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Knowledge Graph Data Management: Models, Methods, and Systems

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Book cover Web Information Systems Engineering (WISE 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1155))

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Abstract

With the rise of artificial intelligence, knowledge graphs have been widely considered as a cornerstone of AI. In recent years, an increasing number of large-scale knowledge graphs have been constructed and published, by both academic and industrial communities, such as DBpedia, YAGO, Wikidata, Google Knowledge Graph, Microsoft Satori, Facebook Entity Graph, and others. In fact, a knowledge graph is essentially a large network of entities, their properties, semantic relationships between entities, and ontologies the entities conform to. Such kind of graph-based knowledge data has been posing a great challenge to the traditional data management theories and technologies. In this paper, we introduce the state-of-the-art research on knowledge graph data management, which includes knowledge graph data models, query languages, storage schemes, query processing, and reasoning. We will also describe the latest development trends of various database management systems for knowledge graphs.

Supported by the National Natural Science Foundation of China (61972275) and the Natural Science Foundation of Tianjin (17JCYBJC15400).

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Acknowledgments

This work is supported by the National Natural Science Foundation of China (61572353) and the Natural Science Foundation of Tianjin (17JCYBJC15400).

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Authors and Affiliations

  1. College of Intelligence and Computing, Tianjin University, Tianjin, 300350, China

    Xin Wang & Weixue Chen

  2. Tianjin Key Laboratory of Cognitive Computing and Application, Tianjin, 300350, China

    Xin Wang & Weixue Chen

Authors
  1. Xin Wang
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  2. Weixue Chen
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Corresponding author

Correspondence to Xin Wang .

Editor information

Editors and Affiliations

  1. University of Macau, Macau, China

    Leong Hou U

  2. Macquarie University, Sydney, NSW, Australia

    Jian Yang

  3. South China University of Technology, Guangzhou, China

    Yi Cai

  4. International Institute of Information Technology, Hyderabad, India

    Kamalakar Karlapalem

  5. Soochow University, Suzhou, China

    An Liu

  6. Hong Kong Baptist University, Hong Kong, China

    Xin Huang

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Wang, X., Chen, W. (2020). Knowledge Graph Data Management: Models, Methods, and Systems. In: U, L., Yang, J., Cai, Y., Karlapalem, K., Liu, A., Huang, X. (eds) Web Information Systems Engineering. WISE 2020. Communications in Computer and Information Science, vol 1155. Springer, Singapore. https://doi.org/10.1007/978-981-15-3281-8_1

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  • DOI: https://doi.org/10.1007/978-981-15-3281-8_1

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-3280-1

  • Online ISBN: 978-981-15-3281-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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