A consensus glossary of temporal database concepts
ACM SIGMOD Record
On-line warehouse view maintenance
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Version models for software configuration management
ACM Computing Surveys (CSUR)
A Layered Architecture for Uniform Version Management
IEEE Transactions on Software Engineering
Historical Multi-Media Databases
VLDB '86 Proceedings of the 12th International Conference on Very Large Data Bases
Versions of Schema for Object-Oriented Databases
VLDB '88 Proceedings of the 14th International Conference on Very Large Data Bases
On Schema Versioning in Temporal Databases
Proceedings of the International Workshop on Temporal Databases: Recent Advances in Temporal Databases
ODMG Language Extensions for Generalised Schema Versioning Support
ER '99 Proceedings of the Workshops on Evolution and Change in Data Management, Reverse Engineering in Information Systems, and the World Wide Web and Conceptual Modeling
Concurrent Warehouse Maintenance Without Compromising Session Consistency
DEXA '98 Proceedings of the 9th International Conference on Database and Expert Systems Applications
A Generalized Modeling Framework for Schema Versioning Support
ADC '00 Proceedings of the Australasian Database Conference
An introduction to schema versioning in OODBMS
DEXA '96 Proceedings of the 7th International Workshop on Database and Expert Systems Applications
Concurrent Maintenance of Views Using Multiple Versions
IDEAS '99 Proceedings of the 1999 International Symposium on Database Engineering & Applications
Exploiting versions for on-line data warehouse maintenance in MOLAP servers
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
| Hi-index | 0.00 |
Data warehouses integrate information from several data sources. Their main goal is to offer an efficient access to data sets and to enable users to make better and faster decisions. In this work, we present our proposition for the management, storage and visualization of a data warehouse (current and historical) in a medical environment using bitemporal schema versions. Changes in data sources concern either data or schema and must be propagated to the warehouse in order to have updated information. This process generates a maintenance transaction. Most research works use the version approach to keep information consistent according to its schema when a maintenance transaction is executed. In a medical context it is essential to manipulate current and historical data. However, we must consider the huge quantity of medical data and propose a mechanism for handling the data sets in an evolving environment. Our version model is placed above the database management system and is completely orthogonal to the DBMS data model.