Aggregation of Empirical Evidence
One of the most important challenges in empirical software engineering today is to better integrate empirical studies with decision support, and to collect appropriate data and experiments. The required steps are to identify the information needed, to collect appropriate studies, and to (objectively) aggregate (i.e., summarize) their results. To be able to make informed decisions on introducing, changing, or evolving technologies and processes in practice as well as research, these decisions have to be based on aggregated trustable (i.e., corroborated) evidence and statements. The benefits of such an approach include reducing the risk of introducing / changing technologies (from industrial point of view), and that it is possible to identify evidence gaps (from research point of view).