Construction of Earth Observation Knowledge Hub Based on Knowledge Graph

Author:

Cai Kuangsheng12ORCID,Chen Zugang123,Li Jin2,Wang Shaohua1ORCID,Li Guoqing1,Li Jing1,Guo Hengliang2,Chen Feng2,Zhu Liping4

Affiliation:

1. Aerospace Information Research Institute Chinese Academy of Sciences Beijing China

2. Zhengzhou University Zhengzhou China

3. Key Laboratory of Earth Observation of Hainan Province Hainan Aerospace Information Research Institute Sanya China

4. China Construction Seven Engineering Division Corp Ltd Zhengzhou China

Abstract

ABSTRACTOwing to the rapid development of Earth observation and Internet technology, researchers have acquired and shared a large amount of Earth observation data. However, traditional data sharing does not provide direct solutions to problems. The large amount of tacit knowledge contained in scientific data, scientific literature, analysis models, software/code, documentation, and other scientific resources on Earth observation applications has not been effectively organized and shared. To solve this problem, the Group on Earth Observations proposed an Earth Observation Knowledge Hub (EOKH); however, there is no unified and clear method for building an EOKH to date. This paper presents an automatic construction method for an EOKH on the basis of a knowledge graph, which describes scientific data, scientific literature, analysis models, software/code, documentation, and other scientific resources and their semantic relationships. An automatic discovery algorithm of scientific and technological resources was also constructed in this study on the basis of a knowledge graph from the Internet. This algorithm is capable of the automatic creation of knowledge packages and the construction of links between knowledge elements. Then, the knowledge discovery algorithm was evaluated through comparison with an existing method in relation to accuracy, and the results showed that our method outperforms the existing method. Lastly, the knowledge package was published on the Linked Open Data Cloud platform in the Resource Description Framework format, and an EOKH was created. Moreover, an application terminal based on SPARQL allowing users to search the EOKH was developed. A clear and operational method for the construction of an EOKH is proposed for the first time in this research, laying the foundation for the development of the EOKH.

Funder

National Natural Science Foundation of China

National Key Research and Development Program of China

Publisher

Wiley

Reference30 articles.

1. Enriching Word Vectors with Subword Information

2. The Semantic Web: the roles of XML and RDF

3. A Critical Comparison of the 4‐Intersection and 9‐Intersection Models for Spatial Relations: Formal Analysis;Egenhofer M. J.;Autocarto,2011

4. Knowledge clusters and knowledge hubs: designing epistemic landscapes for development

5. GEO.2019a.Results‐Oriented GEOSS_A Framework for Transforming Earth Observation Data to Knowledge for Decision Making GEO‐XVI Plenary.https://old.earthobservations.org/documents/geo16/GEO‐XVI‐6.1(Rev1)_Results‐Oriented%20GEOSS_A%20framework%20for%20transforming%20Earth%20observation%20data%20to%20knowledge%20for%20decision%20making.pdf.

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