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DaVE -- A Curated Database of Visualization Examples

Jens Koenen, Marvin Petersen, Christoph Garth, Tim Gerrits

TL;DR

DaVE addresses the need for an accessible, HPC-oriented repository of visualization techniques by curating state-of-the-art visualization examples with domain- and data-specific descriptors and ready-to-run containerized templates. The approach combines a web-based exploration platform (with interactive previews) and containerized execution environments, enabling easy testing and integration across heterogeneous HPC systems. An expert evaluation with five scientists showed high usability and potential for knowledge transfer, though more examples and tooling diversity are needed. The work lays the groundwork for a community-driven visualization hub for HPC, with plans for automation, ML-based recommendations, and an API to broaden adoption.

Abstract

Visualization, from simple line plots to complex high-dimensional visual analysis systems, has established itself throughout numerous domains to explore, analyze, and evaluate data. Applying such visualizations in the context of simulation science where High-Performance Computing (HPC) produces ever-growing amounts of data that is more complex, potentially multidimensional, and multimodal, takes up resources and a high level of technological experience often not available to domain experts. In this work, we present DaVE -- a curated database of visualization examples, which aims to provide state-of-the-art and advanced visualization methods that arise in the context of HPC applications. Based on domain- or data-specific descriptors entered by the user, DaVE provides a list of appropriate visualization techniques, each accompanied by descriptions, examples, references, and resources. Sample code, adaptable container templates, and recipes for easy integration in HPC applications can be downloaded for easy access to high-fidelity visualizations. While the database is currently filled with a limited number of entries based on a broad evaluation of needs and challenges of current HPC users, DaVE is designed to be easily extended by experts from both the visualization and HPC communities.

DaVE -- A Curated Database of Visualization Examples

TL;DR

DaVE addresses the need for an accessible, HPC-oriented repository of visualization techniques by curating state-of-the-art visualization examples with domain- and data-specific descriptors and ready-to-run containerized templates. The approach combines a web-based exploration platform (with interactive previews) and containerized execution environments, enabling easy testing and integration across heterogeneous HPC systems. An expert evaluation with five scientists showed high usability and potential for knowledge transfer, though more examples and tooling diversity are needed. The work lays the groundwork for a community-driven visualization hub for HPC, with plans for automation, ML-based recommendations, and an API to broaden adoption.

Abstract

Visualization, from simple line plots to complex high-dimensional visual analysis systems, has established itself throughout numerous domains to explore, analyze, and evaluate data. Applying such visualizations in the context of simulation science where High-Performance Computing (HPC) produces ever-growing amounts of data that is more complex, potentially multidimensional, and multimodal, takes up resources and a high level of technological experience often not available to domain experts. In this work, we present DaVE -- a curated database of visualization examples, which aims to provide state-of-the-art and advanced visualization methods that arise in the context of HPC applications. Based on domain- or data-specific descriptors entered by the user, DaVE provides a list of appropriate visualization techniques, each accompanied by descriptions, examples, references, and resources. Sample code, adaptable container templates, and recipes for easy integration in HPC applications can be downloaded for easy access to high-fidelity visualizations. While the database is currently filled with a limited number of entries based on a broad evaluation of needs and challenges of current HPC users, DaVE is designed to be easily extended by experts from both the visualization and HPC communities.
Paper Structure (9 sections, 3 figures)

This paper contains 9 sections, 3 figures.

Table of Contents

  1. Introduction
  2. Background and Related Work
  3. DaVE
  4. Web Platform for Visualization Exploration
  5. Integration Through Containerized Examples
  6. Extending DaVE
  7. Evaluation and Expert Feedback
  8. Discussion
  9. Conclusion and Future Work

Figures (3)

  • Figure 1: Through the adaptive web interface, DaVE provides a gallery of visualization examples that can be searched and filtered through tags and requirements.
  • Figure 2: Tags describing data type, visualization technique, and domain of the example are included in the search. Example images, optional interactive previews, and text descriptions provide further information on the technique and usage of provided resources.
  • Figure 3: DaVE supports interactive examples on the websites through VTK.js , allowing users to directly test visualizations.