ONLINE VISUALIZATION AND ANALYSIS OF LARGE ROCK COLLECTIONS WITH SUAVE
SuAVE has been applied to explore surveys in several fields, from sociology and political science to environmental sustainability analysis, biodiversity and landscape ecology studies, art history and digital humanities, and archaeology. It presents a novel visual metaphor for joint analysis of digital image collections and image metadata, through faceted search, efficient subsetting, and Google maps-like navigation over an image gallery. In addition, SuAVE supports several types of data analysis (including interface with R statistical package) and allows exploration of distributions and outliers. In addition, the SuAVE system now includes the ability for users to publish online surveys and collections, annotate patterns they discover via visual and statistical analysis, and share these annotations. We report initial results of SuAVE development, its applications in research and teaching, and its use for online sharing and analysis of several rock collections. In particular, we focus on technical challenges of scalable publication and visualization of large image collections, and on cross-collection integration and analysis.