DQM-Vocabulary Primer

Contents 1 Purpose and Usage of the DQM-Vocabulary 2 Expressing Your Own Data Requirements 3 Consuming DQM-Vocabulary Data 4 Data Quality Knowledge Management 5 Data Quality Management Vocabulary 6 See also 7 References

Purpose and Usage of the DQM-Vocabulary

The DQM-Vocabulary was created to support Data Quality management acitivities in Semantic Web architectures. It's major stregth is the ability to represent Data Requirements, i.e. quality-relevant expectations on data, so that computers can interpret the requirements and take further actions. Among other things, the DQM-Vocabulary enables the following core-features:

• Automated creation of problem reports and Data Quality scores based on Data Requirements
• Automated consistency checks between Data Requirements
• Exchange of Data Quality information and Data Requirements on web-scale

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Expressing Your Own Data Requirements

• Create Data Requirements
• Requirement Metadata

Consuming DQM-Vocabulary Data

• Data Quality Monitoring Reports
• Data Quality Assessment Reports

Data Quality Knowledge Management

• Generate Problem Annotations
• Generate Score Annotations
• Data Requirements Consistency Checks

Data Quality Management Vocabulary

• Latest Technical Specification of DQM-Vocabulary
• Latest DQM-Vocabulary in OWL

See also

• What is Data Quality?
• Data Requirements
• Quality Perception in Information Systems

References

Fürber, Christian and Hepp, Martin: Towards a Vocabulary for Data Quality Management in Semantic Web Architectures, Proceedings of the 1st International Workshop on Linked Web Data Management (LWDM2011), Uppsala, Sweden, March 25, 2011.