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Querying Heterogeneous Property Graph Data Sources based on a Unified Conceptual View

Published: 05 January 2021 Publication History

Abstract

With the great success of NoSQL (Not only SQL) databases, data becomes more heterogeneous than ever. Hence, it is essential to provide solutions to integrate such heterogeneous databases and facilitate accessing them. This paper proposes an Ontology Based Data Access (OBDA) approach to query NoSQL property graph databases using SPARQL language. This allows users to access diverse data sources with the same query through a unified conceptual view (ontology). The proposed work goes through an offline phase to map the property graph data model to a unified ontology model. This is done by proposing hybrid relational graph algebra expressions. Then, an online phase starts when the user submits a SPARQL query. The submitted query is translated into the property graph declarative query language, Cypher. The translated query is then executed on the target property graph database and query results are presented to users in a unified format.

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    ICSIE '20: Proceedings of the 9th International Conference on Software and Information Engineering
    November 2020
    251 pages
    ISBN:9781450377218
    DOI:10.1145/3436829
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    • Ain Shams University: Ain Shams University, Egypt

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    Published: 05 January 2021

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    Author Tags

    1. Cypher
    2. OBDA
    3. Property graph
    4. RDF
    5. Relational graph algebra
    6. SPARQL

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