Data Movement Model for the Vera C. Rubin Observatory

TL;DR

This paper describes the data movement architecture and tools used for managing the transfer and processing of astronomical images from the Vera C. Rubin Observatory across multiple international facilities, ensuring efficient data handling for scientific analysis.

Contribution

It introduces an integrated data movement model combining Rucio and Rubin's Data Butler to streamline data transfer and management across global processing centers.

Findings

Effective data transfer protocols established across continents.

Successful integration of Rucio with Rubin's Data Butler.

Facilitated timely data processing and releases.

Abstract

The sky images captured nightly by the camera on the Vera C. Rubin Observatory's telescope will be processed across facilities on three continents. Data acquisition will occur at the observatory's location on Cerro Pach\'{o}n in the Andes mountains of Chile. A first copy of the raw image data set is stored at the summit and immediately transmitted via dedicated network links to the archive center within the US Data Facility at SLAC National Accelerator Laboratory in California, USA and from there to two European facilities for processing and archiving purposes. Data products resulting from periodic processing campaigns of the entire set of images collected since the beginning of the survey are made available to the scientific community in the form of data releases. In this paper we present an overall view of how we leverage the tools selected for managing the movement of data among the Rubin processing and serving facilities, including Rucio and FTS. We also present the tools we developed to integrate Rucio's data model and Rubin's Data Butler, the software abstraction layer that mediates all access to storage by pipeline tasks that implement science algorithms.