FAIR-Compliant Architecture for Heterogeneous Astronomical Data: KazVO Framework
Abstract
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.
Versions
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BibTeX
@misc{izmailova2026faircompliant,
title = {{FAIR-Compliant Architecture for Heterogeneous Astronomical Data: KazVO Framework}},
author = {Ildana Izmailova and Denis Yurin and Yerlan Aimuratov and Maxim Makukov and Aleksander Serebryanskiy and Saule Shomshekova and Vitaliy Kim and Chingis Omarov and Adel Umirbayeva and Laura Aktay and Dana Kuvatova and Anton Gluchshenko and Gulnara Suliyeva and Maxim Krugov and Nadezhda Vaidman and Daulet Anarbek and Inna Reva and Gauhar Aimanova and Rashit Valiullin and Raushan Kokumbayeva},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.39546},
eprint = {2609.39546},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.39546},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - FAIR-Compliant Architecture for Heterogeneous Astronomical Data: KazVO Framework
AU - Ildana Izmailova
AU - Denis Yurin
AU - Yerlan Aimuratov
AU - Maxim Makukov
AU - Aleksander Serebryanskiy
AU - Saule Shomshekova
AU - Vitaliy Kim
AU - Chingis Omarov
AU - Adel Umirbayeva
AU - Laura Aktay
AU - Dana Kuvatova
AU - Anton Gluchshenko
AU - Gulnara Suliyeva
AU - Maxim Krugov
AU - Nadezhda Vaidman
AU - Daulet Anarbek
AU - Inna Reva
AU - Gauhar Aimanova
AU - Rashit Valiullin
AU - Raushan Kokumbayeva
PY - 2026
DA - 2026/09/30
PB - arXiv
DO - 10.48550/arxiv.2609.39546
UR - https://arxiv.org/abs/2609.39546
AB - 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.
ER -