Uncovering Hidden Qualities - Benefits of Quality Measures for Automatically Generated Metadata

Abstract. Today, digital libraries more and more have to rely on semantic techniques during the workflows of metadata generation, search and navigational access. But, due to the statistical and/or collaborative nature of such techniques, the underlying quality of automatically generated metadata is questionable. Since data quality is essential in digital libraries, we present a user study on one hand evaluating metrics for quality assessment, on the other hand evaluating their benefit for the individual user during interaction. To observe the interaction of domain experts in the sample field of chemistry, we transferred the abstract metrics’ outcome for a sample semantic technique into three different kinds of visualizations and asked the experts to evaluate these visualizations first without, later augmented with the quality information. We show that the generated quality information is indeed not only essential for data quality assurance in the curation step of digital libraries, b...

• Type: Journal
• Year: 2010
• Where: ERCIMDL
• Authors: Sascha Tönnies, Wolf-Tilo Balke
• Keywords: Data Quality, Digital Libraries, Education, ERCIMDL 2010, Semantic Technique