To achieve these goals, this research will develop a framework for making visual analysis sessions not only reproducible but also reusable. This research and its related activities increase accessibility and enhance the data analysis infrastructure for research and education. The increasing use of visual analysis tools for decision making will make data analysis accessible to a broad variety of people, as visual analysis tools are generally easier to use than scripting languages and do not require extensive computational and statistical training. This, in turn will lead to better outcomes, achieved with less effort and cost. This project will develop methods to justify, communicate, and audit decisions made based on visual analysis. Visualization is an important tool for discovery, yet decisions made by humans based on visualizations of data are difficult to capture and to justify. This project is concerned with enabling reproducibility and justifiability of decisions in the data analysis process, specifically as it relates to visual data analysis.
Reproducibility and justifiability are widely recognized as critical aspects of data-driven decision making in fields as varied as scientific research, business, healthcare, or intelligence analysis. Visualization at SCI includes the academic subfields of Scientific Visualization, Information Visualization and Visual Analytics.Įnabling Reproducibility of Interactive Visual Data Analysis Therefore, much of our research is concerned with creating visualizations that are intuitive to interact with and also render at interactive rates. We strongly believe in the role of interactivity in visual data analysis. We also research the process of creating successful visualizations. Research involves novel algorithm and technique development to building tools and systems that assist in the comprehension of massive amounts of (scientific) data. Visualization research at SCI has focused on applications spanning computational fluid dynamics, medical imaging and analysis, biomedical data analysis, healthcare data analysis, weather data analysis, poetry, network and graph analysis, financial data analysis, etc. Visualization, sometimes referred to as visual data analysis, uses the graphical representation of data as a means of gaining understanding and insight into the data.
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