Towards a semantic & domain-agnostic scientific data management system

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 we present PODD, an ontology-centric data management system architecture for scientific experimental data that is extensible and domain independent. In this architecture, the behaviors of domain concepts and objects are specified entirely by ontological entities, around which all data management tasks are carried out. The open and semantic nature of ontology languages also makes PODD amenable to greater data reuse and interoperability. To evaluate this architecture, we have developed a data management system and applied it to the challenge of managing phenomics data.