Effective data visualization is a key part of the discovery process in the era of “big data”. It is the bridge between the quantitative content of the data and human intuition, and thus an essential component of the scientific path from data into knowledge and understanding. Visualization is also essential in the data mining process, directing the choice of the applicable algorithms, and in helping to identify and remove bad data from the analysis. However, a high complexity or a high dimensionality of modern data sets represents a critical obstacle. How do we visualize interesting structures and patterns that may exist in hyper-dimensional data spaces? A better understanding of how we can perceive and interact with multidimensional information poses some deep questions in the field of cognition technology and human-computer interaction. To this effect, we are exploring the use of immersive virtual reality platforms for scientific data visualization, both as software and inexpensive commodity hardware. These potentially powerful and innovative tools for multi-dimensional data visualization can also provide an easy and natural path to a collaborative data visualization and exploration, where scientists can interact with their data and their colleagues in the same visual space. Immersion provides benefits beyond the traditional “desktop” visualization tools: it leads to a demonstrably better perception of a datascape geometry, more intuitive data understanding, and a better retention of the perceived relationships in the data.

NASA's Telexploration Project seeks to make us better explorers by building immersive environments that feel like we are really there. The Mission Operations Innovation Office and its Operations Laboratory at the NASA Jet Propulsion Laboratory (JPL) founded the Telexploration Project, and is researching how immersive visualization and natural human-robot interaction can enable mission scientists, engineers, and the general public to interact with NASA spacecraft and alien environments in a more effective way. These efforts have been accelerated through partnerships with many different companies, especially in the video game industry. These demos will exhibit some of the progress made at NASA and its commercial partnerships by allowing attendees to experience Mars data acquired from NASA spacecraft in a head mounted display using several rendering and interaction techniques.

Cloud Computing has delivered unprecedented compute capacity to NASA missions at affordable rates. Missions like the Mars Exploration Rovers (MER) and Mars Science Lab (MSL) are enjoying the elasticity that enables them to leverage hundreds, if not thousands, or machines for short durations without making any hardware procurements. In this paper, we describe Polyphony, a resilient, scalable, and modular framework that efficiently leverages a large set of computing resources to perform parallel computations. Polyphony can employ resources on the cloud, excess capacity on local machines, as well as spare resources on the supercomputing center, and it enables these resources to work in concert to accomplish a common goal. Polyphony is resilient to node failures, even if they occur in the middle of a transaction. We will conclude with an evaluation of a production-ready application built on top of Polyphony to perform image-processing operations of images from around the solar system, including Mars, Saturn, and Titan.

The Science Activity Planner (SAP) is the primary science operations tool for the Mars Exploration Rover mission and NASA’s Software of the Year for 2004. SAP utilizes a variety of visualization and planning capabilities to enable the mission operations team to direct the activities of the Spirit and Opportunity rovers. This paper outlines some of the challenging requirements that drove the design of SAP and discusses lessons learned from the development and use of SAP in mission operations.

We present an account of the scientific visualization techniques that were used to support science planning for NASA's 2003 Mars Exploration Rover Mission. The great sophistication of the rover's Athena Science Payload required a wide variety of visualization modalities to make the large amounts of scientific data accessible and readily understood by the science planners under the tight time constraints of the tactical planning schedule. A number of techniques were also newly developed to support science operations, including on-the-fly mosaic stitching and rendering, image cube visualization, and data fusion. Many other well-established visualization techniques were applied to science operations also, such as anaglyph stereo, high performance 3D visualization, and optimized I/O and memory management techniques for the loading, processing, and visualization of very large data sets. We discuss each of these topics and demonstrate their application in the MER mission with examples.

The Science Activity Planner (SAP) is the science planning tool used for the Mars Exploration Rover (MER) mission. This paper begins with an overview of the software developed for MER and how it was used for science downlink analysis and activity planning. The overview of SAP is then followed by a report on a number of new development efforts that aim to improve on the capabilities of SAP for future missions. The selected areas discussed herein include the application of geographical information systems in tactical downlink analysis, new strategies for distributed data access and planning support, a virtual field test capability to support “what if?” scenarios for new technologies and mission concepts, and the use of agile development methods to improve the development of Mars surface mission support software as a whole.

Group collaboration capabilities have been developed for Internet-based Mars rover mission operations. Internet-based operations enables scientists to participate in daily Mars rover mission operations from their home institutions. Group collaboration enables geographically separated users to collaboratively analyze downlinked data and plan new activities for the rover. The motivation for group collaboration in Mars rover mission operations and the technologies developed to provide group collaboration are discussed. The group collaboration capability was developed for use in rover mission operations in the 2003 NASA Mars Exploration Rover mission.

This paper discusses a proof-of-concept prototype for ground-based automatic generation of validated rover command sequences. This prototype is based on ASPEN (Automated Scheduling and Planning Environment). This Artificial Intelligence (AI) based planning and scheduling system will automatically generate a command sequence that will execute: within resource constraints and satisfy flight rules. An automated planning and scheduling system encodes rover design knowledge and uses the search and reasoning techniques to automatically generate low-level command sequences while respecting the rover operability constraints. This prototype planning system has been field-tested using the Rocky-7 rover at JPL, and will be field-tested on more complex rovers to prove its effectiveness before transferring the technology to flight operations for an upcoming NASA mission. The goal-driven commanding of planetary rovers greatly reduces the requirements for highly skilled rover engineering personnel. This in turn greatly reduces mission operations costs and permits a faster response to changes in rover states.

The Mars Polar Lander (MPL) mission was the first planetary mission to use Internet-based distributed ground operations where scientists and engineers collaborate in daily mission operations from multiple geographically distributed locations via the Internet. This paper describes the operations system, the Web interface for telescience (WITS), which was used by the MPL mission for Internet-based operations. WITS was used for generating command sequences for the lander's robotic arm and robotic arm camera, and as a secondary tool for sequence generation for the stereo camera on the lander. WITS was also used as a public outreach tool. Results are shown from the January 2000 field test in Death Valley, California.