Implications of data quality for spreadsheet analysis
ACM SIGMIS Database
Methodology for allocating resources for data quality enhancement
Communications of the ACM
Not all answers are equally good: estimating the quality of database answers
Flexible query answering systems
Communications of the ACM - Supporting community and building social capital
Information Systems Development: Methodologies, Techniques, and Tools
Information Systems Development: Methodologies, Techniques, and Tools
AIMQ: a methodology for information quality assessment
Information and Management
Completeness of integrated information sources
Information Systems - Special issue: Data quality in cooperative information systems
Sample-Based Quality Estimation of Query Results in Relational Database Environments
IEEE Transactions on Knowledge and Data Engineering
Beyond accuracy: what data quality means to data consumers
Journal of Management Information Systems
Economics-Driven Data Management: An Application to the Design of Tabular Data Sets
IEEE Transactions on Knowledge and Data Engineering
Brokering infrastructure for minimum cost data procurement based on quality-quantity models
Decision Support Systems
GIGO or not GIGO: The Accuracy of Multi-Criteria Satisficing Decisions
Journal of Data and Information Quality (JDIQ)
Knowledge-based scenario management - Process and support
Decision Support Systems
GIGO or not GIGO: The Accuracy of Multi-Criteria Satisficing Decisions
Journal of Data and Information Quality (JDIQ)
Determining the relative accuracy of attributes
Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data
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This study introduces a mathematical-statistical theory that illustrates the effect of input errors on the accuracy of dichotomous decisions which are implemented through logical conjunction and disjunction of selected criteria. Decision-making instances in this category are often labeled ''satisficing.'' Mainly, our theory provides criteria for ranking the effect of errors in different inputs on decision accuracy. This ranking can be used to improve the efficiency and effectiveness of resource allocation decisions in data quality management settings. All other things being equal, inputs in which errors exhibit a higher negative effect on the output would naturally earn higher priority.