## 2 Background and Related Work  
### Overview of Linked Open Data  
Spurred by efforts such as the LOD project [22], large amounts of semantic data are published in the RDF format in several diverse fields such as publishing, life sciences, social networking, internet of things (IOT), and healthcare. The LOD cloud now covers 1269 datasets from diverse domains. Especially, the emergence of LOD has been making an excellent revolution in the healthcare sector. For example, corona virus disease 19 (COVID-19) is an infectious disease caused by a newly discovered coronavirus. In the midst of a global pandemic, Big Data such as LOD are showing an outstanding capability to analyze complex interactions among groups of people and locations. Through the work such as sharing and analyzing available LOD in the world, a cure for COVID-19 will be discovered. Efficient use of the large-scale LOD could find to a way to divine how the virus is spreading and how the number of infections can be reduced. The processing of such Big RDF Data requires a scalable data management system that can efficiently store, index, and query RDF data. RDF is a graph-based data model for the LOD cloud, and SPARQL is a standard query language for this data model. Assume **U**, **B**, and **L** are a set of all URIs, blank nodes, and literals, respectively. An RDF triple is a tuple \(t=(s,\,p,\,o)\in(\textbf{U}\cup\textbf{B})\times\textbf{U}\times(\textbf{U} \cup\textbf{B}\cup\textbf{L})\), where \(s,\,p,\,and\,o\) are the subject, predicate, and object, respectively. For instance, the triple (<[[http://dbpedia.org/person/[PERSON]](http://dbpedia.org/person/[PERSON])]([http://dbpedia.org/person/[PERSON]](http://dbpedia.org/person/[PERSON]))>, <[[http://xmlns.com/foaf/0.1/knows](http://xmlns.com/foaf/0.1/knows)]([http://xmlns.com/foaf/0.1/knows](http://xmlns.com/foaf/0.1/knows))>, <[[http://university.edu/students/[PERSON]](http://university.edu/students/[PERSON])]([http://university.edu/students/[PERSON]](http://university.edu/students/[PERSON]))>, accessed on 17 January 2021) indicates \"[PERSON] knows [PERSON]\" SPARQL is a graph-matching query language, and a SPARQL query is typically a combination of graph patterns. A basic graph pattern is a set of triple patterns, where a triple pattern is an RDF triple that can contain query variables (prefixed with '?') at the subject, predicate, and object positions. The main operation of SPARQL is matching these basic graph patterns. ```
Refer1:for://xmlns.com/foaf/0.1/ (accessed on 17 January 2021)  user. [[http://dbpedia.org/person/](http://dbpedia.org/person/)]([http://dbpedia.org/person/](http://dbpedia.org/person/)) (accessed on 17 January 2021)
```  
**Example 1:**_The following SPARQL query asks for the projects in which [PERSON]'s friends participated. This query comprises two triple patterns joined by variable?f:_Because SPARQL statements can be represented as graphs, we can transform SPARQL into a query graph to perform query processing. Based on the query graph structure, SPARQL queries can be divided into five different join types [23]--star, chain, directed cycle, complex, and tree--as shown in Figure 1. Our experiments include all join query types based on the real benchmark dataset. * Star queries are a set of triples formed using the same subject or object variable (subject = subject or object = object). Usually, we consider only subject-subject joins (i.e., all triples have the same subject). * Chain and directed cycle queries are triple patterns in which the subject and object variables are the same (subject = object) (i.e., the object of the triple is the subject of the next triple). * Complex queries are a combination of star and chain queries. * Tree queries contain subject-subject and subject-object joins and some more complex queries. Critical problems in the LOD cloud are the massive number of LOD datasets and potentially very large numbers of joins required to answer the queries.