iV-Morph: Interactive Visual Metamorphosis for Multi-view Data Exploration

Multifaceted datasets, such as those found on social media platforms, are characterized by interconnected entities like users, posts, reactions, and comments. Each entity holds diverse attributes, such as user profiles, post timestamps, and reaction types. Relationships between entities form dynamically over time as users follow others, engage with posts, or exchange comments. Entities and their relationships may also be embedded in space, for example, when users share their location or posts include GPS-tagged photos. Such multifaceted data, including space, time, attributes, and relationships, presents significant challenges for their interactive visual analysis.

The standard approach to tackling these challenges is to use a multi-view visualization. The key idea is to provide multiple dedicated visualizations, each focusing on a particular data facet. Typically, all views are shown simultaneously side by side in a suitable arrangement. Yet, despite its wide use, multi-view visualization also faces challenges on its own. These include the difficulty for users to integrate information across diverse visual representations, coordination issues between views, and arranging multiple visualizations side by side when display space is limited. Another key concern is context switching when users look from one view to another. Context switching can adversely disrupt the analysis flow due to the increased cognitive effort - and hinder a seamless exploration of multifaceted datasets.

To address these issues, researchers have proposed alternative approaches that integrate views more smoothly by embedding visualizations directly within other visualizations. For example, responsive matrix cells facilitate the exploration of the relationship facet by a matrix visualization, and the attributes facet of each entity is embedded with another visual representation directly into selected cells of the matrix. While such integrated solutions attempt to ease some challenges, they introduce their own drawbacks, including reduced readability and perceptual difficulties when integrating information. Both approaches may still suffer from the distractions caused by attention shifts during context switching.

Our project, the iV-Morph (Interactive Visual Metamorphosis) aims to tackle these challenges by using smooth transitions between visual representations. The goal is to bridge the visual and conceptual gaps between non-trivial multifaceted visualizations, enabling fluid exploration across diverse views. The project builds on the idea of multi-view visualization but focuses on minimizing the cognitive load due to context-switching through seamless view transformations. Instead of showing multiple views simultaneously on the display, iV-Morph shows one view at a time, but that view can transform itself to different visualization techniques. To achieve this, we aim to investigate the following aspects:

  • Conceptualize the idea of a shape-shifting view that is capable of metamorphosis to take on the form of different visualization techniques
  • Develop smooth transitions that can transform different visualization techniques with reduced cognitive load for users
  • Combine multiple shape-shifting views, smooth transitions, and appropriate interaction techniques in a framework that facilitates comprehensive data exploration activities.
  • Conduct comparative evaluation studies of traditional side-by-side views and our new one-after-the-other smoothly transitioned views

With iV-Morph, we hope to provide a novel approach to exploring complex multifaceted data, improving user experience and enabling intuitive data insights.

Research Interest

Smooth Transitions

Interaction techniques

Animations

News

Project start: Feb 8, 2024

Funding

DFG

Institutions

VA VAC Uni Rostock