We present the QUery-driven Exploration of Semistructured data and meta-data with conflicTs and partial knowledge (QUEST) system for supporting the integration of scientific data and taxonomies in the presence of misalignments and conflicts. QUEST relies on a novel constraint-based data model that captures both value and structural conflicts and enables researchers to observe and resolve such misalignments in the integrated data by considering the context provided by the data requirements of given research questions.
Integrating and Querying Taxonomies with Quest in the presence of Conflicts
SAPINO, Maria Luisa;
2007-01-01
Abstract
We present the QUery-driven Exploration of Semistructured data and meta-data with conflicTs and partial knowledge (QUEST) system for supporting the integration of scientific data and taxonomies in the presence of misalignments and conflicts. QUEST relies on a novel constraint-based data model that captures both value and structural conflicts and enables researchers to observe and resolve such misalignments in the integrated data by considering the context provided by the data requirements of given research questions.
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