Data administration: a practical guide to successful data management
Data administration: a practical guide to successful data management
Data architecture: the information paradigm (2nd ed.)
Data architecture: the information paradigm (2nd ed.)
DoD legacy systems: reverse engineering data requirements
Communications of the ACM
An approach for reverse engineering of relational databases
Communications of the ACM
Relational database: a practical foundation for productivity
Communications of the ACM
Data Model Patterns: Conventions of Thought
Data Model Patterns: Conventions of Thought
Reverse Engineering and Design Recovery: A Taxonomy
IEEE Software
Observed idiosyncracies of relational database designs
WCRE '95 Proceedings of the Second Working Conference on Reverse Engineering
Dimensions of Data ase Reverse Engineering
WCRE '97 Proceedings of the Fourth Working Conference on Reverse Engineering (WCRE '97)
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
Extracting entity-relationship diagram from a table-based legacy database
Journal of Systems and Software
Towards a Modernization Process for Secure Data Warehouses
DaWaK '09 Proceedings of the 11th International Conference on Data Warehousing and Knowledge Discovery
KBB: a knowledge-bundle builder for research studies
ER'10 Proceedings of the 2010 international conference on Advances in conceptual modeling: applications and challenges
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Data reverse engineering (DRE) is a relatively new approach used to address a general category of data disintegration problems. DRE combines structured data analysis techniques with rigorous data management practices. The approach is growing in popularity as an integrative systems re-engineering method because of its ability to address multiple problem types concurrently. This paper describes a general DRE template both as an activity model and as a data model to be populated with reverse engineered data. Scenarios show how DRE has been used to (1) harness data assets to address organizational data integration problems, (2) develop organizational data migration strategies, (3) specify distributed systems architectures, and (4) implement and propagate organizational CASE-tool usage to address system maintenance problems. Selectively applied DRE can be an important first step toward eventual organization-wide data integration.