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

• URL: http://arxiv.org/abs/2102.10133v1
• Date: Fri, 19 Feb 2021 19:34:12 GMT
• Title: Abstracting data in distributed ledger systems for higher level analytics and visualizations
• Authors: Leny Vinceslas, Hirsh Pithadia, Safak Dogan, Srikumar Sundareshwar, Ahmet M. Kondoz
• Abstract summary: This article proposes an abstraction layer architecture that enables the design of high-level analytics of distributed ledger systems. Based on the analysis of existing initiatives and identification of the relevant user requirements, this work aims to establish key insights and specifications.
• Score: 1.5381930379183162
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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.

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