Unlike the world wide web or general libraries, digital libraries typically serve a specialized community of experts sharing a relatively narrow focus, such as some aspect of law, science, technology, or business. Moreover, these experts are not casual users; they have stringent. information requirements. For these reasons, digital libraries increasingly invest in sophisticated methods for indexing and retrieving their information assets. The goal of this project is to develop and test a method of knowledge-based information retrieval, in which a request for information is posed as a question, and information sources are identified that pertain to steps in the logical process of answering the question. We aim to develop this technology by leveraging our results from fifteen years of research on building knowledge bases and developing automated methods for using them to answer questions. Vv'hile our previous research required extensive knowledge bases that are costly to build and maintain, our current research will significantly reduce this requirement with a novel combination of symbolic reasoning and more conventional information retrieval. To evaluate our results, we plan to build an information retrieval system for the wide variety of users needing information on the effects of global climate change, and to measure its success compared with human experts and conventional systems. This paper introduces knowledge-based.information retrieval. While our work on an integrated system is preliminary, the components of our solution (an extensive knowledge base and methods of using it to answer questions) are well developed.