Sabrina: Modeling and Visualization of Economy Data with Incremental Domain Knowledge

TL;DR

Sabrina is a visualization tool that integrates heterogeneous economic data and domain knowledge to help financial analysts understand large-scale financial landscapes through interactive analysis.

Contribution

It introduces a pipeline for fusing diverse data sources with incremental domain knowledge into a unified visual analysis framework for economic data.

Findings

User study with domain experts shows Sabrina eases analysis.

The pipeline effectively integrates heterogeneous data sources.

Visualization improves understanding of economic landscapes.

Abstract

Investment planning requires knowledge of the financial landscape on a large scale, both in terms of geo-spatial and industry sector distribution. There is plenty of data available, but it is scattered across heterogeneous sources (newspapers, open data, etc.), which makes it difficult for financial analysts to understand the big picture. In this paper, we present Sabrina, a financial data analysis and visualization approach that incorporates a pipeline for the generation of firm-to-firm financial transaction networks. The pipeline is capable of fusing the ground truth on individual firms in a region with (incremental) domain knowledge on general macroscopic aspects of the economy. Sabrina unites these heterogeneous data sources within a uniform visual interface that enables the visual analysis process. In a user study with three domain experts, we illustrate the usefulness of Sabrina, which eases their analysis process.