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Views over probabilistic data contain correlations between tuples, and the current approach is to capture these correlations using explicit lineage. In this paper we propose an alternative approach to materializing probabilistic views, by giving conditions under which a view can be represented by a block-independent disjoint (BID) table. Not all views can be represented as BID tables and so we propose a novel partial representation that can represent all views but may not define a unique probability distribution. We then give conditions on when a query's value on a partial representation will be uniquely defined. We apply our theory to two applications: query processing using views and information exchange using views. In query processing on probabilistic data, we can ignore the lineage and use materialized views to more efficiently answer queries. By contrast, if the view has explicit lineage, the query evaluation must reprocess the lineage to compute the query resulting in dramatically slower execution. The second application is information exchange when we do not wish to disclose the entire lineage, which otherwise may result in shipping the entire database. The paper contains several theoretical results that completely solve the problem of deciding whether a conjunctive view can be represented as a BID and whether a query on a partial representation is uniquely determined. We validate our approach experimentally showing that representable views exist in real and synthetic workloads and show over three magnitudes of improvement in query processing versus a lineage based approach.