## 1 Introduction
### Motivating Example of Linked Open Data in ZTF Repository
A CCD quadrant is the fundamental image-unit for pipeline processing and the source of all scientific data output. ZTF's large data will serve as a reference for the Large Synoptic Survey Telescope's next project (LSST) [22]. LSSTwill conduct surveys of location, flux and shape measurements, light curve analysis, and calibrated images. The PTF and ZTF projects' progress, as well as specifications regarding the products, are listed in Table 1.  
All image data are available in the Flexible Image Transport System (FITS) format [23], which includes epochal (single-exposure) photos and photometric catalogs. The images were captured using 64 CCD (Charge-Coupled Device) cameras equipped with a variety of filters that affect the image quality [19]. The photometric catalogs provide information on images that comprise key-value pairs and header information. These key-value pairs can be converted to relations and stored in relational database management systems(RDBMS). Provided the data's size and the available resources, only a subset of the data is downloaded for indexing. Thus, the header files containing astronomical image information are downloaded. The header files are retrieved from the IRSA online service's Hierarchical File System (HFS) and replicated on the local server. Additionally, the catalogs include header files that include the metadata (HTML elements) necessary for establishing a connection to the IRSA web service and retrieving the images. PostgreSQL is used to store the key values and header information for the images obtained from IRSA/IPAC. The images are accessible via IRSA/cloud IPAC's service. Currently, the repository houses data for the years 2017-2021, comprising around 50 Terabytes. As a result, astronomy has developed into a data-intensive science that continues to grow in size. Secure and scalable mass storage systems are in high demand for aggregate data in efficient processing [24]. Thus, data schemas may be modified often, and new data products can be added frequently. The data types include images of astronomical objects, unstructured texts, relations, and key-value pairs. To manage these data effectively, it will be necessary to categorize the sources of the data using extremely efficient machine learning algorithms. Significant increase across several identified sources will require the development of efficient and well-designed databases. The study is primarily motivated by the goal of developing a scalable multidata storage architecture for querying heterogeneous data which are available in polysources. The enormous number and variety of data available in the astronomical realm present a significant management challenge. Currently available solutions in the astronomical area rely heavily on relational databases. Additionally, the majority of solutions require users to create sophisticated programs in order to gain significant insights. This project aims to propose a solution to astronomy's challenges with huge data and a dearth of appropriate query tools. The goals of this research are as follows:  
1. Create an effective multidatabase architecture for managing heterogeneous astronomical data; \begin{table}
\begin{tabular}{l l l l l} \hline \hline
**Project Name** & **Duration** & **Data Download** & **No. of FITS File** & **Product** \\ \hline PTF (Level 0, Level 1) & 2009–2012 & 0.1 TB per night & Around 3 million & Epochal images, photometric catalogs \\ \hline iPTF (Level 2) & 2013–2017 & 0.3 TB per night & Around 5 million & Deep reference, light curves \\ \hline ZTF (Data & 2017–2021 & 1.4 TB per night & Around 50 million & New reference, lightcurves, transient candidates, catalog \\ \hline LSST (Data & 2022–2024 & 3 TB per night & Around 500 & Calibrated images, measure of position, flux and shapes, and light curves \\ \hline \hline \end{tabular}
\end{table} 
Table 1: ZTF science data product. 2. Provide a query language that federates data, transforms it, and migrates it effectively inside the underlying data repositories;
3.