A metadata system for information modeling and integration
ISCI '90 Proceedings of the first international conference on systems integration on Systems integration '90
Information Resources Management in Heterogeneous, Distributed Environments: A Metadatabase Approach
IEEE Transactions on Software Engineering
The metadatabase project at Rensselaer
ACM SIGMOD Record
The model-assisted global query system for multiple databases in distributed enterprises
ACM Transactions on Information Systems (TOIS)
Maintaining data warehouses over changing information sources
Communications of the ACM
Enterprise Integration and Modeling: The Metadatabase Approach
Enterprise Integration and Modeling: The Metadatabase Approach
Expert versus novice use of the executive support systems: an empirical study
Information and Management
TSER: A Data Modeling System Using the Two-Stage Entity-Relationship Approach
Proceedings of the Sixth International Conference on Entity-Relationship Approach
A metadatabase-enabled executive information system (part A): a flexible and adaptable architecture
Decision Support Systems
A metadatabase-enabled executive information system (part A): a flexible and adaptable architecture
Decision Support Systems
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In tandem with the growth of the Internet and e-business, the number of digital data sources has increased immensely. These data sources contain important transactional data and are generally interconnected via a network. This has created a pressing need for a suitable executive information system (EIS) that is capable of extracting data from internal and external data sources and providing data analysis on demand for business executives. On-demand data analysis requires an information integration approach that can manage rapid changes in data sources. Existing EISs commonly adopt data warehousing technology to consolidate data from multiple sources in a tailor-made fashion, and support predefined multidimensional data analysis. However, this architecture is neither adaptable to changes in local sources nor flexible enough for ad hoc analyses. This paper develops methods and algorithms for a new EIS architecture that takes advantage of a metadatabase to achieve adaptability and flexibility. A PC-based prototype is built to prove the concept.