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dc.contributor.authorSaleem, Muhammed Asif
dc.contributor.authorVarghese, Blesson
dc.contributor.authorBarker, Adam
dc.date.accessioned2015-06-11T10:10:09Z
dc.date.available2015-06-11T10:10:09Z
dc.date.issued2015-01-07
dc.identifier.citationSaleem , 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.2014.7004458en
dc.identifier.citationconferenceen
dc.identifier.isbn9781479956654
dc.identifier.otherPURE: 165451896
dc.identifier.otherPURE UUID: 89986594-507e-4a58-953f-8267197d5395
dc.identifier.otherArXiv: http://arxiv.org/abs/1411.1215v1
dc.identifier.otherScopus: 84921759717
dc.identifier.otherWOS: 000380462900255
dc.identifier.urihttp://hdl.handle.net/10023/6805
dc.descriptionThis research was pursued through an Amazon Web Services Education Research Grant. The first author was the recipient of an Erasmus Mundus scholarship.en
dc.description.abstractThis 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/.
dc.format.extent8
dc.language.isoeng
dc.publisherIEEE Computer Society
dc.relation.ispartof2014 IEEE International Conference on Big Data, IEEE Big Data 2014en
dc.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.2014.7004458en
dc.subjectBig dataen
dc.subjectReal-time processingen
dc.subjectHiveen
dc.subjectHadoopen
dc.subjectWeb-based queryingen
dc.subjectQA75 Electronic computers. Computer scienceen
dc.subjectDASen
dc.subject.lccQA75en
dc.titleBigExcel : a web-based framework for exploring big data in Social Sciencesen
dc.typeConference itemen
dc.description.versionPostprinten
dc.contributor.institutionUniversity of St Andrews.School of Computer Scienceen
dc.identifier.doihttps://doi.org/10.1109/BigData.2014.7004458
dc.identifier.urlhttp://cci.drexel.edu/bigdata/bigdata2014/en


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