Voovle: A linked data search engine for scientific data

Zhihong Shen, Yanfei Hou, Chengzan Li, Jianhui Li

Abstract: Research activities are generating huge amounts of scientific data. This data deluge calls for search engines which can efficiently find out the required scientific data from a wide range of scientific data management systems for the users. The traditional document-oriented search engines are generally ineffective at discovering scientific data. This paper briefly introduces the background and requirement for developing scientific data-oriented search engines, and analyzes the issues and challenges are required to reflect upon and overcome for such search engines. It summarizes at the state of the art of the related work. And then in the main part of this paper, a linked data search engine for scientific data named Voovle is presented. It has been used in the Scientific Database project of Chinese Academy of Sciences. The workflow of Voovle is described emphatically. It consists of four processes including publishing, fetching scientific data and metadata, searching scientific data and discovering links among them. At last, the paper gives a glance at the application status of Voovle and the further work for improving it.