ProGOMap: Automatic Generation of Mappings From Property Graphs to Ontologies

被引:5
作者
Fathy, Naglaa [1 ]
Gad, Walaa [1 ]
Badr, Nagwa [1 ]
Hashem, Mohamed [1 ]
机构
[1] Ain Shams Univ, Fac Comp & Informat Sci, Dept Informat Syst, Cairo 11566, Egypt
关键词
Ontologies; Resource description framework; Semantics; Relational databases; Data models; Object recognition; Measurement; Property graph database; resource description framework; ontology engineering; ontology alignment; graph model heterogeneity; OWL;
D O I
10.1109/ACCESS.2021.3104293
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Property Graph databases (PGs) are emerging as efficient graph stores with flexible schemata. This raises the need to have a unified view over heterogenous data produced from these stores. Ontology based Data Access (OBDA) has become the most dominant approach to integrate heterogeneous data sources by providing a unified conceptual view (ontology) over them. The corner stone of any OBDA system is to define mappings between the data source and the target (domain) ontology. However, manual mapping generation is time consuming and requires great efforts. This paper proposes ProGOMap (Property Graph to Ontology Mapper) system that automatically generates mappings from property graphs to a domain ontology. ProGOMap starts by generating a putative ontology with direct axioms from PG. A novel ontology learning algorithm is proposed to enrich the putative ontology with subclass axioms inferred from PG. The putative ontology is then aligned to an existing domain ontology using string similarity metrics. Another algorithm is proposed to align object properties between the two ontologies considering different modelling criteria. Finally, mappings are generated from alignment results. Experiments were done on eight data sets with different scenarios to evaluate the effectiveness of the generated mappings. The experimental results achieved mapping accuracy up to 97% and 81% when addressing PG-to-ontology terminological and structural heterogeneities, respectively. Ontology learning by inferring subclass axioms from a property graph helps to address the heterogeneity between the PG and ontology models.
引用
收藏
页码:113100 / 113116
页数:17
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