Fast and Reproducible LOFAR Workflows with AGLOW

TL;DR

The paper introduces AGLOW, a workflow system that streamlines LOFAR data processing on distributed computing platforms, significantly reducing setup time and enabling efficient scientific analysis of large radio telescope datasets.

Contribution

It presents AGLOW, a novel workflow orchestration system that simplifies and accelerates LOFAR data processing on distributed clusters, with demonstrated case studies.

Findings

Workflow setup time reduced from months to days

Successful processing of LOFAR Survey data with AGLOW

Future plans for automated multi-product data generation

Abstract

The LOFAR radio telescope creates Petabytes of data per year. This data is important for many scientific projects. The data needs to be efficiently processed within the timespan of these projects in order to maximize the scientific impact. We present a workflow orchestration system that integrates LOFAR processing with a distributed computing platform. The system is named Automated Grid-enabled LOFAR Workflows (AGLOW). AGLOW makes it fast and easy to develop, test and deploy complex LOFAR workflows, and to accelerate them on a distributed cluster architecture. AGLOW provides a significant reduction in time for setting up complex workflows: typically, from months to days. We lay out two case studies that process the data from the LOFAR Surveys Key Science Project. We have implemented these into the AGLOW environment. We also describe the capabilities of AGLOW, paving the way for use by other LOFAR science cases. In the future, AGLOW will automatically produce multiple science products from a single dataset, serving several of the LOFAR Key Science Projects.