Berkeley Lab Scientific Computing Seminar

I will discuss my attempts to address the challenges of ad hoc data with my work on the PADS project. I will present an introduction to PADS/ML, a declarative data description language that permits analysts to describe the physical layout of their data and its semantic properties. From a description, the PADS compiler can automatically generate a collection of useful data-processing tools for the data source described, including parsing routines, statistical profiling tools, and translators to standard formats like XML. I will discuss the formal semantics of the PADS language and two of its essential properties. Finally, I will describe support for querying ad hoc data with the PADS tool PADX. I will discuss PADX from the users perspective and review the main challenges encountered in implementing PADX and their solutions.