The Gemini Recipe System: a dynamic workflow for automated data reduction

Labrie, Kathleen

Gemini's next generation data reduction software suite aims to offer greater automation of the data reduction process without compromising the flexibility required by science programs using advanced or unusual observing strategies.

The Recipe System is central to our new data reduction software. Developed in Python, it facilitates near-real time processing for data quality assessment, and both on- and off-line science quality processing. The Recipe System can be run as a standalone application or as the data processing core of an automatic pipeline. Using a concept from ORAC-DR, a data reduction process is defined in a Recipe written in a science (as opposed to computer) oriented language, and consists of a sequence of data reduction steps called Primitives. The Primitives are written in Python and can be launched from the PyRAF user interface by users wishing for more hands-on optimization of the data reduction process. The fact that the same processing Primitives can be run within both the pipeline context and interactively in a PyRAF session is an important strength of the Recipe System.

The Recipe System offers dynamic flow control allowing for decisions regarding processing and calibration to be made automatically, based on the pixel and the metadata properties of the dataset at the stage in processing where the decision is being made, and the context in which the processing is being carried out.

Processing history and provenance recording are provided by the AstroData middleware, which also offers header abstraction and data type recognition to facilitate the development of instrument-agnostic processing routines. All observatory or instrument specific definitions are isolated from the core of the AstroData system and distributed in external configuration packages that define a lexicon including classifications, uniform metadata elements, and transformations.

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