DQM-Vocabulary Primer

Contents 1 Purpose and Usage of the DQM-Vocabulary 2 Quick Start 2.1 Create Data Requirements 2.2 Generate Problem and Score Annotations 2.3 Generate Problem Reports 2.4 Generate Data Quality Score Reports 3 Examples 4 Querying the DQM-Vocabulary

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

Quick Start

Create Data Requirements

Generate Problem and Score Annotations

Generate Problem Reports

Generate Data Quality Score Reports

Examples

• Creating Data Requirements
• Usage of DQM-Vocab as OWL DL or OWL Full

Querying the DQM-Vocabulary

• Data Quality Monitoring Reports
• Data Quality Assessment Reports