An important reality when integrating scientific data is the fact that data may often be "missing", partially specified, or conflicting. Therefore, in this paper, we present an assertion-based data model that captures both value-based and structure-based "nulls" in data. We also introduce the QUEST system, which leverages the proposed model for Query-driven Exploration of Semistructured data with conflicT s and partial knowledge. Our approach to integration lies in enabling researchers to

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... e and resolve conflicts in the data by considering the context provided by the data requirements of a given research question. In particular, we discuss how pathcompatibility can be leveraged, within the context of a query, to develop a high-level understanding of conflicts and nulls in data.