Abstracting data in distributed ledger systems for higher level analytics and visualizations

TL;DR

This paper proposes an abstraction layer architecture for distributed ledger systems to enable higher-level analytics and visualizations, improving auditability and user interface development.

Contribution

It introduces a novel abstraction layer architecture that facilitates advanced analytics and visualization of distributed ledger data, addressing limitations of low-level data analysis.

Findings

Enhanced analytics capabilities demonstrated in a regulated sector use case.

Improved auditability and user interface development for distributed ledgers.

Framework supports high-level analysis beyond traditional block explorers.

Abstract

By design, distributed ledger technologies persist low-level data which makes conducting complex business analysis of the recorded operations challenging. Existing blockchain visualization and analytics tools such as block explorers tend to rely on this low-level data and complex interfacing to provide enriched level of analytics. The ability to derive richer analytics could be improved through the availability of a higher level abstraction of the data. This article proposes an abstraction layer architecture that enables the design of high-level analytics of distributed ledger systems and the decentralized applications that run on top. Based on the analysis of existing initiatives and identification of the relevant user requirements, this work aims to establish key insights and specifications to improve the auditability and intuitiveness of distributed ledger systems by leveraging the development of future user interfaces. To illustrate the benefits offered by the proposed abstraction layer architecture, a regulated sector use case is explored.