The problem of analyzing and classifying conceptual schemas is becomig increasingly important due to the availability of a large number of schemas related to existing applications. The purposes of schema analysis and classification activities can be different: to extract information on intensional properties of legacy systems in order to restructure or migrate to new architectures; to build libraries of reference conceptual components to be used in building new applications in a given domain; and to identify information flows and possible replication of data in an organization. This article proposes a set of techniques for schema analysis and classification to be used separately or in combination. The techniques allow the analyst to derive significant properties from schemas, with human intervention limited as far as possible. In particular, techniques for associating descriptors with schemas, for abstracting reference conceptual schemas based on schema clustering, and for determining schema similarity are presented. A methodology for systematic schema analysis is illustrated, with the purpose of identifying and abstracting into reference components the similar and potentially reusable parts of a set of schemas. Experiences deriving from the application of the proposed techniques and methodology on a large set of Entity-Relationship conceptual schemas of information systems in the Italian Public Administration domain are described