VISUALIZATION: A Metadata-Driven Visualization Interface Technology for Scientific Data Exploration

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This project lays out our plan for research and development aimed atdramatically improving the processand outcome of scientific data analysis and visualization. The improvement will be achieved by coupling an expressive and extensible metadata management framework with novel visualization interfaces that facilitateeffective reuse, sharing, and cross-exploration of visualizationinformation and thus will make a profoundimpact on a broad range of scientific applications. The process of scientific visualization is inherently iterative. A good visualization comes from experimenting with visualization and rendering parameters to bring out the most relevant information in the data.This raises a question. Considering the computer and human time we routinely invest for exploratory andproduction visualization, are there methodologies and mechanisms to enhance not only the productivity ofscientists but also their understanding of the visualization process anddata used?Recent advances in the field of data visualization have been made mainly in rendering and displaytechnologies (such as realtime volume rendering and immersive environments), but little in coherently managing, representing, and sharing information about the visualization processand results (images and insights).Naturally, the various information about data exploration should be shared and reused to leveragethe knowledge and experience scientists gain from visualizing scientific data. A visual representation of thedata exploration process along with expressive models for recording and querying task specific informationhelp scientists keep track of their visualization experience and findings, use it to generate new visualizations, and share it with others.While previous research has addressed some related issues, a more comprehensive study remains to bedone. Thus, we propose two complementary avenues of research: (1) new user interfaces for data visualization tasks, and (2) expressive metadata models supporting the recording andquerying of information related to data exploration tasks. In addition, a set of user studies will beconducted on a Web-based visualization testbed realizing (1) and (2) in order to refine the proposedmethodologies and designs.Traditional user interfaces cannot support the increasingly complex process of scientific data exploration.A fundamental change in the conventional designs and functionality must be made to offer moreintuitive interaction, guidance, and enhanced perception. We will begin our study with enriching the graphbased and spreadsheet-like interfaces we have developed, and also investigate alternative designs. An expressive and extensible metadata model representing the data exploration process and its embedded data visualization process is needed. Such a model along with an appropriate user interface makes it possible to manage diverse information about the input and results of the visualization process, analyze parameter coverage and usage, identify unexplored visualization spaces, and incorporate findings on the process and results in form of visualization metadata. The model is independent of the actual visual interface used and is open in that its realization in form of a metadata repository can be loosely coupled with a variety of different visualization tools. A set of interfaces and protocols to the repository will be designed to manage, query, and analyze visualization metadata gathered from and utilized by different visualization tools.Our goal is ambitious and can only be accomplished by working closely with application scientists.They will help us understand application-dependent and independent visualization requirements, processes,and information. In return, we will offer them a new and greatly improved way to understand their scientificdata, which will help them lead to new discoveries quicker, likely with reduced cost.