Experiment explorer: lightweight provenance search over metadata
TaPP'12 Proceedings of the 4th USENIX conference on Theory and Practice of Provenance
An ontology-centric architecture for extensible scientific data management systems
Future Generation Computer Systems
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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 data combined with data models that evolve over time 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 architecture for data management systems that is extensible and domain independent. In this architecture, the behaviors of domain concepts and objects are captured 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 the PODD architecture, we have applied it to the challenge of managing phenomics data.