Measuring and improving data quality of media collections for professional tasks

Carrying out research tasks on data collections is hampered, or even made impossible, by data quality issues of different types, such as incompleteness or inconsistency, and severity. We identify research tasks carried out by professional users of data collections that are hampered by inherent quality issues. We investigate what types of issues exist and how they influence these research tasks. To measure the quality perceived by professional users, we develop a quality metric. This allows us to measure the suitability of the data quality for a chosen user task. For a chosen task, we study how the data quality can be improved using crowdsourcing. We validate our quality metric by investigating whether professionals perform better on the chosen research task.