Abstract

Open government data (OGD) portals are official websites where governments can publish OGD in a controlled way. OGD portals foster discoverability, accountability, and reusability for stakeholders. This data article presents the data collected while monitoring the OGD portals in the 28 countries of the European Union. Several parameters and indicators observed over a period of 3 years in the official national open data portals were located and recorded to create this dataset. Data were manually obtained from existing public data sources and official OGD portals freely available on the Web. Clustering techniques using Density-based spatial clustering of applications with noise (DBSCAN) were applied to elaborate a dataset showcasing similar countries with respect to different parameters and indicators. Cluster data validation was carried out using the Davies–Bouldin index. The data presented in this article are related to the research article entitled “Open government data portals in the European Union: Considerations, development and expectations” [1].

Highlights

  • Open government data (OGD) portals are official websites where governments can publish OGD in a controlled way

  • OGD portals foster discoverability, accountability, and reusability for stakeholders. This data article presents the data collected while monitoring the OGD portals in the 28 countries of the European Union

  • Data were manually obtained from existing public data sources and official OGD portals freely available on the Web

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Summary

Data Article

Open government data (OGD) portals are official websites where governments can publish OGD in a controlled way. OGD portals foster discoverability, accountability, and reusability for stakeholders. This data article presents the data collected while monitoring the OGD portals in the 28 countries of the European Union. Several parameters and indicators observed over a period of 3 years in the official national open data portals were located and recorded to create this dataset. Data were manually obtained from existing public data sources and official OGD portals freely available on the Web. Clustering techniques using Density-based spatial clustering of applications with noise (DBSCAN) were applied to elaborate a dataset showcasing similar countries with respect to different parameters and indicators.

Related research article
United Kingdom
Number of datasets
CPI datasets organizations applications
Full Text
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