A Heterogeneous Data Integration Model

• Published in: Geo-Informatics in Resource Management and Sustainable Ecosystem pp. 298 - 312
• Main Authors: Liu, Hai, Liu, Yunzhen, Wu, Qunhui, Ma, Shilong
• Format: Book Chapter
• Language: English
• Published: Berlin, Heidelberg Springer Berlin Heidelberg
• Series: Communications in Computer and Information Science
• Subjects: data integration; Internet Of Things; view mapping
• ISBN: 9783642450242; 3642450245
• ISSN: 1865-0929; 1865-0937
• DOI: 10.1007/978-3-642-45025-9_31

With the rapid development of the Internet of Things (IOT), the data management, data mining and data analysis in IOT systems require improving the usability of the multi-sourced, distributed, autonomous and heterogeneous data from the subsystems, making the aggregation, integration and collaboration of the data a focus in research. According to the characteristics of basic IOT data environment, a HDIM is proposed based on the comparison and analysis of the current existing data integration approaches. This model can not only mask the data heterogeneity in distributions, but also provide the customized application view for the upper applications, which can decouple the programs and data structures; additionally, the model can maintain the integrity and consistency of the data. Based on this HDIM model, a pattern-mapping-based system with the name of UDMP is designed and implemented. The experiments show that the proposed model and the corresponding system can address the features of the IOT with relative good performance.