Abstract-When exploring noisy or visually complex data, such as seismic data from the oil and gas industry, it is often the case that algorithms cannot completely identify features of interest. Human intuition must complete the process. Given the nature of intuition, this can be a source of differing interpretations depending on the human expert; thus we do not have a single feature but multiple views of a feature. Managing multi-user and multi-version interpretations, combined with version tracking, is challenging as these interpretations are often stored as geometric objects separately from the raw data and possibly in different local machines. In this paper we combine the storage of the raw data with the storage of the interpretations produced by the visualization of features by multiple user sessions. We present case studies that illustrate our system's ability to reproduce users' amendments to the interpretations of others and the ability to retrace the history of amendments to a visual feature.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.