Applied Sciences (Jun 2022)

A Survey of Big Data Archives in Time-Domain Astronomy

  • Manoj Poudel,
  • Rashmi P. Sarode,
  • Yutaka Watanobe,
  • Maxim Mozgovoy,
  • Subhash Bhalla

DOI
https://doi.org/10.3390/app12126202
Journal volume & issue
Vol. 12, no. 12
p. 6202

Abstract

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The rise of big data has resulted in the proliferation of numerous heterogeneous data stores. Even though multiple models are used for integrating these data, combining such huge amounts of data into a single model remains challenging. There is a need in the database management archives to manage such huge volumes of data without any particular structure which comes from unconnected and unrelated sources. These data are growing in size and thus demand special attention. The speed with which these data are growing as well as the varied data types involved and stored in scientific archives is posing further challenges. Astronomy is also increasingly becoming a science which is now based on a lot of data processing and involves assorted data. These data are now stored in domain-specific archives. Many astronomical studies are producing large-scale archives of data and these archives are then published in the form of data repositories. These mainly consist of images and text without any structure in addition to data with some structure such as relations with key values. When the archives are published as remote data repositories, it is challenging work to organize the data against their increased diversity and to meet the information demands of users. To address this problem, polystore systems present a new model of data integration and have been proposed to access unrelated data repositories using an uniform single query language. This article highlights the polystore system for integrating large-scale heterogeneous data in the astronomy domain.

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