Linked Data Platform D2R +

Qingling Chang, Shiting Xu, Yuanchun Zhou, Jing Shao, Jianhui Li, Baoping Yan

Abstract: The concept of linked data has developed very fast since outlined in 2006 by Tim Berners-Lee, and now it has become a hot topic of web. It connects the traditional isolation data sets, and has become an important force to promote the development of semantic web. But firstly, we should publish the datasets into the web and interlink them with each other. On the other hand, the large number of data is heterogeneous, distributed, closed which bring in a serious impact on the sharing and use of data resources. How to expose them into the web under some unified standard or specification and providing meaningful association between them become the current problems to be solved. Thirdly, most of the current publishing tools do not support the interlinking of different datasets. In this paper, for relational database, we proposed the theory that relational database could be converted into ontology naturally, and based on which, we develop a linked data platform D2R +  with the help of D2R open source. The platform could not only publish the data into web, but also support the interlinking among different datasets. What’s more, the platform provides a user interface that allows the user to add data sets, as well as custom association relationship, and an intuitive way to browser the published data. It supports multiple types of data. Here, we take Qinghai Lake data and scientist data as an example to demonstrate the application of D2R + .