Award Abstract # 1528203
III: Small: Technologies for Creating Explanatory and Exploratory Animations from Scientific Data

NSF Org: IIS
Division of Information & Intelligent Systems
Recipient: UNIVERSITY OF CALIFORNIA, DAVIS
Initial Amendment Date: September 14, 2015
Latest Amendment Date: November 29, 2017
Award Number: 1528203
Award Instrument: Standard Grant
Program Manager: Hector Munoz-Avila
IIS
 Division of Information & Intelligent Systems
CSE
 Directorate for Computer and Information Science and Engineering
Start Date: October 1, 2015
End Date: September 30, 2020 (Estimated)
Total Intended Award Amount: $499,996.00
Total Awarded Amount to Date: $507,996.00
Funds Obligated to Date: FY 2015 = $499,996.00
FY 2018 = $8,000.00
History of Investigator:
  • Kwan-Liu Ma (Principal Investigator)
    ma@cs.ucdavis.edu
Recipient Sponsored Research Office: University of California-Davis
1850 RESEARCH PARK DR STE 300
DAVIS
CA  US  95618-6153
(530)754-7700
Sponsor Congressional District: 04
Primary Place of Performance: University of California-Davis
One Shields Avenue
Davis
CA  US  95616-5270
Primary Place of Performance
Congressional District:
04
Unique Entity Identifier (UEI): TX2DAGQPENZ5
Parent UEI:
NSF Program(s): Info Integration & Informatics
Primary Program Source: 01001516DB NSF RESEARCH & RELATED ACTIVIT
01001819DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 7364, 7923, 9251
Program Element Code(s): 736400
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.070

ABSTRACT

Animation is a powerful, expressive medium for visual explanations and for telling stories with data. Scientists make extensive use of animations to explain their findings and to illustrate complex phenomena. By presenting time as time, animation is one of the most natural ways to illustrate how objects evolve and interact, and how they change in shape, size, position, and spatial relationship to other objects over time. Both commercial and open-source visualization tools offer a wealth of visualization techniques, enabling scientists to explore their data and to generate individual images to capture key aspects of the subject under study. However, most visualization packages include very limited support for creating explanatory animations. As a result, scientists who wish to use animations to illustrate their findings must spend considerable amounts of time learning how to produce animations, often using external software packages, or turn to professional animators or production specialists for assistance. This research aims to develop adequate support for composing animation content and constructing scientific video narratives, and also extend explanatory animation to exploratory animation and study its usability. This project will thus have a significant impact on both the visualization researchers and users in a range of domains, including education. The new concepts introduced in this project will inspire others to also develop similar and even better support for scientific storytelling using visualization. More users will benefit from such advanced visualization technologies leading to high productivity in their work, or support educational and outreach activities. The research team will continue collaboration with a science museum to seek the opportunities to convert explanatory/exploratory animations into interactive exhibits. Research will be integrated into teaching, in the form of special topic courses, the establishment of internships with industry and national laboratories, and the introduction of visualization technology to students from other disciplines. The project will provide an environment for research training for graduate and undergraduate students.

