Abstract: The growth in the past decade of both the infrastructure and the number of users of the Internet has enabled a corresponding growth in the number of users of digital reference services on the Internet. This increase has led to an increase in the number of questions received by these services, putting a strain on the human intermediaries employed therein. The ability of a digital reference service to 'scale up' to handle an increasingly large number of questions is directly affected by the amount of automation employed by that service: the more processes that are automated, the more of human intermediaries' time and effort can be dedicated to tasks that cannot yet be automated. There is, now more than ever, an increased and immediate need in digital reference for automation. This study identifies (1) the types of questions that are received by digital reference services, according to several taxonomies of questions at different levels of linguistic analysis, and (2) the rules by which questions are triaged within and between services (triage being the process of routing and assigning questions to expert digital reference question answerers and other services). Taxonomies of questions are identified though an extensive review of literature that deals with questions, from several fields: desk and digital reference, question answering, and linguistics. The rules by which questions are triaged are identified through a think-aloud study of digital reference triagers performing the task of triage. The goal of this study is to develop specifications according to which an automated triage system can be built. These specifications will take into account the question type, as well as other attributes of questions that affect triage decisions. These taxonomies of questions may also prove to be useful as the basis for algorithms for automating other steps in the digital reference process.