{What is a Negative Result?} In a sense, well-designed experiments never have a completely negative result, since there is always the opportunity to learn something. In fact, unexpected results by definition provide the most information. Conventionally, negative results refer to those that do not support the hypothesis that an experiment has been designed to test; that is, results that are unable to disprove the null hypothesis (e.g., that the distinction between results from novel and baseline approaches can be explained by chance variability). Such a result can certainly be due to many causes, including bugs, and does not by itself confirm any hypothesis. However, learning about negative as well as positive results can be instrumental in providing the context for the development of new hypotheses to be tested. Hearing only about the successes is equivalent to throwing away half of the information. Personally, we have often been more intrigued with reports of significant unexpected failures than with the usual reports of method A being 5\% better than baseline method B. Such reports often provide little surprise at all. We hope that the new journal will provide a forum for experimenters who have unexpected results from well-designed experiments.