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Challenging issues for processing queries specified over large-scale information spaces (e.g. digital libraries or the World Wide Web) include the diversity of the information sources (ISs) in terms of their structures, query interfaces, as well as the dynamics of ISs continuously being added, removed or upgraded. Typically user queries are loosely specified expressing what the user wants but not how and from where the information is to be retrieved. In this paper we give an innovative solution for semantical query planning in such environments. The key idea underlying our solution is the notion of connected query rules defined to be precisely specified, executable queries that are semantically equivalent to a user query. For query planning in such a large-scale space, we introduce DIIM-the Dynamic Information Integration Model which supports the description of not only content but also capabilities of ISs, e.g., query templates of and interrelationships between ISs. This then lays the foundation for the translation algorithm that based on the connected query rule principle maps a loosely-specified query into the set of semantically equivalent queries.