IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i19p10602-d642258.html
   My bibliography  Save this article

A Method for Constructing Geographical Knowledge Graph from Multisource Data

Author

Listed:
  • Xuan Guo

    (Institute of Geospatial Information, Information Engineering University, Zhengzhou 450001, China)

  • Haizhong Qian

    (Institute of Geospatial Information, Information Engineering University, Zhengzhou 450001, China)

  • Fang Wu

    (School of Earth Science and Technology, Zhengzhou University, Zhengzhou 450001, China)

  • Junnan Liu

    (School of Earth Science and Technology, Zhengzhou University, Zhengzhou 450001, China)

Abstract

Global problems all occur at a particular location on or near the Earth’s surface. Sitting at the junction of artificial intelligence (AI) and big data, knowledge graphs (KGs) organize, interlink, and create semantic knowledge, thus attracting much attention worldwide. Although the existing KGs are constructed from internet encyclopedias and contain abundant knowledge, they lack exact coordinates and geographical relationships. In light of this, a geographical knowledge graph (GeoKG) construction method based on multisource data is proposed, consisting of a modeling schema layer and a filling data layer. This method has two advantages: (1) the knowledge can be extracted from geographic datasets; (2) the knowledge on multisource data can be represented and integrated. Firstly, the schema layer is designed to represent geographical knowledge. Then, the methods of extraction and integration from multisource data are designed to fill the data layer, and a storage method is developed to associate semantics with geospatial knowledge. Finally, the GeoKG is verified through linkage rate, semantic relationship rate, and application cases. The experiments indicate that the method could automatically extract and integrate knowledge from multisource data. Additionally, our GeoKG has a higher success rate of linking web pages with geographic datasets, and its exact coordinates have increased to 100%. This paper could bridge the distance between a Geographic Information System and a KG, thus facilitating more geospatial applications.

Suggested Citation

  • Xuan Guo & Haizhong Qian & Fang Wu & Junnan Liu, 2021. "A Method for Constructing Geographical Knowledge Graph from Multisource Data," Sustainability, MDPI, vol. 13(19), pages 1-17, September.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:19:p:10602-:d:642258
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/19/10602/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/13/19/10602/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Junnan Liu & Haiyan Liu & Xiaohui Chen & Xuan Guo & Qingbo Zhao & Jia Li & Lei Kang & Jianxiang Liu, 2021. "A Heterogeneous Geospatial Data Retrieval Method Using Knowledge Graph," Sustainability, MDPI, vol. 13(4), pages 1-21, February.
    2. Tianxing Wu & Guilin Qi & Cheng Li & Meng Wang, 2018. "A Survey of Techniques for Constructing Chinese Knowledge Graphs and Their Applications," Sustainability, MDPI, vol. 10(9), pages 1-26, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Qi He & Chenyang Yu & Wei Song & Xiaoyi Jiang & Lili Song & Jian Wang, 2023. "ISLKG: The Construction of Island Knowledge Graph and Knowledge Reasoning," Sustainability, MDPI, vol. 15(17), pages 1-26, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Chunyang Pan & William X. Wei & Etayankara Muralidharan & Jia Liao & Bernadette Andreosso-O’Callaghan, 2020. "Does China’s Outward Direct Investment Improve the Institutional Quality of the Belt and Road Countries?," Sustainability, MDPI, vol. 12(1), pages 1-21, January.
    2. Junnan Liu & Haiyan Liu & Xiaohui Chen & Xuan Guo & Qingbo Zhao & Jia Li & Lei Kang & Jianxiang Liu, 2021. "A Heterogeneous Geospatial Data Retrieval Method Using Knowledge Graph," Sustainability, MDPI, vol. 13(4), pages 1-21, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:13:y:2021:i:19:p:10602-:d:642258. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.