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Data Analysis and Knowledge Discovery  2019, Vol. 3 Issue (6): 109-116    DOI: 10.11925/infotech.2096-3467.2018.1240
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Visualizing Knowledge Graph of Academic Inheritance in Song Dynasty
Haici Yang,Jun Wang()
Information Management Department, Peking University, Beijing100871, China
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Abstract  

[Objective] The study constructs a knowledge graph of academic relationships among scholars in China’s Song Dynasty, aiming to provide new techniques for knowledge exploration in humanity research. [Context] Our study addresses the usability and visualization issues facing digital collections (i.e. the China Biographical Database Project), and establishes a knowledge portal for history researchers and amateurs. [Methods] First, we built the ontology of ancient Chinese scholars. Then, we transformed their relationship to RDF data for the knowledge graph. Finally, we created an online platform to demonstrate the visualization results. [Results] We created the knowledge graph with five classes and 39 relationships based on 48,018 peoples and 6,599 geographic data. The Song’s Academic Inheritance Platform integrates the RelFinder visualization tool to display the entities’ relationships in the knowledge graph. [Conclusions] This study offers practical solutions for semantic research on the China Biographical Database Project and related fields in history.
Key words： Academia in Song Dynasty      Digital Humanities      Knowledge Graph      Visualization     
Received: 08 November 2018      Published: 15 August 2019
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Haici Yang
Jun Wang

Cite this article:

Haici Yang,Jun Wang. Visualizing Knowledge Graph of Academic Inheritance in Song Dynasty. Data Analysis and Knowledge Discovery, 2019, 3(6): 109-116.

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https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.2096-3467.2018.1240     OR     https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2019/V3/I6/109

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