Citation: Poudel, M.; Sarode, R.P.;
Watanobe, Y.; Mozgovoy, M.; Bhalla,
S. Processing Analytical Queries over
Polystore System for a Large
Astronomy Data Repository. Appl.
Sci. 2022, 12, 2663. https://doi.org/
10.3390/app12052663
Academic Editor: Sławomir
Nowaczyk
Received: 7 January 2022
Accepted: 1 March 2022
Published: 4 March 2022
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Article
Processing Analytical Queries over Polystore System for a Large
Astronomy Data Repository
Manoj Poudel * , Rashmi P. Sarode * , Yutaka Watanobe, Maxim Mozgovoy and Subhash Bhalla
Graduate Department of Computer and Information Systems, The University of Aizu, Aizu-Wakamatsu,
Fukushima 965-8580, Japan; yutaka@u-aizu.ac.jp (Y.W.); mozgovoy@u-aizu.ac.jp (M.M.);
c21bhala@u-aizu.ac.jp (S.B.)
* Correspondence: d8212102@u-aizu.ac.jp (M.P.); rashmipsarode@gmail.com (R.P.S.)
Abstract:
There are extremely large heterogeneous databases in the astronomical data domain, which
keep increasing in size. The data types vary from images of astronomical objects to unstructured
texts, relations, and key-values. Many astronomical data repositories manage such kinds of data. The
Zwicky Transient Facility (ZTF) is one such data repository with a large amount of data with different
varieties. Handling different types of data in a single database may have performance and efficiency
issues. In this study, we propose a web-based query system built around the Polystore database
architecture, and attempt to provide a solution for the growing size of data in the astronomical domain.
The proposed system will unify querying over multiple datasets directly, thereby eliminating the effort
to translate complex queries and simplify the work for the users in the astronomical domain. In this
proposal, we study the models of data integration, analyze them, and incorporate them into a system
to manage linked open data provided by astronomical domain. The proposed system is scalable, and
its model can be used for various other systems to efficiently manage heterogeneous data.
Keywords: ZTF data; PTF data; Polystore; link data; data integration
1. Introduction
On the web, there is a plethora of data sources. There are Smart cities, IoT and
personal devices, human-curated datasets (e.g., Open Maps or Wikipedia), large-scale
collaborative data-driven research, satellite data, and open government initiatives, which
are all contributing to an enormous amount of data available for analysis. As a result of
this diversity, related data can be found in a wide range of database engines.
The term “open data” refers to data that can be accessed, used, and shared by anybody.
Open data can be used to help society, the economy, and the environment by governments,
businesses, and individuals [
1
]. There are only two restrictions to open data: that it must be
attributed and that it must be shared with others in a non-commercial manner. In order for
the data to be accessible, it must be offered in its entirety and at a fair cost, preferably via
the internet. Access to and modification of the data is also important. In order to allow for
reuse and redistribution, the data must be made available under license terms that allow
this, as well. Anyone can use, reuse, and redistribute; there should be no discrimination
against fields of endeavor or individuals or groups [2].
The phrase “Linked Data” refers to a collection of best practices for publishing and
connecting structured data on the Web. The data discovery technique is to access the data
from integration tasks, such as schema matching, query reformulation, and mapping, from
data lakes. It is about building the connections necessary for a person or machine to examine
the data network [
3
]. When linked data are accessible, related data can be discovered. As
with the hypertextual web, the data web is constructed using web documents. Unlike
the web of data, where links are anchors for relationships in hypertext pages written in
Hypertext Markup Language (HTML), data links are between arbitrary items represented
by Resource Description Framework (RDF). Uniform Resource Identifier (URIs) can be
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