Visualization as a service for scientific data

David Pugmire, James Kress, Jieyang Chen, Hank Childs, Jong Choi, Dmitry Ganyushin, Berk Geveci, Mark Kim, Scott Klasky, Xin Liang, Jeremy Logan, Nicole Marsaglia, Kshitij Mehta, Norbert Podhorszki, Caitlin Ross, Eric Suchyta, Nick Thompson, Steven Walton, Lipeng Wan, Matthew Wolf

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

50 Citations (SciVal)


One of the primary challenges facing scientists is extracting understanding from the large amounts of data produced by simulations, experiments, and observational facilities. The use of data across the entire lifetime ranging from real-time to post-hoc analysis is complex and varied, typically requiring a collaborative effort across multiple teams of scientists. Over time, three sets of tools have emerged: One set for analysis, another for visualization, and a final set for orchestrating the tasks. This trifurcated tool set often results in the manual assembly of analysis and visualization workflows, which are one-off solutions that are often fragile and difficult to generalize. To address these challenges, we propose a serviced-based paradigm and a set of abstractions to guide its design. These abstractions allow for the creation of services that can access and interpret data, and enable interoperability for intelligent scheduling of workflow systems. This work results from a codesign process over analysis, visualization, and workflow tools to provide the flexibility required for production use. Finally, this paper describes a forward-looking research and development plan that centers on the concept of visualization and analysis technology as reusable services, and also describes several realworld use cases that implement these concepts.

Original languageEnglish
Title of host publicationDriving Scientific and Engineering Discoveries Through the Convergence of HPC, Big Data and AI - 17th Smoky Mountains Computational Sciences and Engineering Conference, SMC 2020, Revised Selected Papers
EditorsJeffrey Nichols, Arthur ‘Barney’ Maccabe, Suzanne Parete-Koon, Becky Verastegui, Oscar Hernandez, Theresa Ahearn
Number of pages18
StatePublished - 2021
Event17th Smoky Mountains Computational Sciences and Engineering Conference, SMC 2020 - Virtual, Online
Duration: Aug 26 2020Aug 28 2020

Publication series

NameCommunications in Computer and Information Science
Volume1315 CCIS
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937


Conference17th Smoky Mountains Computational Sciences and Engineering Conference, SMC 2020
CityVirtual, Online

Bibliographical note

Publisher Copyright:
© Springer Nature Switzerland AG 2020.


  • High-performance computing
  • In situ analysis
  • Scientific visualization
  • Visualization

ASJC Scopus subject areas

  • General Computer Science
  • General Mathematics


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