• DocumentCode
    2227757
  • Title

    An Architecture for Mining and Visualization of U.S. Higher Educational Data

  • Author

    Ngo, Linh Bao ; Dantuluri, Vijay ; Stealey, Michael ; Ahalt, Stan ; Apon, Amy

  • Author_Institution
    Sch. of Comput., Clemson Univ., Clemson, SC, USA
  • fYear
    2012
  • fDate
    16-18 April 2012
  • Firstpage
    783
  • Lastpage
    789
  • Abstract
    Higher education has undergone considerable change in the past decades. As a result, the higher education community is collecting and disseminating a great deal of data that is typically used to benchmark performance or satisfy reporting requirements. This data is a rich source for scholarly inquiry, and particularly interesting for questions related to investment strategies within the academy. However, the real value of these data sets can often only realized when the data is viewed and studied across the aggregate collection of data sources. This is a complex task that requires gathering, cleaning, and applying consistent metadata standards to data sets. This paper presents a Unified Data Framework that allows the aggregation of high demand data sources into a single useful research resource that is relevant to research in higher education. The Unified Data Framework guides the aggregation of existing and new data sets, and provides the option of connecting and automatically, or semi-automatically, updating data from the original sources. The Unified Data Framework presents to researchers of higher education a robust suite of analytic tools for data mining and visualization of combined and complex data sources.
  • Keywords
    computer aided instruction; data acquisition; data mining; data visualisation; further education; information dissemination; investment; meta data; U.S. higher education; data collection; data dissemination; data mining; data sets; data source aggregation; data visualization; investment strategy; meta data standard; unified data framework; Awards activities; Data mining; Databases; Educational institutions; Standards; Supercomputers; aggregation of institutional data; data consolidation; data framework; data interoperability;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Technology: New Generations (ITNG), 2012 Ninth International Conference on
  • Conference_Location
    Las Vegas, NV
  • Print_ISBN
    978-1-4673-0798-7
  • Type

    conf

  • DOI
    10.1109/ITNG.2012.151
  • Filename
    6209086