Abstract
With the development of knowledge-based artificial intelligence, the scale of knowledge graphs has been increasing rapidly. The RDF graph and the property graph are two mainstream data models of knowledge graphs. On the one hand, with the development of the Semantic Web, there are a large number of RDF knowledge graphs. On the other hand, property graphs are widely used in the graph database community. However, different families of data management methods of RDF graphs and property graphs have been seperately developed in each community over a decade, which hinder the interoperability in managing large knowledge graph data. To address this problem, we propose a unified storage scheme for knowledge graphs which can seamlessly accommodate both RDF and property graphs. Meanwhile, the concept of ontology is introduced to meet the need for RDF graph data storage and query load. Experimental results on the benchmark datasets show that the proposed ontology-aware unified storage scheme can effectively manage large-scale knowledge graphs and significantly avoid data redundancy.
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Acknowledgments
This work is supported by the National Natural Science Foundation of China (61972275), the Natural Science Foundation of Tianjin (17JCYBJC15400), and CCF-Huawei Database Innovation Research Plan.
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Li, S., Rao, G., Liu, B., Liu, P., Dong, S., Feng, Z. (2020). An Ontology-Aware Unified Storage Scheme for Knowledge Graphs. In: Wang, X., Zhang, R., Lee, YK., Sun, L., Moon, YS. (eds) Web and Big Data. APWeb-WAIM 2020. Lecture Notes in Computer Science(), vol 12317. Springer, Cham. https://doi.org/10.1007/978-3-030-60259-8_17
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DOI: https://doi.org/10.1007/978-3-030-60259-8_17
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