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SOCRAT Platform Design: A Web Architecture for Interactive Visual Analytics Applications.

Alexandr A Kalinin1, Selvam Palanimalai1, Ivo D Dinov1

  • 1University of Michigan.

Proceedings of the 2Nd Workshop on Human-In-The-Loop Data Analytics. Workshop on Human-In-The-Loop Data Analytics (2Nd : 2017 : Chicago, Ill.)
|April 10, 2018
PubMed
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This summary is machine-generated.

Researchers developed a modular visual analytics (VA) platform, SOCRAT, to streamline web application development. This open-source tool integrates data management, visualization, and analysis, simplifying complex research workflows.

Keywords:
System DesignVisual AnalyticsWeb Platform Architecture

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Area of Science:

  • Computer Science
  • Data Science
  • Scientific Computing

Background:

  • The web supports interactive applications, but lacks design principles for complex visual analytics (VA) systems.
  • Integrating data management, computation, and analysis into VA web applications is time-consuming for researchers.
  • Existing VA development processes hinder efficient knowledge discovery and hypothesis testing.

Purpose of the Study:

  • To establish design principles for modular VA web application architecture.
  • To present the preliminary design and implementation of the SOCRAT platform.
  • To optimize module interaction, re-usability, and extensibility in VA systems.

Main Methods:

  • Considered design requirements for a module-based VA system architecture.
  • Adopted practices from large-scale web application development.
  • Implemented an open-source platform, SOCRAT, with multi-level modularity and interaction optimization methods.

Main Results:

  • Developed a specification for a modular VA application architecture.
  • Defined methods for optimizing module interaction, re-use, and extension.
  • Implemented an example application demonstrating integration of data management, visualization, and analysis tools.

Conclusions:

  • The SOCRAT platform provides a foundation for building efficient, modular VA web applications.
  • This approach simplifies the integration of diverse analytical tools for researchers.
  • The open-source platform facilitates data management, interactive visualization, and analysis tasks.