I am working on the Introduction to an edited volume on the nitty-gritty behind-the-scenes work involved in empirical social science research (to be published by The University of Michigan Press in 2008). While each chapter in the book gets into considerable detail about how to approach various types of projects (from sampling online populations to interviewing hard-to-access groups, from collecting biomarkers to compiling cross-national quantitative data sets), I want to address more general issues in the introductory chapter.
One of the topics I would like to discuss concerns larger-level lessons learned after conducting such projects. The motivation behind the entire volume is that unprecedented things happen no matter the quality and detail of preparation, but even issues that can be anticipated are rarely passed along to researchers new to a type of method. The volume tries to rectify this.
I am curious, what are your biggest lessons learned? If you had to pick one or two (or three or four) things you really wish you had known before you had embarked on a project, what are they? I am happy to hear about any type of issue from learning more about a collaborator’s qualifications or interests, to leaving more time for cleaning data, from type of back-up method to unprecedented issues with respondents. If you don’t feel comfortable posting here, please email me off-blog. Thanks!