VMetaFlow: A Meta-Framework for Integrating Visualizations in Coordinated View Applications

Abstract

The analysis and exploration of complex data sets are common problems in many areas, including scientific and business domains. This need has led to substantial development of the data visualization field. However, the diversity of problems to which visual data analysis is applied hinders the implementation of a universal solution that meets the current and future needs of all disciplines. In this paper, we present VMetaFlow, a graphical meta-framework to design interactive and coordinated views applications for data visualization. Our meta-framework is based on data flow diagrams since they have proved their value in simplifying the design of data visualizations. VMetaFlow operates as an abstraction layer that encapsulates and interconnects visualization frameworks in a web-based environment, providing them with interoperability mechanisms. The only requirement is that the visualization framework must be accessible through a JavaScript API. We propose a novel data flow model that allows users to define both interactions between multiple data views and how the data flows between visualization and data processing modules. In contrast with previous data-flow-based frameworks for visualization, we separate the view interactions from data items, broadening the expressiveness of our model and supporting the most common types of multi-view interactions. Our meta-framework allows visualization and data analysis experts to focus their efforts on creating data representations and transformations for their applications, whereas nonexperts can reuse previously developed components to design their applications through a user-friendly interface. We validate our approach through a critical inspection with visualization experts and two case studies. We have carefully selected these case studies to illustrate its capabilities. Finally, we compare our approach with the subset flow model designed for multiple coordinated views.