UW Interactive Data Lab
IDL logo

Towards Design Principles for Visual Analytics in Operations Contexts

Matt Conlen, Sara Stalla, Chelly Jin, Maggie Hendrie, Hillary Mushkin, Santiago Lombeyda, Scott Davidoff. ACM Human Factors in Computing Systems (CHI), 2018
Figure for Towards Design Principles for Visual Analytics in Operations Contexts
The Meridian system was designed for operations engineers at the NASA Jet Propulsion Laboratory. Engineers using the system are tasked with selecting a heading at which to park the rover and an overpassing satellite to connect to in order to maximize the amount of data transferred back to Earth. 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.
Materials
PDF
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.
BibTeX
@inproceedings{2018-meridian,
  title = {Towards Design Principles for Visual Analytics in Operations Contexts},
  author = {Conlen, Matt AND Stalla, Sara AND Jin, Chelly AND Hendrie, Maggie AND Mushkin, Hillary AND Lombeyda, Santiago AND Davidoff, Scott},
  booktitle = {ACM Human Factors in Computing Systems (CHI)},
  year = {2018},
  url = {https://uwdata.github.io/papers/meridian},
  doi = {10.1145/3173574.3173712}
}