Enhanced analysis of Open Government Data: Proposed metrics for improving data quality assessment

The release of Open Government Data (OGD) in recent years has maintained a very rapid pace to enable the OGD initiative to reach its full potential, such as enhancing transparency, citizen collaboration, and participation and boosting economic innovation value. Moreover, by publishing OGD, citizens can participate in governance processes, like policy-making and decision-making. Using Linked Open Data (LOD) technology allows us to understand and correctly use the released data by humans and machines. However, expert evidence shows that releasing data without quality control can threaten the reuse of datasets and negatively affect the benefits of the OGD initiative. Data accessibility is classified among the essential categories in Linked Open Data (LOD) quality models to enable efficient access to the released datasets. Most existing evaluations of data accessibility for the OGD portals focus on defining dimensions and measures, but there is no closed formulation to apply them. Some works propose marks to assess the data that meet the defined measures, and there is no broad scale of marks to standardize the application of these measures. This leads to difficulties in comparing and benchmarking evaluations. This paper aims to propose a percentage scale of marks for metrics to assess the accessibility of data in the OGD portals. Finally, we experiment with the proposed scale of marks on the American OGD portal since America launched the OGD initiative, and its portal is considered an example of OGD initiatives.