A Constraint Framework for Uncertain Spatiotemporal Data in RDF Graphs

  • Jinyao Wang
  • Xiaofeng Di
  • Jiemin Liu
  • Luyi BaiEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1074)


Researches on spatiotemporal data based on the Resource Description Framework (RDF) have received increasing attention owing to that RDF has a lot of advantages such as extensibility and flexibility. At the same time, the works for uncertain data based on RDF have been extensively studied because of imprecision and uncertainty of data in many real-world applications. Although RDF has been employed to model and handle spatiotemporal data and uncertain data respectively, relatively little work has been carried out to further investigate spatiotemporal data with uncertainty, especially the consistencies of uncertain spatiotemporal data in RDF graphs. In this paper, we first propose an uncertain spatiotemporal data model and define the corresponding constraint framework for the model, then study the types of inconsistencies for uncertain spatiotemporal data in RDF graphs. On this basis, we present the methods for fixing the inconsistencies in the uncertain spatiotemporal RDF graphs caused by updating operations, inserting operations, and deleting operations.


Consistency RDF graph Uncertain spatiotemporal data 



This work was supported by the National Natural Science Foundation of China (61402087), the Natural Science Foundation of Hebei Province (F2019501030), the Natural Science Foundation of Liaoning Province (2019-MS-130), and the Fundamental Research Funds for the Central Universities (N172304026).


  1. 1.
    Lyell, M., Voyadgis, D., Song, M., et al.: An ontology-based spatiotemporal data model and query language for use in GIS-type applications. In: Proceedings of the 2nd International Conference on Computing for Geospatial Research & Applications, p. 15, DC (2011)Google Scholar
  2. 2.
    Perry, M., Jain, P., Sheth, A.P., et al.: SPARQL-ST: extending SPARQL to support spatiotemporal queries. In: Geospatial Semantics and the Semantic Web, pp. 61–86 (2011)Google Scholar
  3. 3.
    Wang, D., Zou, L., Zhao, D.: gst-store: querying large spatiotemporal RDF graphs. Data Inf. Manag. 1(2), 84–103 (2017)Google Scholar
  4. 4.
    Vaneková, V., Bella, J., Gurský, P., et al.: Fuzzy RDF in the semantic web: deduction and induction. In: Proceedings of the 6th Workshop on Data Analysis, Abaujszanto, pp. 16–29 (2005)Google Scholar
  5. 5.
    Lv, Y.H., Ma, Z.M., Yan, L.: Fuzzy RDF: a data model to represent fuzzy metadata. In: Proceedings of the 2008 IEEE International Conference on Fuzzy Systems, Hong Kong, China, pp. 1439–1445 (2008)Google Scholar
  6. 6.
    Ma, Z.M., Yan, L.: Modeling fuzzy data with RDF and fuzzy relational database models. Int. J. Intell. Syst. 33(7), 1534–1554 (2018)CrossRefGoogle Scholar
  7. 7.
    Del, M.G., Rodríguez, M.A., Claramunt, C.: Modeling consistency of spatiotemporal graphs. Data Knowl. Eng. 84, 59–80 (2013)CrossRefGoogle Scholar
  8. 8.
    Shuhadah, W.N., Deris, M.M., Noraziah, A.: Database consistency using update-ordering in distributed databases. J. Algorithms Comput. Technol. 1(1), 17–44 (2007)CrossRefGoogle Scholar
  9. 9.
    Sun, J., Xing, Y.J.: An effective image retrieval mechanism using family-based spatial consistency filtration with object region. Int. J. Autom. Comput. 7(1), 23–30 (2010)MathSciNetCrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Jinyao Wang
    • 1
  • Xiaofeng Di
    • 1
  • Jiemin Liu
    • 1
  • Luyi Bai
    • 1
    Email author
  1. 1.School of Computer and Communication EngineeringNortheastern University (Qinhuangdao)QinhuangdaoChina

Personalised recommendations