Asset Details
Do you wish to reserve the book?
A semantic network analysis of categorization in open government data portals
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
A semantic network analysis of categorization in open government data portals
Do you wish to request the book?
A semantic network analysis of categorization in open government data portals
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Journal Article
A semantic network analysis of categorization in open government data portals
2025
Overview
Purpose
This study aims to evaluate the semantic relationships between category terms that are used in open government data (OGD) portals and those identified in policy documents through the implementation of a semantic network analysis.
Design/methodology/approach
This study was conducted in three stages. Firstly, the study examined the semantic relationships between category terms in OGD portals by constructing a similarity matrix based on the terms’ co-occurrence and visualizing six-word groups. Secondly, the study investigated the semantic relationships among terms in OGD policy documents using latent semantic analysis and community detection methods, resulting in the identification and visualization of three network groups. Finally, the study used chi-squared and Z-tests to analyse differences in category terms between countries with and without redefined categories.
Findings
The results indicate that the three-word groups were identified by community detection, covering various aspects of government. In addition, there is a significant difference between the two country groups, with category terms being more prevalent in countries with predefined categories. This emphasizes the impact of categorization on term prevalence within OGD portals.
Originality/value
This study uniquely focuses on the categorization of government portals for sustainable open data management. The findings underscore the importance of effectively structuring and organizing data categories to enhance user discoverability and accessibility in OGD portals.
