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

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BigHumanities2014_CRV.pdf (2.429Mb)
Date
07/01/2015
Author
Saleem, Muhammed Asif
Varghese, Blesson
Barker, Adam
Keywords
Big data
Real-time processing
Hive
Hadoop
Web-based querying
QA75 Electronic computers. Computer science
DAS
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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/.
Citation
Saleem , M A , Varghese , B & Barker , A 2015 , BigExcel : a web-based framework for exploring big data in Social Sciences . in 2014 IEEE International Conference on Big Data, IEEE Big Data 2014 . IEEE Computer Society , pp. 84-91 , 2nd IEEE International Conference on Big Data, IEEE Big Data 2014 , Washington , United States , 27/10/14 . https://doi.org/10.1109/BigData.2014.7004458
 
conference
 
Publication
2014 IEEE International Conference on Big Data, IEEE Big Data 2014
DOI
https://doi.org/10.1109/BigData.2014.7004458
Type
Conference item
Rights
© 2014 IEEE. Reproduced in accordance with the publisher's manuscript reuse policy. The final published version can be found here: http://dx.doi.org/10.1109/BigData.2014.7004458
Description
This research was pursued through an Amazon Web Services Education Research Grant. The first author was the recipient of an Erasmus Mundus scholarship.
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  • Computer Science Research
  • University of St Andrews Research
URL
http://cci.drexel.edu/bigdata/bigdata2014/
URI
http://hdl.handle.net/10023/6805

Items in the St Andrews Research Repository are protected by copyright, with all rights reserved, unless otherwise indicated.

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