Selecting Experts Using Data Quality Concepts

Personal networks are not always diverse or large enough to reach those with the right information. This problem increases when assembling a group of experts from around the world, something which is a challenge in Future-oriented Technology Analysis (FTA). In this work, we address the formation of a panel of experts, specifically how to select a group of experts from a huge group of people. We propose an approach which uses data quality dimensions to improve expert selection quality and provide quality metrics to the forecaster. We performed a case study and successfully showed that it is possible to use data quality methods to support the expert search process.