The number of potentially-related data resources available for querying -- databases, data warehouses, virtual integrated schemas -continues to grow rapidly. Perhaps no area has seen this problem as acutely as the life sciences, where hundreds of large, complex, interlinked data resources are available on fields like proteomics, genomics, disease studies, and pharmacology. The schemas of individual databases are often large on their own, but users also need to pose queries across multiple sources, exploiting foreign keys and schema mappings. Since the users are not experts, they typically rely on the existence of pre-defined Web forms and associated query templates, developed by programmers to meet the particular scientists' needs. Unfortunately, such forms are scarce commodities, often limited to a single database, and mismatched with biologists' information needs that are often context-sensitive and span multiple databases. We present a system with which a non-expert user ...