The challenge of generating and evolving real-life like synthetic data when real data is not available - a systematic literature reviewTitle and Abstract Analysis and Full Text Analysis results

The objective of this Systematic Literature Review (SLR) is to identify existing approaches for creating and evolving synthetic data<br>without using real-life data. The research team consisted of four researchers. Screening, quality assessment, and data extraction were<br>conducted in pairs.<br>Our search found 1013 publications in IEEE Xplore, ACM Digital Library, and SCOPUS. We extracted data from 75 of those<br>publications and identified 37 approaches that answer our research question partly.<br>Further research is necessary to enhance the existing approaches to the point where either one or a combination of them answers<br>the full research question of this SLR.