DCHCNov 10, 2021

A Visual Analytics Framework for Distributed Data Analysis Systems

arXiv:2111.05979v14 citations
Originality Synthesis-oriented
AI Analysis

This work addresses usability challenges for users of distributed data analysis systems, but it appears incremental as it builds on existing visual analytics and distributed system concepts without claiming major breakthroughs.

The paper tackles the complexity of user interactions in distributed data analysis systems by proposing a visual analytics framework that facilitates server management, data incorporation, analysis execution, progress monitoring, and result exploration through interactive visualizations, demonstrated with use cases in earth science and Sustainable Human Building Ecosystem research.

This paper proposes a visual analytics framework that addresses the complex user interactions required through a command-line interface to run analyses in distributed data analysis systems. The visual analytics framework facilitates the user to manage access to the distributed servers, incorporate data from the source, run data-driven analysis, monitor the progress, and explore the result using interactive visualizations. We provide a user interface embedded with generalized functionalities and access protocols and integrate it with a distributed analysis system. To demonstrate our proof of concept, we present two use cases from the earth science and Sustainable Human Building Ecosystem research domain.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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