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Fully combining the emerging intelligent technologies, such as big data and artificial intelligence, to realize the effective data fusion of bridge management with multi-source, autonomous, massive, heterogeneous features, and to further improve the capability of domain knowledge sharing and services have become the urgent demand and future development trend in the field of bridge engineering. This paper summarizes the business background and big data characteristics of bridge management, and represents a brief review of related work. According to the big data knowledge engineering paradigm, this paper proposes a novel BigKE-based intelligent bridge management and maintenance framework consisting of the layers of data-sources, storage and computing, knowledge representation, knowledge computing, and knowledge services. The corresponding main research contents involved in each layer are discussed as well. Finally, we point out some possible application scenarios and main challenges of the proposed framework, which elaborate on areas for future research. • This paper provides the state-of-the-art survey of data-driven manners related to bridge management and maintenance. • A novel framework driven by big data knowledge engineering is proposed for intelligent bridge management and maintenance. • The typical application scenarios are used to illustrate the effect. The main challenges are discussed to elaborate on future research. [ABSTRACT FROM AUTHOR]