This talk focuses on three frameworks developed by the KM3NeT collaboration: KM3Pipe, aanet and OrcaNet.
KM3Pipe is a Python-based pipeline framework which is used to modularise different kinds of processes and workflows like data analysis, detector monitoring and ML training in the KM3NeT neutrino telescope experiment. Although it contains many implementations of project specific data formats...
I will present the history, general design considerations and challenges related to the prototype data processing framework ctapipe. The purpose of creating ctapipe was to provide an API and standard algorithms for creating low-level (reconstruction level) data processing pipelines for Atmospheric Cherenkov Telescopes---specifically for CTA, but also supporting other existing instruments. ...
An overview of past and current efforts to establish high-level data analysis with open-source tools (i.e. Gammapy or ctools) for the H.E.S.S. experiment will be presented. A focus will be given to ongoing work about the validation of these tools on public H.E.S.S. data (see https://www.mpi-hd.mpg.de/hfm/HESS/pages/dl3-dr1), as well as to the exploration of a 3D likelihood analysis...
MAGIC is one of the current Imaging Atmospheric Cherenkov Telescope (IACT) located at the Roque of los Muchachos Observatory on La Palma, one of the Canary Islands. It started to operate in 2003 and is still currently running. Since 2009, MAGIC operates in a stereoscopic mode with two telescopes. A Major hardware upgrade was performed in 2012 for both camera. I will present the status on the...
As the multi-messenger era is now fully active, it is crucial that the community has a framework within which to analyze data from multiple messengers, wavelengths, and instruments in a statistically robust, common way. 3ML (https://threeml.readthedocs.io) provides an abstract, plugin-based data interface for instruments to combine analysis through each instrument's own unique likelihood. As a...
