Impact of Data Quality and Provenance

How do limitations and intransparencies in data quality and data provenance bias research outcomes, and how can we detect and mitigate these limitations? For example, we have been investigating the impact of entity resolution errors on network analysis results. We found that commonly reported network metrics and derived implications can strongly deviate from the truth—as established based on gold standard data or approximations thereof—depending on the efforts dedicated to entity resolution.