Metrics proposal to measure the quality of governmental datasets

The government challenge is to provide citizens with information efficiently and transparently. In this context, the new challenges that arise can be considered as an opportunity to rethink the methodologies of designing and implementing public policies and promoting a State with collaborating publi...

Full description

Saved in:
Bibliographic Details
Published in:Revista IEEE América Latina 2022-02, Vol.20 (2), p.301-308
Main Authors: Martinez, Roxana, Rodriguez, Rocio Andrea, Vera, Pablo Martin
Format: Article
Language:English
Subjects:
Best practices
Datasets
Government
Interoperability
Open Access
Open data
Portals
Proposals
Silicon
Software
Visualization
Citations: Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The government challenge is to provide citizens with information efficiently and transparently. In this context, the new challenges that arise can be considered as an opportunity to rethink the methodologies of designing and implementing public policies and promoting a State with collaborating public officials. All this leads to a new paradigm in the treatment of open and public information. Currently, data is an indispensable resource for any public management activity, so it is necessary to keep it updated and complete. Although it can be determined that more and more governments are embarking on this new concept of open data, there is still a long way to go. Several related works on this subject are increasingly focused on the quality of open data from the portals of government entities, but it is still necessary to reinforce and understand the importance of the data, that is, if a data has quality, it can be better used, manipulated and distributed to citizens for various purposes. This work focuses on the proposal of quality metrics to analyze the contents of published datasets and thus obtain an analysis to improve their dissemination and interoperability between databases and software.
ISSN:1548-0992
1548-0992
DOI:10.1109/TLA.2022.9661470