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The Knowledge Set of Landslide Factors and Their Relationships


LUO Chenchen1HUANG Shixiu1ZHANG Chunju1
1 School of Civil and Hydraulic Engineering,Hefei University of Technology,Hefei 230009,China

DOI:10.3974/geodb.2024.02.06.V1

Published:Feb. 2024

Visitors:679       Data Files Downloaded:24      
Data Downloaded:1.59 MB      Citations:

Key Words:

landslide,factor,knowledge,OWL,disaster

Abstract:

The landslide is a comprehensive result of geographical, geological, hydrological, vegetation, and human activities. It is important to identify the landslide factors and understand the relationships among them why and how the landslides happen. The knowledge set of landslide factors and their relationships was developed using the OWL (Web Ontology Language) language and the protege software. The knowledge set contains 319 landslide conceptual factors, 16 conceptual attribute relationships, 602 conceptual relationships between factors, 17 landslide basic values, and 246 annotations. The data is archived in .ttl format, and consists of two files with data size of 806 KB (Compressed into one file with 66.2 KB).

Foundation Item:

National Natural Science Foundation of China (42171453, 41971337)

Data Citation:

LUO Chenchen, HUANG Shixiu, ZHANG Chunju.The Knowledge Set of Landslide Factors and Their Relationships[J/DB/OL]. Digital Journal of Global Change Data Repository, 2024. https://doi.org/10.3974/geodb.2024.02.06.V1.

References:


     [1] Xu, Q., Cui, S. H., Huang, W., et al. Research on the construction method of landslide knowledge graph for the field of engineering geology [J]. Geomatics and Information Science of Wuhan University, 2023, 48(10): 1601-1615. DOI: 10.13203/j.whugis20230245.
     [2] Liu, W. C. Construction and Application of Landslide Knowledge Graph [D]. Hefei: Hefei University of Technology, 2022. DOI: 10.27101/d.cnki.ghfgu.2022.001288.
     [3] Gong, F., Wang, M., Wang, H., et al. SMR: medical knowledge graph embedding for safe medicine recommendation [J]. Big Data Research, 2021, 23: 100174.
     

Data Product:

ID Data Name Data Size Operation
1 KnowledgeSet_Landslide.rar 67.83KB
Co-Sponsors

Institute of Geographic Sciences and Natural Resources Research,Chinese Academy of Sciences

The Geographical Society of China

Parteners

Committee on Data for Science and Technology (CODATA) Task Group on Preservation of and Access to Scientific and Technical Data in/for/with Developing Countries (PASTD)

Jomo Kenyatta University of Agriculture and Technology

Digital Linchao GeoMuseum