Integrating Big Data: A Semantic Extract-Transform-Load Framework

Srividya Bansal, Sebastian Kagemann

Research output: Contribution to specialist publicationArticle

29 Scopus citations

Abstract

Current tools that facilitate the extract-transform-load (ETL) process focus on ETL workflow, not on generating meaningful semantic relationships to integrate data from multiple, heterogeneous sources. A proposed semantic ETL framework applies semantics to various data fields and so allows richer data integration.

Original languageEnglish (US)
Pages42-50
Number of pages9
Volume48
No.3
Specialist publicationComputer
DOIs
Publication statusPublished - Mar 1 2015

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Keywords

  • big data
  • data integration
  • linked data
  • LOD
  • ontology engineering
  • semantic technologies

ASJC Scopus subject areas

  • Computer Science(all)

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