Towards a semantic & domain-agnostic scientific data management system
Yuan-Fang Li, Philippe Cudré-Mauroux, Gavin C. Kennedy, Brian Parsia, Faith E. Davies, Jane Hunter · International Semantic Web Conference · 2010
Data management has become a critical challenge faced by a wide array of scientic 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 man- agement 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 scientic experimental data that is extensible and domain independent. In this architecture, the behaviors of domain concepts and objects are specied entirely by ontological enti- ties, 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.