Object-oriented database support for scientific data management: a system for experimentation

Abstract

Scientific data management has recently become a critical research issue due to computerization and automation of scientific research procedures and the resulting explosion of electronic data. For proper management of scientific data, adequate data types must be provided for representing the semantics of scientific data directly. Issues such as large data volume and data evolution are common among scientific applications, so traditional database support, such as storage management, are also beneficial to them. Current approaches such as standardized data formats and adoption of traditional databases do not accommodate the data support requirements of existing scientific applications well. Object-oriented databases, on the other hand, seem to hold promise, by combining flexible data models with traditional database support. In this dissertation, we constructed an experimental platform for exploring the design space for a scientific data management system. With this experimental approach, we could dynamically examine possible architectures for data support against actual instances of scientific data and typical operations executed on them. As many of the dynamic features of existing scientific applications, such as data access patterns, are yet to be discovered, the platform also provides an opportunity to explore such features. Based on the observed potential of object-oriented databases for scientific data management, the GemStone object-oriented database management system was chosen for the baseline data management architecture of the platform. Among scientific applications where better data support is desired, a scientific persistent language and data analysis environment called NewS and applications using it were selected as a target for the study. Connecting NewS with GemStone provided a cost-effective experimental platform where we could investigate a variety of scientific applications with single implementation. We incorporated GemStone into the NewS environment in such a manner that we could use existing NewS applications without modifications for experiments. We describe the design and implementation of our platform, GemStone-based NewS, and experiments performed on the platform. At the end, we describe primary contributions of the work, and assess whether or not our approach was a productive initial step toward improved scientific data management.