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In this article, we present Gammapy, an open-source Python package for the analysis of astronomical $\gamma$-ray data, and illustrate the functionalities of its first long-term-support release, version 1.0. Built on the modern Python scientific ecosystem, Gammapy provides a uniform platform for reducing and modeling data from different $\gamma$-ray instruments for many analysis scenarios. Gammapy complies with several well-established data conventions in high-energy astrophysics, providing serialized data products that are interoperable with other software packages. Starting from event lists and instrument response functions, Gammapy provides functionalities to reduce these data by binning them in energy and sky coordinates. Several techniques for background estimation are implemented in the package to handle the residual hadronic background affecting $\gamma$-ray instruments. After the data are binned, the flux and morphology of one or more $\gamma$-ray sources can be estimated using Poisson maximum likelihood fitting and assuming a variety of spectral, temporal, and spatial models. Estimation of flux points, likelihood profiles, and light curves is also supported. After describing the structure of the package, we show, using publicly available $\gamma$-ray data, the capabilities of Gammapy in multiple traditional and novel $\gamma$-ray analysis scenarios, such as spectral and spectro-morphological modeling and estimations of a spectral energy distribution and a light curve. Its flexibility and power are displayed in a final multi-instrument example, where datasets from different instruments, at different stages of data reduction, are simultaneously fitted with an astrophysical flux model., Comment: 26 pages, 16 figures

We developed a system to run quick analyses of Cherenkov data in compliance with the FAIR Guiding Principles for scientific data management (FAIR: Findable, Accessible, Interoperable and Reusable), through the use of interoperability standards and technologies, particularly those provided by the International Virtual Observatory Alliance (IVOA) to build the Virtual Observatory (VO). We therefore provide a controlled and stable environment on a computing cluster, in order to execute and re-execute well defined jobs. User-specific input parameters can be specified to configure the execution of an analysis job. Provenance information is automatically captured by the system and accessible to the user. To avoid long transfers, the data can be placed close to the computing nodes. This system is primarily used to analyse Cherenkov astronomy data, though it may be used for other purposes., Comment: ADASS XXXII, Oct 2022, Victoria, Canada

We present here a provenance management system adapted to astronomical projects needs. We collected use cases from various astronomy projects and defined a data model in the ecosystem developed by the IVOA (International Virtual Observatory Alliance). From those use cases, we observed that some projects already have data collections generated and archived, from which the provenance has to be extracted (provenance "on top"), and some projects are building complex pipelines that automatically capture provenance information during the data processing (capture "inside"). Different tools and prototypes have been developed and tested to capture, store, access and visualize the provenance information, which participate to the shaping of a full provenance management system able to handle detailed provenance information.

The International Virtual Observatory Alliance (IVOA) has developed and built, in the last two decades, an ecosystem of distributed resources, interoperable and based upon open shared technological standards. In doing so the IVOA has anticipated, putting into practice for the astrophysical domain, the ideas of FAIR-ness of data and service resources and the Open-ness of sharing scientific results, leveraging on the underlying open standards required to fill the above. In Europe, efforts in supporting and developing the ecosystem proposed by the IVOA specifications has been provided by a continuous set of EU funded projects up to current H2020 ESCAPE ESFRI cluster. In the meantime, in the last years, Europe has realised the importance of promoting the Open Science approach for the research communities and started the European Open Science Cloud (EOSC) project to create a distributed environment for research data, services and communities. In this framework the European VO community, had to face the move from the interoperability scenario in the astrophysics domain into a larger audience perspective that includes a cross-domain FAIR approach. Within the ESCAPE project the CEVO Work Package (Connecting ESFRI to EOSC through the VO) has one task to deal with this integration challenge: a challenge where an existing, mature, distributed e-infrastructure has to be matched to a forming, more general architecture. CEVO started its works in the first months of 2019 and has already worked on the integration of the VO Registry into the EOSC e-infrastructure. This contribution reports on the first year and a half of integration activities, that involve applications, services and resources being aware of the VO scenario and compatible with the EOSC architecture., Comment: 14 pages, 9 figures Proceedings of SPIE 2020 Astronomical Telescopes + Instrumentation Conference 11449 Observatory Operations: Strategies, Processes, and Systems VIII

