Towards a Semantic Extract-Transform-Load (ETL) framework for big data integration

Research output: Chapter in Book/Report/Conference proceedingConference contribution

44 Scopus citations

Abstract

Big Data has become the new ubiquitous term used to describe massive collection of datasets that are difficult to process using traditional database and software techniques. Most of this data is inaccessible to users, as we need technology and tools to find, transform, analyze, and visualize data in order to make it consumable for decision-making. One aspect of Big Data research is dealing with the Variety of data that includes various formats such as structured, numeric, unstructured text data, email, video, audio, stock ticker, etc. Managing, merging, and governing a variety of data is the focus of this paper. This paper proposes a semantic Extract-Transform-Load (ETL) framework that uses semantic technologies to integrate and publish data from multiple sources as open linked data. This includes - creation of a semantic data model to provide a basis for integration and understanding of knowledge from multiple sources, creation of a distributed Web of data using Resource Description Framework (RDF) as the graph data model, extraction of useful knowledge and information from the combined data using SPARQL as the semantic query language.

Original languageEnglish (US)
Title of host publicationProceedings - 2014 IEEE International Congress on Big Data, BigData Congress 2014
EditorsPeter Chen, Peter Chen, Hemant Jain
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages522-529
Number of pages8
ISBN (Electronic)9781479950577
DOIs
StatePublished - Sep 22 2014
Event3rd IEEE International Congress on Big Data, BigData Congress 2014 - Anchorage, United States
Duration: Jun 27 2014Jul 2 2014

Publication series

NameProceedings - 2014 IEEE International Congress on Big Data, BigData Congress 2014

Other

Other3rd IEEE International Congress on Big Data, BigData Congress 2014
CountryUnited States
CityAnchorage
Period6/27/147/2/14

Keywords

  • Big data
  • Data integration
  • Ontology
  • Semantic technolgies

ASJC Scopus subject areas

  • Computer Science Applications

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  • Cite this

    Bansal, S. (2014). Towards a Semantic Extract-Transform-Load (ETL) framework for big data integration. In P. Chen, P. Chen, & H. Jain (Eds.), Proceedings - 2014 IEEE International Congress on Big Data, BigData Congress 2014 (pp. 522-529). [6906824] (Proceedings - 2014 IEEE International Congress on Big Data, BigData Congress 2014). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BigData.Congress.2014.82