Adaptive Data Reduction Workflows for Astronomy -- The ESO Data Processing System (EDPS)

Abstract

Astronomical data reduction is usually done with processing pipelines that consist of a series of individual processing steps that can be executed stand-alone. These processing steps are then strung together into workflows and fed with data to address a particular processing goal. In this paper, we propose a data processing system that automatically derives processing workflows for different use cases from a single specification of a cascade of processing steps. The system works by using formalized descriptions of data processing pipelines that specify the input and output of each processing step. Inputs can be existing data or the output of a previous step. Rules to select the most appropriate input data are directly attached to the description. A version of the proposed system has been implemented as the ESO Data Processing System (EDPS) in the Python language. The specification of processing cascades and data organisation rules use a restrictive set of Python classes, attributes and functions. The EDPS implementation of the proposed system was used to demonstrate that it is possible to automatically derive from a single specification of a pipeline processing cascade the workflows that the European Southern Observatory uses for quality control, archive production, and specialized science reduction. The EDPS will be used to replace all data reduction systems using different workflow specifications that are currently used at the European Southern Observatory.