This research will introduce key technologies that can greatly increase scientists' ability to make visualization animations and video narratives for storytelling. To facilitate scientific narrations using animations, this project will design a semi-automatic animation generation system tightly coupled with the interactive data exploration and visualization process. That is to make the process of animation and storytelling a first class citizen within exploratory data visualization tools. This will allow the scientists to focus on gaining insight from their data, and the visualization tools should assist them in assembling findings together into a coherent story for presentation. This project will design methods to choose views, camera paths, lighting, transitions, etc. for users. Methods for users to interact with animations will also be designed, instead of passively watching, to achieve new levels of inspection and apprehension. Explorable images, a powerful and novel concept introduced for realizing exploratory animation, enables multidimensional data exploration using a medium comparable to a video in terms of compactness and simplicity. The task of realizing these novel concepts and designs, and integrating them into scientists' workflows and tools, will be challenging. This research will conduct extensive evaluation of the animation support, with the participation of domain scientists who are prospective users of the new technology. The lessons learned in this project may establish guidelines for the effective use of animation in explaining complex phenomena, and suggest a new framework for next-generation visualization systems. The project web site (http://vis.cs.ucdavis.edu/NSF/IIS1528203) will provide access to research results, including data and prototype software.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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(Showing: 1 - 10 of 13)
Chien-Hsin Hsueh, Jacqueline Chu, Kwan-Liu Ma, Joyce Ma, and Jennifer Frazier "Fostering comparisons: Designing an interactive exhibit that visualizes marine animal behaviors" IEEE Pacific Visualization Symposium , 2016 , p.259 10.1109/PACIFICVIS.2016.7465282
Chien-Hsin Hsueh, Jia-Kai Chou, Kwan-Liu Ma "A study of using motion for comparative visualization" IEEE Pacific Visualization Symposium , 2016 , p.219 10.1109/PACIFICVIS.2016.7465274
Chris Bryan, Gregory Guterman, Kwan-Liu Ma, Harris Lewin, Denis Larkin, Jaebum Kim, Jian Ma, and Marta Farre "Synteny Explorer: An Interactive Visualization Application for Teaching Genome Evolution" IEEE Transactions on Visualization and Computer Graphics , v.23 , 2017 , p.711 https://doi.org/10.1109/TVCG.2016.2598789
Christopher Bryan, Kwan-Liu Ma, and Jonathan Woodring "Temporal Summary Images: An Approach to Narrative Visualization via Interactive Annotation Generation and Placement" IEEE Transactions on Visualization and Computer Graphics , v.23 , 2017 , p.511 https://doi.org/10.1109/TVCG.2016.2598876
Franz Sauer, Tyson Neuroth, Jacqueline Chu, and Kwan-Liu Ma "Audience-Targeted Design Considerations for Effective Scientific Storytelling" IEEE Computing in Science and Engineering , v.18 , 2016 , p.68 https://doi.org/10.1109/MCSE.2016.100
Jacqueline Chu, Chris Bryan, Min Shih, Leonardo Ferrer, and Kwan-Liu Ma "Navigable Videos for Presenting Scientific Data on Affordable Head-Mounted Displays" Proceedings of ACM MMSys 2017 , 2017 , p.250 http://doi.acm.org/10.1145/3083187.3084015
Jianping Kelvin Li and Kwan-Liu Ma "P4: Portable Parallel Processing Pipelines for Interactive Information Visualization" IEEE Transactions on Visualization and Computer Graphics , v.26 , 2020 , p.1548 https://doi.org/10.1109/TVCG.2018.2871139
Jianping Kelvin Li and Kwan-Liu Ma "P5: Portable Progressive Parallel Processing Pipelines for Interactive Data Analysis and Visualization" IEEE Transactions on Visualization and Computer Graphics (VIS 2019 Early Access) , v.26 , 2020 , p.1151 https://doi.org/10.1109/TVCG.2019.2934537
Joyce Ma, Kwan-Liu Ma, Jennifer Frazier "Decoding a Complex Visualization in a Science Museum - An Empirical Study" IEEE Transactions on Visualization and Computer Graphics , v.26 , 2020 , p.472 https://doi.org/10.1109/TVCG.2019.2934401
Keshav Dasu, Takanori Fujiwara, and Kwan-Liu Ma "An Organic Visual Metaphor for Public Understanding of ConditionalCo-occurrences," Proceedings of 2018 IEEE SciVis , 2018 10.1109/SciVis.2018.8823624
Min Shih, Charles Rozhon, and Kwan-Liu Ma "A Declarative Grammar of Flexible Volume Visualization Pipelines" IEEE Transactions on Visualization and Computer Graphics , v.25 , 2019 , p.1050 10.1109/TVCG.2018.2864841
(Showing: 1 - 10 of 13)

PROJECT OUTCOMES REPORT

Disclaimer

This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.

Animation is a powerful, expressive medium for visual explanations and for telling stories with data.  For example, by presenting time as time, animation is one of the most natural ways to illustrate how objects evolve and interact, and how they change in shape, size, position, and spatial relationship to other objects over time. This project developed new user interfaces and methods for composing and using animations in data visualization to better support scientific exploration, discovery, and storytelling.  Methods for users to interact with animations were also studied, instead of passively watching, to achieve new levels of inspection and apprehension.  One design derived based on our extensive user study suggests how to communicate complex, multi-layered data in public settings. Another design enables scientists to focus on gaining insight from their data, and the visualization tools assist them in assembling findings together into a coherent story for presentation. In addition to technical publications presenting our design concepts, algorithms, and interactive systems, this project produced open-source software tools and libraries, interactive exhibits for science museum, web-based visual storytelling contents, etc. Furthermore, the lessons learned from our user studies helped establish guidelines for the effective use of animation in explaining complex phenomena and also suggested a new framework for next-generation visualization systems.

 


Last Modified: 12/29/2020
Modified by: Kwan-Liu Ma

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