Development of the polyglot Asian medicine knowledge graph system

The Polyglot Asian Medicine system hosts a research database of Asian traditional and herbal medicines, represented as a knowledge graph and implemented in a Neo4j graph database system. The current coverage of the database is mainly traditional Chinese medicines with some Malay and Indonesian data,...

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Main Authors: Khoo, Christopher S. G., Stanley-Baker, Michael, Faizah Binte Zakaria, Chen, Jinju, Ang, Shaun Qiao Rou, Huang, Bo
Other Authors: School of Humanities
Format: Conference or Workshop Item
Language:English
Published: 2024
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Online Access:https://hdl.handle.net/10356/179419
https://link.springer.com/chapter/10.1007/978-981-99-8088-8_1
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1794192024-07-31T05:23:53Z Development of the polyglot Asian medicine knowledge graph system Khoo, Christopher S. G. Stanley-Baker, Michael Faizah Binte Zakaria Chen, Jinju Ang, Shaun Qiao Rou Huang, Bo School of Humanities Wee Kim Wee School of Communication and Information 25th International Conference on Asia-Pacific Digital Libraries (ICADL 2023) Computer and Information Science Knowledge graph Traditional Chinese medicine The Polyglot Asian Medicine system hosts a research database of Asian traditional and herbal medicines, represented as a knowledge graph and implemented in a Neo4j graph database system. The current coverage of the database is mainly traditional Chinese medicines with some Malay and Indonesian data, with plans to extend to other Southeast Asian communities. The knowledge graph currently links the medicine names in the original and English languages, to alternate names and scientific names, to plant/animal parts they are made from, to literary and historical sources they were mentioned in, to geographic areas they were associated with, and to external database records. A novel graph visualization interface supports user searching, browsing and visual analysis. This is an example of representing a digital humanities research dataset as a knowledge graph for reference and research purposes. The paper describes how the knowledge graph was derived based on a dataset comprising over 25 Microsoft Excel spreadsheets, and how the spreadsheet data were processed and mapped to the graph database using upload scripts in the Neo4j Cypher graph query language. The advantages of using a knowledge graph system to support user browsing and analysis using a graph visualization interface are illustrated. The paper describes issues encountered, solutions adopted, and lessons learned that can be applied to other digital humanities data. 2024-07-31T05:23:53Z 2024-07-31T05:23:53Z 2023 Conference Paper Khoo, C. S. G., Stanley-Baker, M., Faizah Binte Zakaria, Chen, J., Ang, S. Q. R. & Huang, B. (2023). Development of the polyglot Asian medicine knowledge graph system. 25th International Conference on Asia-Pacific Digital Libraries (ICADL 2023), LNCS 14458, 3-11. https://dx.doi.org/10.1007/978-981-99-8088-8_1 9789819980871 https://hdl.handle.net/10356/179419 10.1007/978-981-99-8088-8_1 2-s2.0-85180149900 https://link.springer.com/chapter/10.1007/978-981-99-8088-8_1 LNCS 14458 3 11 en © 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. All rights reserved.
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Computer and Information Science
Knowledge graph
Traditional Chinese medicine
spellingShingle Computer and Information Science
Knowledge graph
Traditional Chinese medicine
Khoo, Christopher S. G.
Stanley-Baker, Michael
Faizah Binte Zakaria
Chen, Jinju
Ang, Shaun Qiao Rou
Huang, Bo
Development of the polyglot Asian medicine knowledge graph system
description The Polyglot Asian Medicine system hosts a research database of Asian traditional and herbal medicines, represented as a knowledge graph and implemented in a Neo4j graph database system. The current coverage of the database is mainly traditional Chinese medicines with some Malay and Indonesian data, with plans to extend to other Southeast Asian communities. The knowledge graph currently links the medicine names in the original and English languages, to alternate names and scientific names, to plant/animal parts they are made from, to literary and historical sources they were mentioned in, to geographic areas they were associated with, and to external database records. A novel graph visualization interface supports user searching, browsing and visual analysis. This is an example of representing a digital humanities research dataset as a knowledge graph for reference and research purposes. The paper describes how the knowledge graph was derived based on a dataset comprising over 25 Microsoft Excel spreadsheets, and how the spreadsheet data were processed and mapped to the graph database using upload scripts in the Neo4j Cypher graph query language. The advantages of using a knowledge graph system to support user browsing and analysis using a graph visualization interface are illustrated. The paper describes issues encountered, solutions adopted, and lessons learned that can be applied to other digital humanities data.
author2 School of Humanities
author_facet School of Humanities
Khoo, Christopher S. G.
Stanley-Baker, Michael
Faizah Binte Zakaria
Chen, Jinju
Ang, Shaun Qiao Rou
Huang, Bo
format Conference or Workshop Item
author Khoo, Christopher S. G.
Stanley-Baker, Michael
Faizah Binte Zakaria
Chen, Jinju
Ang, Shaun Qiao Rou
Huang, Bo
author_sort Khoo, Christopher S. G.
title Development of the polyglot Asian medicine knowledge graph system
title_short Development of the polyglot Asian medicine knowledge graph system
title_full Development of the polyglot Asian medicine knowledge graph system
title_fullStr Development of the polyglot Asian medicine knowledge graph system
title_full_unstemmed Development of the polyglot Asian medicine knowledge graph system
title_sort development of the polyglot asian medicine knowledge graph system
publishDate 2024
url https://hdl.handle.net/10356/179419
https://link.springer.com/chapter/10.1007/978-981-99-8088-8_1
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