Empirical evaluation of dependability is a complement to modeling and analytical methods. Although empirical evaluation applies to real systems and is more realistic, more accurate, and provides a higher level of confidence, it is not extensively used, for multiple reasons: it is time and effort consuming; the results have limited portability; there are no benchmarks to define what measures to be collected, how to measure the data, how to report it, what are the models that indicate the ranges of "good" and "bad" values, and how to compare the values for different systems. Due to these challenges, very few results and empirical data are available for dependability evaluation, comparison, and benchmarking. Acknowledging these challenges, but also the need for empirical dependability evaluation, this workshop will bring together researchers and practitioners for sharing their solutions and results, as well as for documenting their needs, problems, and ideas with respect to this topic. The workshop will include presentations and a hands-on session where participants will work on finding solutions to pre-selected questions.