces POnto, a domain ontology for Polkadot, to improve data integration and communication, enabling broader participation and AI application development in the complex multi-chain ecosystem.

Contribution

It presents a novel knowledge-oriented framework with an ontology and query engine roadmap to enhance data analysis and accessibility in Polkadot.

Findings

Validated through expert feedback and community insights

Facilitates formal understanding of Polkadot's ecosystem concepts

Supports development of AI-based applications in Polkadot

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.