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Saule Shomshekova

Publications and source records attributed to Saule Shomshekova.

3 recordsLinked to original sources

ArxSP: A Python-Based Modular Application for the Reduction of Digitized Archival Spectra

We present a methodology for the reduction of archival spectral data together with the description of a newly developed Python-based software package featuring an interactive graphical interface. The work is primarily aimed at processing spectra obtained with electron-optical converters (EOCs), which are characterized by geometric distortions induced by the magnetic field of the registration system. Such data are preserved, in particular, in the archive of the Fesenkov Astrophysical Institute (FAI), which contains about 10,000 photographic plates. These distortions, along with the need to transform the optical density of the photographic material into relative intensity, cannot be corrected by standard astronomical packages such as IRAF and therefore require a dedicated approach. Historically, reductions at FAI were performed using a program written in the Microsoft QuickC language for computing platforms of the 1990s, rendering it incompatible with modern operating systems. The new package is implemented with the PyQt5 framework, retaining the logic of the original code while extending its functionality. The implemented algorithms include image rotation and cropping, geometric distortion correction, construction of the characteristic curve linking optical density and intensity, and direct conversion of pixel values in object spectra. The developed software ensures reproducible reduction of archival spectra and provides a cross-platform environment with potential for further extensions.

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FAIR-Compliant Architecture for Heterogeneous Astronomical Data: KazVO Framework

This paper presents the architecture of the Kazakhstani National Virtual Observatory (KazVO) - an International Virtual Observatory Alliance (IVOA) compliant node that unifies the heterogeneous observational datasets of the Fesenkov Astrophysical Institute (FAI). The architectural foundation of the system is built upon a partitioned Data Lake, a German Astrophysical Virtual Observatory (GAVO) Data Center Helper Suite (DaCHS) publishing backend, and a PostgreSQL database that maps heterogeneous metadata to the unified IVOA ObsCore standard. We follow Open Science by introducing metadata-only model featuring based on a four-class data embargo mechanism. Machine-to-machine services deployed via IVOA protocols are listed in the global Registry of Registers, enabling analysis of Kazakhstani observational assets within external clients such as Tool for OPerations on Catalogues And Tables (TOPCAT), Aladin, and PyVO. As a result, KazVO framework provides a scalable platform driven by a developed end-to-end pipeline that bridges two fundamentally distinct data types - digitized historical glass-plate heritage (1950-1997) and live operational photometric and spectroscopic digital streams from telescopes at the Assy-Turgen and Tien-Shan Observatories - opening FAI's combined data datasets to the global scientific and time-domain astrophysics community.

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The Astronomical Hub: A Unified Ecosystem for Modern Astronomical Research

We present the conceptual framework of the Astronomical Hub (AstroHub), a unified platform combining various optical instruments at a single observatory. Its major approach lies in arranging conditions for research groups to install telescopes and equipment and participate in joint projects. AstroHub is planned to integrate Virtual Observatory (VO) tools, FAIR data principles, and a telescope network to create a powerful and attractive ecosystem for both robust near-Earth object (NEO) monitoring and diverse deep space research. We provide an overview of the AstroHub development directions in the case study of the Assy-Turgen Observatory.

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