# A Survey of Big Data Archives in Time-Domain Astronomy
## 1 Introduction  
Due to the abundance of data sources, the amount of data available for analysis is increasing rapidly, and there has been a great deal of research into how to manage heterogeneous data. Big data refers to large or complex information that cannot be processed using traditional methods. For a long time, people have been storing and accessing huge amounts of data for analytics [1]. In today's world, big data, comprising both structured as well as unstructured data, is available. Databases and spreadsheets that have been used in the past include structured data that are often numerical. An unstructured data set is a collection of unrelated pieces of information that does not follow a predetermined structure. It is common practice to store and process large amounts of data using specialized computer databases and applications [2]. The Semantic Web, often known as the Web of Data, is based on the concept of Linked Data [3]. The Semantic Web's emphasis on Linked Data's best practices for creating meaningful links between resources will benefit humans and robots. It is a collection of design concepts for sharing machine-readable and cross-referenced data [4]. Linked Data is a collection of best practices for publishing and interconnecting structured data on the Internet. Uniform Resource Identifiers (URIs, a common means of identifying concepts or entities), Hypertext Transfer Protocol (HTTP, a protocol used to retrieve resources or descriptions of resources, which is fundamental and universal) and Resource Description Framework (RDF, a data model based on graphs to organize data describing things in the world by structuring and linking it) are some technologies that support Linked Data [5]. Linked Data is a way to identify entities or concepts in the world and retrieve resources or descriptions of resources [6]. Open-linked data are known as linked open data (LOD) [7]. The [PERSON] definition of linked open data compared to linked data is the most precise: \"Linked Open Data is Linked Data provided under an open license that does not hinder its free usage\" [6]. The current model that focuses on data integration is open data integration. This feature is coherent worldwide discovery, or data influenced by the need for data analysis. The latest integration techniques require extensive data analysis to pinpoint the data to be used for extracting information with respect to big data [8]. Stores with copious amounts of varied data sets containing diverse data, called data lakes, may contain data in raw format, or may be organized into rich data schemas. The challenge presented to scientists is to match the pace of growth of data repositories and archives [9]. Other problems arise when storing heterogeneous data in native data stores and creating a communication protocol in data stores to query for information retrieval. Celestial phenomena that arise outside our atmosphere are studied by astronomers in their quest to better understand the universe. Similar to other scientific disciplines, astronomy deals with data tsunamis that require new methods and techniques for conducting scientific research [10]. Advances in telescopes, detector technology, and exponential increases in processing power have led to an avalanche of data in astronomy and other data-heavy sciences such as physics, biology, and geology. This data avalanche is expected to continue for several years. An efficient federation of database technologies is required to properly handle this avalanche and process enormous amounts of data. Ultimately, data-mining tools for analysis are crucial for extracting knowledge from enormous data volumes. In Section 3, we discuss mining in astronomy in detail [11]. The goal of this research is to survey big data archives in time-domain astronomy and find a solution to efficiently manage large repositories of data. Modern astronomical studies are heavily focused on undertaking large sky surveys and archiving the results.