• DocumentCode
    1791786
  • Title

    BigExcel: A web-based framework for exploring big data in social sciences

  • Author

    Saleem, Muhammed Asif ; Varghese, Binni ; Barker, Adam

  • Author_Institution
    Sch. of Comput. Sci., Univ. of St. Andrews, St. Andrews, UK
  • fYear
    2014
  • fDate
    27-30 Oct. 2014
  • Firstpage
    84
  • Lastpage
    91
  • 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/.
  • Keywords
    Big Data; Internet; social sciences computing; Big Data; BigExcel framework; Yahoo Buzz Score data set; Yahoo Sandbox datasets; Yahoo n-gram corpus; ad hoc exploration; infrastructure management; noncomputer science related disciplines; social sciences; source code; three tier Web-based framework; trending technology prediction; user interaction management; Big data; Browsers; Correlation; Electronic publishing; Games; Market research; Real-time systems; Big data; Hadoop; Hive; Real-time processing; Web-based querying;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Big Data (Big Data), 2014 IEEE International Conference on
  • Conference_Location
    Washington, DC
  • Type

    conf

  • DOI
    10.1109/BigData.2014.7004458
  • Filename
    7004458