Abstract
With the continuous expansion of spatiotemporal applications, spatiotemporal data has been widely used in various fields. Because XML (eXtensible Markup Language) has been the de-facto standard for representing and exchanging data on the Web, and fuzziness is an inherent feature of most spatiotemporal applications, researches on fuzzy spatiotemporal XML data have received increasing attention. Although XML has been employed to represent and query fuzzy spatiotemporal data, relatively little work has been carried out to integrate heterogeneous fuzzy spatiotemporal data. More importantly, current efforts do not take global and local cases into account when representing and querying heterogeneous fuzzy spatiotemporal XML data. In this paper, after presenting fuzzy spatiotemporal data based on XML, we propose an integration model for fuzzy spatiotemporal XML data. Then, feature expression and field mapping table are used to decompose the query, and the local data sources that do not exist in the query results are excluded to improve the query efficiency. Then, using the information in the feature expression, the XQuery query language is transformed into the query language corresponding to the local data source. After getting the results of each local data source, the semantic heterogeneity is eliminated by using field mapping table, and the query results are uniformly described as data source views by using XML Schema. Finally, the query results are screened and combined by using the query conditions stored in the query decomposition process. This query process shields the semantic heterogeneity and structural heterogeneity of the underlying data source, and ensures the transparency of user query. Finally, the presented instance show that our approach is correct, and the experimental results show the performance advantages of our approach.
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Funding
The work was supported by the National Natural Science Foundation of China (61402087), the Natural Science Foundation of Hebei Province (F2022501015), and the Fundamental Research Funds for the Central Universities (2023GFYD003).
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Lin Zhu: Methodology, Investigation, Validation, Formal analysis, Writing—original draft, Writing—review & editing; Jiahui Wang: Validation, Formal analysis, Writing—original draft; Luyi Bai: Conceptualization, Methodology, Formal analysis, Funding acquisition, Writing—original draft, Writing—review & editing.
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Lin Zhu, received her PhD degree from Liaoning Technical University, China. She is currently a lecturer at Northeastern University at Qinhuangdao, China. Her current research interests include knowledge graph and spatiotemporal database. She has published over 20 papers in several journals such as Expert Systems with Applications, Applied Soft Computing, and Applied Intelligence, etc. She is also a member of CAAI.
Jiahui Wang is pursuing the bachelor’s degree with Northeastern University, China. Her main research interests include spatiotemporal data modeling and reasoning
Luyi Bai, received his PhD degree from Northeastern University in 2013, China. He is an academic visiting scholar at University of Leicester, UK. He is currently an associate professor at Northeastern University (Qinhuangdao), Qinhuangdao, China. His current research interests include knowledge graph, uncertain databases, fuzzy spatiotemporal data management. He has published over 40 papers in several journals such as ACM Transactions on Knowledge Discovery from Data, World Wide Web Journal, Information Sciences, Neural Networks, Knowledge-Based Systems, and Expert Systems with Applications, etc. He has also published over 30 papers in several conferences such as WWW and DASFAA. He has authored one monograph published by Springer. He is also a member of IEEE, ACM, CCF, and CAAI.
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Zhu, L., Wang, J. & Bai, L. A general characterization of integrating and querying heterogeneous fuzzy spatiotemporal XML data. Earth Sci Inform 16, 3303–3321 (2023). https://doi.org/10.1007/s12145-023-01091-8
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DOI: https://doi.org/10.1007/s12145-023-01091-8