IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i3p1407-d734706.html
   My bibliography  Save this article

Using OpenGovB Transparency Indicator to Evaluate National Open Government Data

Author

Listed:
  • Petar Milić

    (Faculty of Technical Sciences, University of Priština—Kosovska Mitrovica, Kneza Miloša 7, 38227 Kosovska Mitrovica, Serbia)

  • Nataša Veljković

    (Faculty of Electronic Engineering, University of Niš, Aleksandra Medvedeva 14, 18000 Niš, Serbia)

  • Leonid Stoimenov

    (Faculty of Electronic Engineering, University of Niš, Aleksandra Medvedeva 14, 18000 Niš, Serbia)

Abstract

Transparency evaluation in open government is a process of measuring the extent of transparency against a predefined set of indicators. In this paper, we address the existing initiatives regarding data and government transparency evaluation as two separate indicators and present the analysis of their advantages and drawbacks. Based on that analysis, we extend a part of the OpenGovB benchmark related to transparency in open government. What is unique about this benchmark is that it utilizes metadata of data published on the open government data portals to calculate the majority of indicators related to data transparency indicators. For the government transparency indicator evaluation, the benchmark utilizes some of the well-known transparency indicators. The article shows concrete results obtained from the application of the defined transparency evaluation model on 22 open data portals, thus demonstrating the possibilities of its application as well as the gains regarding generated results. The proposed model bridges the gap between available methodologies for evaluating transparency based on collaboration and participation and methodologies for evaluating transparency based on open data.

Suggested Citation

  • Petar Milić & Nataša Veljković & Leonid Stoimenov, 2022. "Using OpenGovB Transparency Indicator to Evaluate National Open Government Data," Sustainability, MDPI, vol. 14(3), pages 1-16, January.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:3:p:1407-:d:734706
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/3/1407/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/3/1407/
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Daniyar Mukhametov, 2022. "Exploring the Influence of Government Data Performance on Knowledge Capabilities: Towards a Data-Oriented Political Economy," Social Sciences, MDPI, vol. 11(9), pages 1-14, August.

    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:gam:jsusta:v:14:y:2022:i:3:p:1407-:d:734706. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.