The Semantic Web Approach for the Collaborative Analysis and Visualization of Ethnic Education and Vocation

The economic, educational and vocational growth is the key factor to the unity and development of ethnic areas and population in China. Ethnic universities dedicated to minority nationalities play a key role in cultivating ethnic graduates for such a purpose. This paper proposes a Semantic Web approach for the collaborative analysis and visualization of ethnic education and vocation based on ethnic university-centric statistics. Semantic Web techniques are adopted for the modeling, storage and query of ethnic education and vocation data. A modified PageRank algorithm is derived to evaluate ethnic entrepreneurship and innovation achievements. Then, hidden relationships between educational and vocational statistics are mined by means of SPARQL query language. Finally, the collaborative analysis is visualized in a Baidu Map based Web frontend. Experiment results and demonstration of our system exhibit its applicability in analyzing and rendering ethnic education and vocation statistics.