The PIVOTS partnership has developed the Science & Theatre Magic Program, a service learning summer program of multidisciplinary, magic-themed science exploration. Faculty participants mentor teenagers, who in turn create and stage a day-long adventure that brings younger children from Philadelphia by train to an "American School of Magic." The creation of the magic school gives powerful expression to the youth voice inherent in the service learning paradigm: ownership of the design in the context of meaningful service sparks active learning. The result is a memorable, scienceinspired, interactive educational performance that connects the diverse populations of teens and the children served in an immersive urban and suburban setting. The program makes significant inroads in realizing the PIVOTS ultimate goals of engaging students in highly motivational multidisciplinary STEM programs and activities that promote positive images of STEM professionals and thus attract and retain interest in STEM careers. (www.csc.villanova.edu/~map/pivots/) Index Terms -Service-learning, Creative design experiences, Magical illusion, K-12 initiatives and partnerships, Theatre.

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The purpose of data warehouses is to enable business analysts to make better decisions. Over the years the technology has matured and data warehouses have become extremely successful. As a consequence, more and more data has been added to the data warehouses and their schemas have become increasingly complex. These systems still work great in order to generate pre-canned reports. However, with their current complexity, they tend to be a poor match for non tech-savvy business analysts who need answers to ad-hoc queries that were not anticipated.This paper describes the design, implementation, and experience of the SODA system (Search over DAta Warehouse). SODA bridges the gap between the business needs of analysts and the technical complexity of current data warehouses. SODA enables a Google-like search experience for data warehouses by taking keyword queries of business users and automatically generating executable SQL. The key idea is to use a graph pattern matching algorithm that uses the metadata model of the data warehouse. Our results with real data from a global player in the financial services industry show that SODA produces queries with high precision and recall, and makes it much easier for business users to interactively explore highly-complex data warehouses.