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Data management has become a critical challenge faced by a wide array of scientific disciplines in which the provision of sound data management is pivotal to the achievements and impact of research projects. Massive and rapidly expanding amounts of experimental data combined with evolving domain models contribute to making data management an increasingly challenging task that warrants a rethinking of its design. In this paper, the authors present PODD, an ontology-centric data management system architecture for scientific experimental data that is extensible and domain independent.
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