The European Open Science Cloud (EOSC) is in its early stages, but already some aspects of the EOSC vision are starting to become reality, for example the EOSC portal and the development of metadata catalogues. In the astrophysical domain already exists an open approach to science data: the Virtual Observatory view put in place by the International Virtual Observatory Alliance (IVOA) architecture of standards. The ESCAPE (European Science Cluster of Astronomy & Particle physics ESFRI research infrastructures) project has, among its tasks, to demonstrate that the VO architecture can be integrated within the EOSC building one and to provide guidelines to ESFRI partners (European Strategy Forum on Research Infrastructures) in doing this. This contribution reports on the progress of this integration after the first months of work inside ESCAPE., Comment: 4 pages, 2 figures, ADASS XXIX proceedings

We developed several pieces of software to enable the tracking of provenance information for the large-scale complex astronomical observatory CTA, the Cherenkov Telescope Array. Such major facilities produce data that will be publicly released to a large community of scientists. There are thus strong requirements to ensure data quality, reliability and trustworthiness. Among those requirements, traceability and reproducibility of the data products have to be included in the development of large projects. Those requirements can be answered by structuring and storing the provenance information for each data product. We followed the Provenance data model, currently discussed at the IVOA, and implemented solutions to collect provenance information during the CTA data processing and the execution of jobs on a work cluster., Comment: To appear in the ADASS XXVII Proceedings

Since its inception in the early 2000, the Virtual Observatory (VO), developed as a collaboration of many national and international projects, has become a major factor in the discovery and dissemination of astronomical information worldwide. The IVOA has been coordinating all these efforts worldwide to ensure a common VO framework that enables transparent access to and interoperability of astronomy resources (data and software) around the world. The VO is not a magic solution to all astronomy data management challenges but it does bring useful solutions in many areas borne out by the fact that VO interfaces are broadly found in astronomy major data centres and projects worldwide. Astronomy data centres have been building VO services on top of their existing data services to increase interoperability with other VO-compliant data resources to take advantage of the continuous and increasing development of VO applications. VO applications have made multi-instrument and multi-wavelength science, a difficult and fruitful part of astronomy, somewhat easier. More recently, several major new astronomy projects have been directly adopting VO standards to build their data management infrastructure, giving birth to VO built-in archives. Embracing the VO framework from the beginning brings the double gain of not needing to reinvent the wheel and ensuring from the start interoperability with other astronomy VO resources. Some of the IVOA standards are also starting to be used by neighbour disciplines like planetary sciences. There is still quite a lot to be done on the VO, in particular tackling the upcoming big data challenge and how to find interoperable solutions to the new data analysis paradigm of bringing and running the software close to the data., Comment: 4 pages, no figures, ADASS 2015 conference proceedings

Gammapy is a Python package for high-level gamma-ray data analysis built on Numpy, Scipy and Astropy. It enables us to analyze gamma-ray data and to create sky images, spectra and lightcurves, from event lists and instrument response information, and to determine the position, morphology and spectra of gamma-ray sources. So far Gammapy has mostly been used to analyze data from H.E.S.S. and Fermi-LAT, and is now being used for the simulation and analysis of observations from the Cherenkov Telescope Array (CTA). We have proposed Gammapy as a prototype for the CTA science tools. This contribution gives an overview of the Gammapy package and project and shows an analysis application example with simulated CTA data., Comment: Proc. 35th ICRC, Busan, South Korea, PoS(ICRC2017)766

The landscape of ground-based gamma-ray astronomy is drastically changing with the perspective of the Cherenkov Telescope Array (CTA) composed of more than 100 Cherenkov telescopes. For the first time in this energy domain, CTA will be operated as an observatory open to the astronomy community. In this context, a structured high level data model is being developed to describe a CTA observation. The data model includes different classes of metadata on the project definition, the configuration of the instrument, the ambient conditions, the data acquisition and the data processing. This last part relies on the Provenance Data Model developed within the International Virtual Observatory Alliance (IVOA), for which CTA is one of the main use cases. The CTA data model should also be compatible with the Virtual Observatory (VO) for data diffusion. We have thus developed a web-based data diffusion prototype to test this requirement and ensure the compliance., Comment: To appear in the ADASS XXVI Proceedings

