Scientific Mashups: Runtime-Configurable Data Product Ensembles

The concept of a mashup is gaining popularity as a rapid-development, reuse-oriented programming model to replace monolithic, bottom-up application development - a programming style well-suited to scientific data management applications. A variety of mashup development frameworks exist, but none fully address the needs of the scientific community. Specifically, scientists may be proficient programmers, but they use different tools than are usually supported in mashup frameworks (e.g., arrays and MATLAB rather than XML and Javascript). Further, typical scientific mashups may extract tens of thousands of records from terabyte-scale datasets. At this scale, visualization techniques must be employed to quickly convey the gross features of the data - paging through 10 records at a time is not sufficient. Finally, scientific mashups must accommodate users across a wide spectrum of skills and domain knowledge - the same mashup must be reconfigurable for use by specialists, researchers, policy makers, or K12 students. In this poster presentation, we articulate these requirements, describe an initial prototype scientific mashup system, provide visual examples of scientific mashups, and outline ongoing research directions.