Plans and situated actions: the problem of human-machine communication
Plans and situated actions: the problem of human-machine communication
A scientific methodology for MIS case studies
MIS Quarterly
The relational model for database management: version 2
The relational model for database management: version 2
Unified theories of cognition
WITS '92 Selected papers of the workshop on Information technologies and systems
Anchoring data quality dimensions in ontological foundations
Communications of the ACM
Communications of the ACM
Quality information and knowledge
Quality information and knowledge
Dynamic memory revisited
Conducting action research: high risk and high reward in theory and practice
Qualitative research in IS
Communications of the ACM - Supporting community and building social capital
Innovation Explosion: Using Intellect and Software to Revolutionize Growth Strategies
Innovation Explosion: Using Intellect and Software to Revolutionize Growth Strategies
Database Systems: Design, Implementation, and Management
Database Systems: Design, Implementation, and Management
AIMQ: a methodology for information quality assessment
Information and Management
Human Problem Solving
Natural language access to multiple databases: a model and a prototype
Journal of Management Information Systems - Special section: Toward a theory of business process change management
Journal of Management Information Systems - Special section: Navigation in information-intensive environments
Learning to specify information requirements: the relationship between application and methodology
Journal of Management Information Systems - Special section: Strategic and competitive information systems
Knowing-Why About Data Processes and Data Quality
Journal of Management Information Systems
VLDB '81 Proceedings of the seventh international conference on Very Large Data Bases - Volume 7
Information Technology Competence of Business Managers: A Definition and Research Model
Journal of Management Information Systems
Toward a Theory of Knowledge Reuse: Types of Knowledge Reuse Situations and Factors in Reuse Success
Journal of Management Information Systems
Learning to Implement Enterprise Systems: An Exploratory Study of the Dialectics of Change
Journal of Management Information Systems
Journal of Management Information Systems
Genre Combinations: A Window into Dynamic Communication Practices
Journal of Management Information Systems
Overview and Framework for Data and Information Quality Research
Journal of Data and Information Quality (JDIQ)
An object-oriented framework for data quality management of enterprise data warehouse
PRICAI'06 Proceedings of the 9th Pacific Rim international conference on Artificial intelligence
Information Asymmetry in Information Systems Consulting: Toward a Theory of Relationship Constraints
Journal of Management Information Systems
Improving financial data quality using ontologies
Decision Support Systems
Information Asymmetry in Information Systems Consulting: Toward a Theory of Relationship Constraints
Journal of Management Information Systems
Normal accidents: Data quality problems in ERP-enabled manufacturing
Journal of Data and Information Quality (JDIQ)
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Motivated by the growing importance of data quality in data-intensive, global business environments and by burgeoning data quality activities, this study builds a conceptual model of data quality problem solving. The study analyzes data quality activities at five organizations via a five-year longitudinal study. The study finds that experienced practitioners solve data quality problems by reflecting on and explicating knowledge about contexts embedded in, or missing from, data. Specifically, these individuals investigate how data problems are framed, analyzed, and resolved throughout the entire information discourse. Their discourse on contexts of data, therefore, connects otherwise separately managed data processes, that is, collection, storage, and use. Practitioners' context-reflective mode of problem solving plays a pivotal role in crafting data quality rules. These practitioners break old rules and revise actionable dominant logic embedded in work routines as a strategy for crafting rules in data quality problem solving.