A Non-prescriptive Environment to Scaffold High Quality and Privacy-aware Production of Open Data with AI
Giuseppe Ferretti, Delfina Malandrino, Maria Angela Pellegrino, Donato Pirozzi, Gianluigi De Renzi, Vittorio Scarano · 2019
Data quality is strictly related to fitness for use. Therefore, data providers should improve the intrinsic quality of published data to prevent the diffusion of data sets practically impossible to use. Among all data providers, it is critical that governments and public agencies better assess and improve the quality of the produced data sets as early as possible - ideally during the production phase. Besides the quality aspect, data providers should also bear in mind that if they want to expose personal information, data must be compliant with EU General Data Protection Regulation (GDPR).