An Approach for Automatically Generating R2RML-Based Direct Mapping from Relational Databases

作     者：Mohamed A.G. Hazber Ruixuan Li Guandong Xu Khaled M. Alalayah 

作者机构：School of Computer Science and TechnologyHuazhong University of Science and TechnologyWuhanChina Faculty of Engineering and ITUniversity of Technology SydneySydneyAustralia Computer ScienceIBB UniversityIbbYemen Computer ScienceNajran University-SharurahNajranSaudi Arabia 

出 版 物：《国际计算机前沿大会会议论文集》 (International Conference of Pioneering Computer Scientists, Engineers and Educators（ICPCSEE）)

年 卷 期：2016年第1期

页      面：41-44页

学科分类：0303[法学-社会学] 03[法学] 

基　　金：This work is supported by National Natural Science Foundation of China under grants 61572221  61173170  61300222  61370230  61433006 and U1401258  Innovation Fund of Huazhong University of Science and Technology under grants 2015TS069 and 2015TS071  Science and Technology Support Program of Hubei Province under grant 2014BCH270 and 2015AAA013  and Science and Technology Program of Guangdong Province under grant 2014B010111007 

主　　题：Relational Database to Resource Description Framework (RDB2RDF) Direct Mapping R2RML Relational database Resource Description Framework (RDF) 

摘      要：For integrating relational databases (RDBs) into semantic web applications, the W3C RDB2RDF Working Group recommended two approaches, Direct Mapping (DM) and R2RML. The DM provides a set of mapping rules according to RDB schema, while the R2RML allows users to manually define mappings according to existing target ontology. The major problem to use R2RML is the effort for creating R2RML mapping documents manually. This may lead to appearance of many mistakes in the R2RML documents and requires domain experts. In this paper, we propose and implement an approach to generate an R2RML mapping documents automatically from RDB schema. The R2RML mapping reflects the behavior of the DM specification and allows any R2RML parser to generate a set of RDF triples from relational *** input of generating approach is DBsInfo class that automatically generated from relational schema. An experimental prototype is developed and shows the effectiveness of our approach algorithms.