Astronomical source finding services for the CIRASA visual analytic platform
This addresses data processing bottlenecks for astronomers using next-generation facilities like the SKA, but it is incremental as it builds on existing tools.
The paper tackles the challenge of managing the data deluge in radio astronomy by integrating source extraction algorithms into the CIRASA visual analytic platform, aiming to improve cataloguing efficiency for large surveys.
Innovative developments in data processing, archiving, analysis, and visualization are nowadays unavoidable to deal with the data deluge expected in next-generation facilities for radio astronomy, such as the Square Kilometre Array (SKA) and its precursors. In this context, the integration of source extraction and analysis algorithms into data visualization tools could significantly improve and speed up the cataloguing process of large area surveys, boosting astronomer productivity and shortening publication time. To this aim, we are developing a visual analytic platform (CIRASA) for advanced source finding and classification, integrating state-of-the-art tools, such as the CAESAR source finder, the ViaLactea Visual Analytic (VLVA) and Knowledge Base (VLKB). In this work, we present the project objectives and the platform architecture, focusing on the implemented source finding services.