BigExcel: a web-based framework for exploring big data in Social Sciences

Muhammed Asif Saleem, Blesson Varghese, Adam Barker

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

6 Citations (Scopus)
4 Downloads (Pure)

Abstract

This paper argues that there are three fundamental challenges that need to be overcome in order to foster the adoption of big data technologies in non-computer science related disciplines: addressing issues of accessibility of such technologies for non-computer scientists, supporting the ad hoc exploration of large data sets with minimal effort and the availability of lightweight web-based frameworks for quick and easy analytics. In this paper, we address the above three challenges through the development of 'BigExcel', a three tier web-based framework for exploring big data to facilitate the management of user interactions with large data sets, the construction of queries to explore the data set and the management of the infrastructure. The feasibility of BigExcel is demonstrated through two Yahoo Sandbox datasets. The first dataset is the Yahoo Buzz Score data set we use for quantitatively predicting trending technologies and the second is the Yahoo n-gram corpus we use for qualitatively inferring the coverage of important events. A demonstration of the BigExcel framework and source code is available at http://bigdata.cs.st-andrews.ac.uk/projects/bigexcel-exploring-big-data-for-social-sciences/.
Original languageEnglish
Title of host publication2014 IEEE International Conference on Big Data, IEEE Big Data 2014
PublisherIEEE Computer Society
Pages84-91
Number of pages8
ISBN (Print)9781479956654
DOIs
Publication statusPublished - 7 Jan 2015
Event2nd IEEE International Conference on Big Data, IEEE Big Data 2014 - Washington, United States
Duration: 27 Oct 201430 Oct 2014

Conference

Conference2nd IEEE International Conference on Big Data, IEEE Big Data 2014
Country/TerritoryUnited States
CityWashington
Period27/10/1430/10/14

Keywords

  • Big data
  • Real-time processing
  • Hive
  • Hadoop
  • Web-based querying

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