Scientists are faced with increasingly larger volumes of data to analyze. To analyze and validate various hypotheses, they need to create insightful visual representations of both observed data and simulated processes. Often, insight comes from comparing multiple visualizations. But data exploration through visualization requires scientists to assemble complex pipelines consisting of sequences of operations that transform the data into appropriate visual representations, and today, this process is far from interactive. It contains many error-prone and time-consuming tasks, greatly hindering the scientific discovery process.
The Visualization Management System (VMS) streamlines the creation, execution, and sharing of complex visualization pipelines. It extends traditional dataflow-based visualization systems in several significant directions: it enables interactive multiple-view visualizations by simplifying the creation and maintenance of visualization pipelines, and by optimizing their execution; it provides scalable mechanisms for generating and managing a large number of visualizations; it allows systematic maintenance of data product provenance (akin to a lab notebook) and enables the automatic re-execution of visualization pipelines. VMS gives scientists more control over the visualization process, simplifying many of their day-to-day activities such as allowing them: to resume their explorations where they left off; to apply identical operations to a new data set without having to redo a long sequence of operations; or to share their findings with colleagues.
VMS has the potential to substantially improve scientists' ability to carry out visualization and data exploration. By making VMS freely-available and by integrating it with the leading visualization systems, it can be widely used by the scientific community to support and facilitate scientific discoveries.
