IDEAS home Printed from https://ideas.repec.org/a/spr/infosf/v15y2013i3d10.1007_s10796-012-9401-x.html
   My bibliography  Save this article

Capturing data quality requirements for web applications by means of DQ_WebRE

Author

Listed:
  • César Guerra-García

    (Polytechnic University of San Luis Potosí, UPSLP)

  • Ismael Caballero

    (University of Castilla-La Mancha)

  • Mario Piattini

    (University of Castilla-La Mancha)

Abstract

The number of Web applications which are part of Business Intelligence (BI) applications has grown exponentially in recent years, as has their complexity. Consequently, the amount of data used by these applications has also increased. The larger the number of data used, the greater the chance to make errors is. That being the case, managing data with an acceptable level of quality is paramount to success in any organizational business process. In order to raise and maintain adequate levels of Data Quality (DQ), it is indispensable for Web applications to be able to satisfy specific DQ requirements. To do so, DQ requirements should be captured and introduced into the development process of the Web Application, together with the other software requirements needed in the applications. In the field of Web application development, however, there appears to us to exist a lack of proposals aimed at managing specific DQ software requirements. This paper considers the MDA (Model Driven Architecture) approach and, principally, the benefits provided by Model Driven Web Engineering (MDWE), putting forward a proposal for two artifacts. These consist of a metamodel and a UML profile for the management of Data Quality Software Requirements for Web Applications (DQ_WebRE).

Suggested Citation

  • César Guerra-García & Ismael Caballero & Mario Piattini, 2013. "Capturing data quality requirements for web applications by means of DQ_WebRE," Information Systems Frontiers, Springer, vol. 15(3), pages 433-445, July.
  • Handle: RePEc:spr:infosf:v:15:y:2013:i:3:d:10.1007_s10796-012-9401-x
    DOI: 10.1007/s10796-012-9401-x
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10796-012-9401-x
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10796-012-9401-x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Xiang Fang & Clyde W. Holsapple, 2011. "Impacts of navigation structure, task complexity, and users’ domain knowledge on Web site usability—an empirical study," Information Systems Frontiers, Springer, vol. 13(4), pages 453-469, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Malu Castellanos & Florian Daniel & Irene Garrigós & Jose-Norberto Mazón, 2013. "Business Intelligence and the Web," Information Systems Frontiers, Springer, vol. 15(3), pages 307-309, July.
    2. Qi Liu & Gengzhong Feng & Nengmin Wang & Giri Kumar Tayi, 2018. "A multi-objective model for discovering high-quality knowledge based on data quality and prior knowledge," Information Systems Frontiers, Springer, vol. 20(2), pages 401-416, April.
    3. Álvaro Carrera & Carlos A. Iglesias & Mercedes Garijo, 2014. "Beast methodology: An agile testing methodology for multi-agent systems based on behaviour driven development," Information Systems Frontiers, Springer, vol. 16(2), pages 169-182, April.
    4. Qi Liu & Gengzhong Feng & Nengmin Wang & Giri Kumar Tayi, 0. "A multi-objective model for discovering high-quality knowledge based on data quality and prior knowledge," Information Systems Frontiers, Springer, vol. 0, pages 1-16.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. R. Ramesh & H. Raghav Rao, 2011. "Editorial," Information Systems Frontiers, Springer, vol. 13(4), pages 451-452, September.
    2. Chulhwan Chris Bang, 2015. "Information systems frontiers: Keyword analysis and classification," Information Systems Frontiers, Springer, vol. 17(1), pages 217-237, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:infosf:v:15:y:2013:i:3:d:10.1007_s10796-012-9401-x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.