By Kristen Childs
Satellite observations of objects in space do not arrive as the colored images that so often appear in science books and magazines. Instead, these visually captivating representations of space originate as data transmitted in long lines of ones and zeros—binary code that scientists can interpret and model in various ways to represent the structure and appearance of space phenomena.
At DCSWA’s 2018 Professional Development Day, Kim Arcand, visualization lead for NASA’s Chandra X-ray Observatory, explained how NASA experts are using Chandra observation data to tell stories about the high-energy universe. Her talk touched on the entire process, from the moment X-ray photons travel away from a high-energy interstellar object, such as an exploded star, to when the emissions reach the Chandra X-ray Observatory, and finally the data processing and creation of a scientifically accurate visual representation at the Chandra X-ray Center.
Chandra observations provide one of the best repositories from which to build stories about high-energy spatial objects and events and their changes over time. The telescope has been in operation since 1999, allowing the Center to model nearly twenty years of data.
Software is employed to scale reflectance values, remove artifacts, mosaic scenes together that were measured at different times, and apply a color scale to provide further meaning to Chandra observations. Since Chandra only observes X-rays, a type of electromagnetic emission that exists outside of the visible light spectrum, a chromatic color scheme is typically applied. Red, green, and blue color bands denote areas ranging from low to high energy, respectively.
Today’s advanced technology enables the simulation of observational data beyond traditional true- and false-color images. To gain a new perspective on the data and to make the findings more accessible to people of different learning methods and physical abilities, the Chandra X-ray Center is now representing space phenomena by generating 3-D computer models, creating physical models with a 3-D printer, and simulating observations using virtual reality.
What began as a project to build a 3-D model of the supernova remnant Cassiopeia A with software borrowed from brain imaging led to the development of tactile and multidimensional learning objects to model Chandra data. Printed 3-D models are especially beneficial for the visually impaired, as they provide a three-dimensional, physical representation of astronomical observations for people with limited to no visibility. Virtual reality with sonic input provides another avenue to experience and learn about space observations.
As with any data representation, the intended audience is a main consideration when Arcand and her team decide how to represent Chandra observation. A physicist might see a red and blue image and interpret the red areas as cooler than the blue, as is the norm in scientific representation. The first questions that often come to mind concern the source of the data, the technology used to collect and model it, and the size of the object. Only then might a scientific expert take a step back and appreciate the image for its aesthetic.
Non-experts often address these concerns in reverse. Their first reactions to an image of astronomical data tend to start with an expression of awe at the visually captivating phenomenon, followed later with more technical questions. Data representation consequently is more effective when the imagery is built to complement the thought process of the audience, Arcand said. To non-experts, astronomical data often appears as equal parts art and science. Treating it as such, by including captions or providing a familiar object such as the sun as a scale reference, can make data presentations both relevant and understandable.
Kim Arcand joined the Chandra team one year before launch. Twenty years later, her knowledge of data and audience interaction, as well as her extensive experience in data visualization, help her transform raw observation data into meaningful representations of space objects and phenomena. Key priorities when developing data visualization, such as considering the audience, creating a frame of reference, and establishing a sense of relevancy, are important for the Chandra mission. The same principles apply to any scientist or research organization looking to not only analyze and interpret data, but to tell captivating and informative stories that seek to explain the world—and the universe—around us.
Sorry, comments are closed for this post.