The sciences of the artificial (3rd ed.)
The sciences of the artificial (3rd ed.)
A product perspective on total data quality management
Communications of the ACM
A relational model of data for large shared data banks
Communications of the ACM
Communications of the ACM - Supporting community and building social capital
Business Dynamics
Data Quality for the Information Age
Data Quality for the Information Age
The Data Warehouse Lifecycle Toolkit: Expert Methods for Designing, Developing and Deploying Data Warehouses with CD Rom
Design Rules: The Power of Modularity Volume 1
Design Rules: The Power of Modularity Volume 1
A Framework for Analysis of Data Quality Research
IEEE Transactions on Knowledge and Data Engineering
Representing and Using Nonfunctional Requirements: A Process-Oriented Approach
IEEE Transactions on Software Engineering - Special issue on knowledge representation and reasoning in software development
Modeling Completeness versus Consistency Tradeoffs in Information Decision Contexts
IEEE Transactions on Knowledge and Data Engineering
Fundamentals of Database Systems (5th Edition)
Fundamentals of Database Systems (5th Edition)
Private Markets for Public Goods: Pricing Strategies of Online Database Vendors
Journal of Management Information Systems
Design science in information systems research
MIS Quarterly
Dual Assessment of Data Quality in Customer Databases
Journal of Data and Information Quality (JDIQ)
Optimal enterprise data architecture using publish and subscribe
Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing
Evaluating a model for cost-effective data quality management in a real-world CRM setting
Decision Support Systems
Designing business-intelligence tools with value-driven recommendations
DESRIST'10 Proceedings of the 5th international conference on Global Perspectives on Design Science Research
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Organizational data repositories are recognized as critical resources for supporting a large variety of decision tasks and for enhancing business capabilities. As investments in data resources increase, there is also a growing concern about the economic aspects of data resources. While the technical aspects of data management are well examined, the contribution of data management to economic performance is not. Current design and implementation methodologies for data management are driven primarily by technical and functional requirements, without considering the relevant economic factors sufficiently. To address this gap, this study proposes a framework for optimizing data management design and maintenance decisions. The framework assumes that certain design characteristics of data repositories and data manufacturing processes significantly affect the utility of the data resources and the costs associated with implementing them. Modeling these effects helps identify design alternatives that maximize net-benefit, defined as the difference between utility and cost. The framework for the economic assessment of design alternatives is demonstrated for the optimal design of a large data set.