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Summary
This summary is machine-generated.

Sabrina 2.0 is a Visual Analytics (VA) approach that integrates diverse financial data, creating firm-to-firm transaction networks. This aids in understanding complex economic relationships and national economies.

Keywords:
Information VisualizationVisual AnalyticsVisualizationVisualization in Finance

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Area of Science:

  • Financial Data Analysis
  • Visual Analytics
  • Economic Modeling

Background:

  • Financial environments are complex, requiring integration of heterogeneous data for holistic understanding.
  • Scattered information across scales hinders comprehension of firm relationships and economic landscapes.

Purpose of the Study:

  • To present Sabrina 2.0, a Visual Analytics (VA) approach for exploring financial data.
  • To develop a pipeline for generating firm-to-firm financial transaction networks.
  • To facilitate a holistic understanding of national economies by integrating data across scales.

Main Methods:

  • Developed Sabrina 2.0, a Visual Analytics (VA) solution for financial data exploration.
  • Created a pipeline to generate firm-to-firm financial transaction networks by fusing firm-level data, sector transactions, and economic domain knowledge.
  • Enabled multi-instance network generation for scenario comparison.

Main Results:

  • Sabrina 2.0 facilitates the generation of insights into financial data.
  • The approach successfully integrates information from individual firms to nation-wide aggregates.
  • Incorporation of transaction models enhances user exploration of national economies.

Conclusions:

  • Sabrina 2.0 provides a robust VA approach for analyzing complex financial environments.
  • The system effectively bridges micro (firm-level) and macro (national) economic data.
  • Expert evaluation confirmed the utility of Sabrina 2.0 in generating economic insights.