The Quality in Databases (QDB) workshop is a qualified forum for presenting and discussing novel ideas and solutions related to the problems of exploring, assessing, monitoring, improving, and maintaining the quality of data. Specific topics include, but are not limited to, the following:

- Duplicate detection, entity resolution, and entity reconciliation
- Conflict resolution and data fusion
- Data quality models and algebra
- Quality of Linked Data
- Cleaning extremely large datasets
- Data Quality on the Web
- Privacy-preserving data quality
- Data quality benchmarks
- Data Quality on novel data management architectures (cloud, streaming data, ...)
- General techniques applicable across many domains with measurable improvements on specific domains.
- State of the art, recent progress, and prospects for the future in data quality.
- Data scrubbing, data standardization, data cleaning techniques
- Quality-aware query languages and query processing techniques
- Quality-aware analytics solutions
- Data quality in data integration settings
- Role of metadata in quality measurement
- Data quality mining
- Quality of scientific, geographical, and multimedia databases
- Data quality assessment, measures and improvement methodologies

Depending on the number and quality of submissions, the best papers of the workshop may be recommended for a special issue in the Information Systems Journal.