In gamma-ray astronomy, a variety of data formats and proprietary software have been traditionally used, often developed for one specific mission or experiment. Especially for ground-based imaging atmospheric Cherenkov telescopes (IACTs), data and software are mostly private to the collaborations operating the telescopes. However, there is a general movement in science towards the use of open data and software. In addition, the next-generation IACT instrument, the Cherenkov Telescope Array (CTA), will be operated as an open observatory. We have created a Github organisation at https://github.com/open-gamma-ray-astro where we are developing high-level data format specifications. A public mailing list was set up at https://lists.nasa.gov/mailman/listinfo/open-gamma-ray-astro and a first face-to-face meeting on the IACT high-level data model and formats took place in April 2016 in Meudon (France). This open multi-mission effort will help to accelerate the development of open data formats and open-source software for gamma-ray astronomy, leading to synergies in the development of analysis codes and eventually better scientific results (reproducible, multi-mission). This write-up presents this effort for the first time, explaining the motivation and context, the available resources and process we use, as well as the status and planned next steps for the data format specifications. We hope that it will stimulate feedback and future contributions from the gamma-ray astronomy community., Comment: 6 pages, 4 figures, Gamma 2016 conference poster contribution

We present the last developments on the IVOA Provenance data model, mainly based on the W3C PROV concept. In the context of the Cherenkov astronomy, the data processing stages imply both assumptions and comparison to dedicated simulations. As a consequence, Provenance information is crucial to the end user in order to interpret the high level data products. The Cherenkov Telescope Array (CTA), currently in preparation, is thus a perfect test case for the development of an IVOA standard on Provenance information. We describe general use-cases for the computational Provenance in the CTA production pipeline and explore the proposed W3C notations like PROV-N formats, as well as Provenance access solutions., Comment: 4 pages, 3 figures, to appear in ADASS XXV proceedings, edited by N. P. F. Lorente, & K. Shortridge (San Francisco: ASP), ASP Conf. Ser

The Cherenkov Telescope Array (CTA) observatory will be one of the largest ground-based very high-energy gamma-ray observatories. The On-Site Analysis will be the first CTA scientific analysis of data acquired from the array of telescopes, in both northern and southern sites. The On-Site Analysis will have two pipelines: the Level-A pipeline (also known as Real-Time Analysis, RTA) and the level-B one. The RTA performs data quality monitoring and must be able to issue automated alerts on variable and transient astrophysical sources within 30 seconds from the last acquired Cherenkov event that contributes to the alert, with a sensitivity not worse than the one achieved by the final pipeline by more than a factor of 3. The Level-B Analysis has a better sensitivity (not be worse than the final one by a factor of 2) and the results should be available within 10 hours from the acquisition of the data: for this reason this analysis could be performed at the end of an observation or next morning. The latency (in particular for the RTA) and the sensitivity requirements are challenging because of the large data rate, a few GByte/s. The remote connection to the CTA candidate site with a rather limited network bandwidth makes the issue of the exported data size extremely critical and prevents any kind of processing in real-time of the data outside the site of the telescopes. For these reasons the analysis will be performed on-site with infrastructures co-located with the telescopes, with limited electrical power availability and with a reduced possibility of human intervention. This means, for example, that the on-site hardware infrastructure should have low-power consumption. A substantial effort towards the optimization of high-throughput computing service is envisioned to provide hardware and software solutions with high-throughput, low-power consumption at a low-cost., Comment: In Proceedings of the 34th International Cosmic Ray Conference (ICRC2015), The Hague, The Netherlands. All CTA contributions at arXiv:1508.05894

The Cherenkov Telescope Array (CTA), a ground-based facility for very-high-energy (VHE) gamma-ray astronomy, will operate as an open observatory, serving a wide scientific community to explore and to study the non-thermal universe. Open community access is a novelty in this domain, putting a challenge on the implementation of services that make VHE gamma-ray astronomy as accessible as any other waveband. We present here the design of the CTA Observer Access system that comprises support of scientific users, dissemination of data and software, tools for scientific analysis, and the system to submit observing proposals. We outline the scientific user workflows and provide the status of the current developments., Comment: In Proceedings of the 34th International Cosmic Ray Conference (ICRC2015), The Hague, The Netherlands. All CTA contributions at arXiv:1508.05894