HAO Unity
Fei Jie, Yanxiang Huang, Qiangwei Bai, Xindong Wu · 2021
Many real-world applications have to face the problem of diversity in data formats and semantics. Currently, how to deal with heterogeneous data effectively is still a big challenge. With the rise of knowledge graphs, more and more applications are built upon graph-like data models, which benefit from flexible schemas and convenient support for relationship queries. We propose a graph-based unifying system for heterogeneous data unification, which helps to (1) transform data in many other formats into graphs, or conversely, from graph to other formats, (2) integrate graph data based on HAO intelligence, which achieves schema integration and entity consolidation, and (3) explore data at different levels via querying the integrated graphs. In this paper, we introduce the overall system architecture, explain in detail the implementation, and display the usage in two practical scenarios.