IoT Data Quality Assurance Framework for Reliable Process Analytics

Abstract

Data quality is a major concern in all data analysis tasks. In IoT-enhanced business processes, data quality issues often arise from faulty sensor measurements, which are propagated through event abstraction to incorrect process decisions. In this paper, we investigate the main challenges in data quality management for IoT-enhanced business processes and isolate four subchallenges. Each subchallenge is first defined and put in perspective with relevant literature and representative real-world use cases before we present five overarching opportunities to address the subchallenges. Finally, we conclude the paper with a research agenda, making recommendations over multiple time horizons to improve data quality management in IoT-enhanced business processes.