Quality analysis of the Italian open government data through a generalized algorithm

The most important asset for today’s economy is data. A lot of businesses, organizations and governments deeply analyze their data, from sales to health, in order to gain useful insights that can be exploited to improve services or products. Indeed, we are in the so-called data-driven economy. Lots of decisions are affected by data and many automated systems don’t need any human supervision at all. As a result, having bad quality data will result in failures or unattended results in most cases. For this reason, having good data that is reliable is becoming a priority for many industries and public sectors. The aim of the thesis is to design and implement a generalized algorithm that can assess the data quality of a structured dataset following the data quality standard defined by ISO/IEC 25012 and ISO/IEC 25024. The algorithm is then exploited by assessing the quality of the Italian open government data. The assessment was conducted by considering several open datasets available in the official Italian site. The result is an analysis of the quality of the Italian open government data that highlights both strengths and weakness and suggests actions to improve the quality of the data.