This paper describes techniques for building and exploiting indexes on semistructured data: data that may not have a fixed schema and that may be irregular or incomplete. We first present a general framework for indexing values in the presence of automatic type coercion. Then based on Lore, a DBMS for semistructured data, we introduce four types of indexes and illustrate how they are used during query processing. Our techniques and indexing structures are fully implemented and integrated into the Lore prototype. 1 Introduction We call data that is irregular or that exhibits type and structural heterogeneity semistructured, since it may not conform to a rigid, predefined schema. Such data arises frequently on the Web, or when integrating information from heterogeneous sources. In general, semistructured data can be neither stored nor queried in relational or object-oriented database management systems easily and efficiently. We are developing Lore 1 , a database management system d...