Evaluation Of Data Visualization Software For Large Astronomical Data Sets

227th Meeting of the American Astronomical Society (AAS Meeting 227)

This study investigates the efficacy of a 3D visualization application used to classify various types of stars using data derived from large synoptic sky surveys. Evaluation methodology included a cognitive walkthrough that prompted participants to identify a specific star type (Supernovae, RR Lyrae or Eclipsing Binary) and retrieve variable information (MAD, magratio, amplitude, frequency) from the star. This study also implemented a heuristic evaluation that applied usability standards such as the Shneiderman Visual Information Seeking Mantra to the initial iteration of the application. Findings from the evaluation indicated that improvements could be made to the application by developing effective spatial organization and implementing data reduction techniques such as linking, brushing, and small multiples.