KUKU

KU ScholarWorks

  • myKU
  • Email
  • Enroll & Pay
  • KU Directory
    • Login
    View Item 
    •   KU ScholarWorks
    • Institute for Policy & Social Research
    • Data Science
    • NADDI
    • View Item
    •   KU ScholarWorks
    • Institute for Policy & Social Research
    • Data Science
    • NADDI
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Generic Statistical Information Model (GSIM)

    Thumbnail
    View/Open
    Gregory_GSIM_NADDI2013.pptx (2.263Mb)
    Gregory_GSIM_NADDI2013.pdf (1.289Mb)
    Gregory_GSIM_NADDI2013.pdf (1.289Mb)
    Issue Date
    2013-04-03
    Author
    Lalor, Thérèse
    Vale, Steven
    Gregory, Arofan
    Type
    Presentation
    Metadata
    Show full item record
    Abstract
    Across the world statistical organizations undertake similar activities. Each of these activities use and produce similar information (for example all agencies use classifications, create data sets and publish products). Although the information is at its core the same, organizations tend to describe this information slightly differently (and often in different ways within each organization). There is no common means to describe the information. GSIM is a conceptual model that provides a set of standardized, consistently described information objects, which are the inputs and outputs in the design and production of statistics. DDI is a key standard in both the development of GSIM itself, and as an implementation tool for organizations using GSIM. Beyond that, it also will influence the future directions of DDI development, attracting a larger number of data producers into the DDI community. This presentation introduces GSIM and looks at the interaction between GSIM and DDI (and other related standards), and provides an update on a rapidly-evolving vision around the use of DDI within the statistical institutes in Europe and elsewhere. It will cover both the direct interaction between DDI and GSIM, and also provide a broader context for understanding what that dynamic may mean in the future.
    Description
    Presentation at the North American Data Documentation Conference (NADDI) 2013
    URI
    http://hdl.handle.net/1808/11045
    Collections
    • NADDI [27]
    Citation
    Lalor, Thérèse, Steven Vale, Arofan Gregory. (2013). Generic Statistical Information Model (GSIM). Paper presented at the North American Data Documentation Initiative Conference (NADDI 2013), University of Kansas, Lawrence, Kansas, April 3, 2013. http://hdl.handle.net/1808/11045

    Items in KU ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.


    We want to hear from you! Please share your stories about how Open Access to this item benefits YOU.


    Contact KU ScholarWorks
    785-864-8983
    KU Libraries
    1425 Jayhawk Blvd
    Lawrence, KS 66045
    785-864-8983

    KU Libraries
    1425 Jayhawk Blvd
    Lawrence, KS 66045
    Image Credits
     

     

    Browse

    All of KU ScholarWorksCommunities & CollectionsThis Collection

    My Account

    LoginRegister

    Statistics

    View Usage Statistics

    Contact KU ScholarWorks
    785-864-8983
    KU Libraries
    1425 Jayhawk Blvd
    Lawrence, KS 66045
    785-864-8983

    KU Libraries
    1425 Jayhawk Blvd
    Lawrence, KS 66045
    Image Credits
     

     

    The University of Kansas
      Contact KU ScholarWorks
    Lawrence, KS | Maps
     
    • Academics
    • Admission
    • Alumni
    • Athletics
    • Campuses
    • Giving
    • Jobs

    The University of Kansas prohibits discrimination on the basis of race, color, ethnicity, religion, sex, national origin, age, ancestry, disability, status as a veteran, sexual orientation, marital status, parental status, gender identity, gender expression and genetic information in the University’s programs and activities. The following person has been designated to handle inquiries regarding the non-discrimination policies: Director of the Office of Institutional Opportunity and Access, IOA@ku.edu, 1246 W. Campus Road, Room 153A, Lawrence, KS, 66045, (785)864-6414, 711 TTY.

     Contact KU
    Lawrence, KS | Maps