Automated Information Extraction from Empirical Software Engineering Literature: Is that possible?

The number of scientific publications is constantly increasing, and the results published on empirical software engineering are growing even faster. Some software engineering publishers have begun to collaborate with research groups to make available repositories of software engineering empirical data. However, these initiatives are limited due to data ownership and privacy issues. As a result, many researchers in the area have adopted systematic reviews as a mean to extract empirical evidence from published material. Systematic reviews are labor intensive and costly. In this paper, we argue that the use of information extraction tools can support systematic reviews and significantly speed up the creation of repositories of SE empirical evidence.