Support citizens in visualising open data

This paper contributes in the field of Open Data and their visualisations, trying to reduce the gap between the public institutions (who publish Open Data) and citizens, providing awareness of data quality and supporting them during the process of chart creation. Proposed solution syntactically analyses the dataset's values to infer its data types and continually shows a list of chart visualisations compatible with the selected dataset and its fields. Instead to start with a catalogue containing all available charts, the system reduces the space of charts proposing any time only those that are compatible. In addition, a well-known barrier in the use of Open Data is the poor quality of the available datasets, thus, this paper proposes two quality indexes to provide at glance awareness of the dataset quality. This provides a quantitative measurement to dataset publishers (e.g., public institutions), who can evaluate the data quality, and also the citizens, who can ask for better open datasets providing a reason for such request.