Synthetic Data in a Data-Intensive World: A Literature Review to Address an Application-Driven Analysis

Synthetic data are increasing their popularity in different disciplines. Indeed, in addition to their affordability, synthetic data may play an effective protective role to address privacy issues, which are extremely critical in certain application domains such as healthcare, as well as they represent a relatively simple solution to overcome access restrictions. However, despite synthetic data are not a novelty and their potentialities in the different domains have been largely discussed, their operationalization and utility are still object of research. More recently, the unprecedented AI capabilities have naturally enabled and quickly consolidated a feedback loop, where synthetic data is, at the same time, a valuable resource to further develop and refine technology, as well as an added, often critical, value within the different application domains. By combining hybrid retrieval and analysis techniques, 250+ relevant papers have been selected, classified and analyzed. In a context of discussion about legal, ethical and political implications amid opportunities and challenges, the review has clearly pointed out a need for a more consolidated engineering approach to synthetic data as a response to the intrinsic complexity of applications in the current technological climate.