{"title":"Hugegraph中RDF到属性图的转换","authors":"E. Haihong, Penghao Han, Meina Song","doi":"10.1145/3410352.3410833","DOIUrl":null,"url":null,"abstract":"The data form in the graph data is divided into RDF and property graph. RDF appeared earlier, but it is generally larger and the data is more redundant. In the property graph, a graph is defined by properties, nodes and edges. It is easier to set property to the edges, which is more helpful for the description of the graph, so it is of great research significance to transform RDF graph to property graph. However, because the structure of RDF and property graph are naturally different, transforming RDF to property graph needs to solve the distinction of nodes and properties while ensuring the uniqueness of the nodes, supporting multiple labels and empty labels in a single-label graph database and other difficulties. In this paper, through analyzing a variety of serialized data, we proposed a specific mapping mechanism to solve the first issue. Through the method of storing the label information of the node with additional fields, we have successfully solved the second issue. Finally, through experimental verification of a specific dataset, we found that the converted data volume was reduced by about 10% to 20%, and it can successfully complete the query requirements in different scenarios.","PeriodicalId":178037,"journal":{"name":"Proceedings of the 6th International Conference on Engineering & MIS 2020","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Transforming RDF to Property Graph in Hugegraph\",\"authors\":\"E. Haihong, Penghao Han, Meina Song\",\"doi\":\"10.1145/3410352.3410833\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The data form in the graph data is divided into RDF and property graph. RDF appeared earlier, but it is generally larger and the data is more redundant. In the property graph, a graph is defined by properties, nodes and edges. It is easier to set property to the edges, which is more helpful for the description of the graph, so it is of great research significance to transform RDF graph to property graph. However, because the structure of RDF and property graph are naturally different, transforming RDF to property graph needs to solve the distinction of nodes and properties while ensuring the uniqueness of the nodes, supporting multiple labels and empty labels in a single-label graph database and other difficulties. In this paper, through analyzing a variety of serialized data, we proposed a specific mapping mechanism to solve the first issue. Through the method of storing the label information of the node with additional fields, we have successfully solved the second issue. Finally, through experimental verification of a specific dataset, we found that the converted data volume was reduced by about 10% to 20%, and it can successfully complete the query requirements in different scenarios.\",\"PeriodicalId\":178037,\"journal\":{\"name\":\"Proceedings of the 6th International Conference on Engineering & MIS 2020\",\"volume\":\"10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-09-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 6th International Conference on Engineering & MIS 2020\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3410352.3410833\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 6th International Conference on Engineering & MIS 2020","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3410352.3410833","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The data form in the graph data is divided into RDF and property graph. RDF appeared earlier, but it is generally larger and the data is more redundant. In the property graph, a graph is defined by properties, nodes and edges. It is easier to set property to the edges, which is more helpful for the description of the graph, so it is of great research significance to transform RDF graph to property graph. However, because the structure of RDF and property graph are naturally different, transforming RDF to property graph needs to solve the distinction of nodes and properties while ensuring the uniqueness of the nodes, supporting multiple labels and empty labels in a single-label graph database and other difficulties. In this paper, through analyzing a variety of serialized data, we proposed a specific mapping mechanism to solve the first issue. Through the method of storing the label information of the node with additional fields, we have successfully solved the second issue. Finally, through experimental verification of a specific dataset, we found that the converted data volume was reduced by about 10% to 20%, and it can successfully complete the query requirements in different scenarios.