LinkWinds: interactive scientific data analysis and visualization
Communications of the ACM
Object management architecture guide (3rd ed.)
Object management architecture guide (3rd ed.)
Volcano— An Extensible and Parallel Query Evaluation System
IEEE Transactions on Knowledge and Data Engineering
ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
OASIS: An Open Architecture Scientific Information System
RIDE '96 Proceedings of the 6th International Workshop on Research Issues in Data Engineering (RIDE '96) Interoperability of Nontraditional Database Systems
On Heterogeneous Distributed Geoscientific Query Processing
RIDE '96 Proceedings of the 6th International Workshop on Research Issues in Data Engineering (RIDE '96) Interoperability of Nontraditional Database Systems
Techniques and Experience in Mining RemotelySensed Satellite Data
Artificial Intelligence Review - Issues on the application of data mining
For Scientific Data Discovery: Why Can't the Archive be More Like the Web?
SSDBM '97 Proceedings of the Ninth International Conference on Scientific and Statistical Database Management
A bibliography of temporal, spatial and spatio-temporal data mining research
ACM SIGKDD Explorations Newsletter
Towards an open architecture for vector GIS
Computers & Geosciences
| Hi-index | 0.00 |
Oasis is a flexible, extensible, and seamless environment for scientific data analysis, knowledge discovery, visualization, and collaboration. The authors describe how Oasis can help explore data analysis and data mining of spatio-temporal phenomena from large geophysical data sets.Exploratory data mining and analysis for scientific hypothesis testing or phenomenon detection is an iterative, successive-refinement process. Scientists apply a preliminary model on the data and then use the outcome of a series of experiments to refine the model and methodology. They repeat this process until they either drop the hypothesis or refine it into one that is consistent with the collected data.For such a research approach to be practical, scientists need a powerful system that supportseasy formulation and execution of powerful queries and discriminant functions against the database,a natural representation of the relationships of the scientific domain of interest (for example, in the natural domains of space and time but possibly in the frequency domain, as well), andefficient execution of these queries without requiring the scientists to be aware of the storage structures and processing strategies involved.We are developing Oasis (open architecture scientific information system) to be such a system. In this article, we explain how scientists can use this flexible, extensible, and seamless computing environment for scientific data analysis, knowledge discovery, visualization, and collaboration.