Welcome to the new version of CaltechAUTHORS. Login is currently restricted to library staff. If you notice any issues, please email coda@library.caltech.edu
Published April 2018 | Supplemental Material
Book Section - Chapter Open

Towards Design Principles for Visual Analytics in Operations Contexts

Abstract

Operations engineering teams interact with complex data systems to make technical decisions that ensure the operational efficacy of their missions. To support these decision-making tasks, which may require elastic prioritization of goals dependent on changing conditions, custom analytics tools are often developed. We were asked to develop such a tool by a team at the NASA Jet Propulsion Laboratory, where rover telecom operators make decisions based on models predicting how much data rovers can transfer from the surface of Mars. Through research, design, implementation, and informal evaluation of our new tool, we developed principles to inform the design of visual analytics systems in operations contexts. We offer these principles as a step towards understanding the complex task of designing these systems. The principles we present are applicable to designers and developers tasked with building analytics systems in domains that face complex operations challenges such as scheduling, routing, and logistics.

Additional Information

© 2018 Copyright held by the owner/author(s). Publication rights licensed to ACM. Special thanks are due to Victoria Scarffe-Barrett and her colleagues on the MER Operations team for insight and feedback on various iterations of the Meridian prototype. We would also like to thank Fred Hohman and Beatrice Jin for their valuable discussions about this research. The development of Meridian was enabled by the JPL/Caltech/ArtCenter data visualization program; this support is gratefully acknowledged.

Attached Files

Supplemental Material - ft_gateway.cfm_id=3173712_type=mp4_path=_2F3180000_2F3173712_2Fsupp_2Fpn1924-file3.mp4_supp=1_dwn=1

Supplemental Material - ft_gateway.cfm_id=3173712_type=mp4_path=_2F3180000_2F3173712_2Fsupp_2Fpn1924-file5.mp4_supp=1_dwn=1

Files

Files (51.5 MB)
Name Size Download all
md5:4bd0da419942c1b40fbb419436014116
5.7 MB Download
md5:256b9a889ee0075e73eda6df8bb74f92
45.8 MB Download

Additional details

Created:
September 22, 2023
Modified:
October 23, 2023