An ontology-based system and method for urban traffic heterogeneous data integration

Abstract

The invention relates to an urban traffic heterogeneous data integration system and method based on a body. The problem that various grammars and lexemes of data and systems in the field of urban traffic are heterogeneous can be solved, and the data processing work efficiency is improved. The system consists of a query and decomposition module, a body and database mapping module, a query and generation submodule, a result merging module and a wrapper module. The method utilizes the body to achieve management of conventional and special data in the field of urban traffic through mapping among an established database table, field and body concepts and attributes, and the heterogeneous problem of data is solved while data integration. The peculiar characteristics of data in the field of urban traffic with respect to data in other fields are fully considered, the heterogeneous problem of the data in the field of urban traffic, which cannot be solved by adopting a pervasive method, is solved, accordingly a unified data query interface is provided for a data processing worker, and the data processing efficiency is improved.

Description

technical field [0001] The invention relates to an ontology-based urban traffic heterogeneous data integration system and method, belonging to the field of database / data integration. Background technique [0002] In order to solve the heterogeneous problem among data sources, researchers at home and abroad have done a lot of research work on data integration so far. At present, the data integration system architectures that have application value and are in the mainstream are mainly divided into two categories: ETL architecture and middleware architecture. [0003] The data processing process of the ETL architecture is mainly divided into three steps: Extract (extract), Transform (transform), Loading (load). In the extraction step, the system reads data from various data sources. In the conversion step, in order to make the data syntactically consistent with the schema in the target data warehouse table, the data will be uniformly converted according to the conversion rule...

AI Technical Summary

Problems solved by technology

[0006] At present, there are a large number of data integration systems based on the above-mentioned architecture in the field of transportation, but the methods used by these systems are suitable for conventional data integration management in various fields, and some unique characteristics of urban traffic data compared with data in other fields are not considered in the design. (such as the spatio-temporal characteristics of trajectory data, etc.), it is impossible to complete the management and query of urban traffic data

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