Computer as Thinker/Doer: Problem-Solving Environments for Computational Science
IEEE Computational Science & Engineering
Web-based development of complex information products
Communications of the ACM
From Scientific Software Libraries to Problem-Solving Environments
IEEE Computational Science & Engineering
Of Objects and Databases: A Decade of Turmoil
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
A Collaborative Informatics Infrastructure for Multi-Scale Science
Cluster Computing
ICCS'03 Proceedings of the 2003 international conference on Computational science
Hi-index | 0.00 |
Next-generation problem-solving environments (PSEs) promise significant advances over those now available. They will span scientific disciplines and incorporate collaboration capabilities. They will host feature-detection and other agents, allow data mining and pedigree tracking, and provide access from a wide range of devices. Fundamental changes in PSE architecture are required to realize these and other PSE goals. This paper focuses specifically on issues related to data management and recommends an approach based on open, metadata-driven repositories with loosely defined, dynamic schemas. Benefits of this approach are discussed, and the redesign of the Extensible Computational Chemistry Environment's (Ecce) data storage architecture to use such a repository is described, based on the distributed authoring and versioning (DAV) standard. The suitability of DAV for scientific data, the mapping of the Ecce schema to DAV, and promising initial results are presented.