Semantic Web Data Quality Control

Data quality is a growing concern on the Semantic Web. The amount of data available is growing faster than ever, and the emphasis thus far has been on creating and interlinking data without much regard to how good the data actually is. The trend is shifting from creating new data to refining what already exists.
Data quality is a subjective concept and a formal representation for it is often troublesome. First, we must define what is meant by data quality - what are the different facets of the concept. Second, a way for representing this quality must be found. Third, actual processes to refine data and improve its quality and ways to take data quality into account on the Semantic Web must be developed.
This work presents some solutions to the problem. Many ways to annotate quality metadata as RDF are first discovered, along with their pros and cons. A framework for managing RDF-based quality metadata is presented, with a set of tools for specifically managing the quality annotations. Additionally, an automatic annotation system and a schema validation system, within the restraints of the open world assumption, have been designed, implemented and integrated into the framework. The system has been tested using real life datasets with promising first results.