Research on big data integration based on Karma modeling

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

Abstract

Aiming at the problem of data integration about heterogeneous and large amount of data in big data 4V features, the method of data integration based on Karma modeling is explored, and the data set of literature area is used as an example to verify the method. First of all, analyze specifically part of the literature data sets that are obtained. And then using Protégé ontology modeling tool to build the related domain ontology. Through the Karma modeling tool, the literature data set is mapped to the literature domain ontology and uniformly published as RDF data so that the semantic mapping is achieved, which effectively solve the important problem of multi-source and heterogeneous data. The Karma model that is built and published will be applied to complete big data set for big data integration. Finally, we sum up the results of the practice and address our future works.

Original languageEnglish
Title of host publicationICSESS 2017 - Proceedings of 2017 IEEE 8th International Conference on Software Engineering and Service Science
EditorsLi Wenzheng, M. Surendra Prasad Babu, Lei Xiaohui
PublisherIEEE Computer Society
Pages245-248
Number of pages4
ISBN (Electronic)9781538645703
DOIs
StatePublished - 2 Jul 2017
Event8th IEEE International Conference on Software Engineering and Service Science, ICSESS 2017 - Beijing, China
Duration: 24 Nov 201726 Nov 2017

Publication series

NameProceedings of the IEEE International Conference on Software Engineering and Service Sciences, ICSESS
Volume2017-November
ISSN (Print)2327-0586
ISSN (Electronic)2327-0594

Conference

Conference8th IEEE International Conference on Software Engineering and Service Science, ICSESS 2017
Country/TerritoryChina
CityBeijing
Period24/11/1726/11/17

Keywords

  • Karma modeling
  • RDF data
  • big data integration
  • ontology

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