Model based development of data integration in graph databases using triple graph grammars

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

Graph databases such as neo4j are designed to handle and integrate big data from heterogeneous sources. For flexibility and performance they do not ensure data quality through schemata but leave it to the application level. In this paper, we present a model-driven approach for data integration through graph databases with data sources in relational databases. We model query and update operations in neo4j by triple graph grammars and map these to Gremlin code for execution. In this way we provide a model-based approach to data integration that is both visual and formal while providing the data quality assurances of a schema-based solution.

Original languageEnglish
Title of host publicationSoftware Technologies
Subtitle of host publicationApplications and Foundations - STAF 2018 Collocated Workshops, Revised Selected Papers
EditorsManuel Mazzara, Gwen Salaün, Iulian Ober
PublisherSpringer Verlag
Pages399-414
Number of pages16
ISBN (Print)9783030047702
DOIs
StatePublished - 2018
Externally publishedYes
EventInternational Conference on Software Technologies: Applications and Foundations, STAF 2018 - Toulouse, France
Duration: 25 Jun 201829 Jun 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11176 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceInternational Conference on Software Technologies: Applications and Foundations, STAF 2018
Country/TerritoryFrance
CityToulouse
Period25/06/1829/06/18

Keywords

  • Data integration
  • Graph databases
  • Model-based development
  • Triple graph grammars

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