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Digital Health Data Quality Issues: Systematic Review
Abstract Background: The promise of digital health is principally dependent on the ability to electronically capture data that can be analyzed to improve decision-making. However, the ability to effectively harness data has proven elusive, largely because of the quality of the data captured. Despite the importance of data quality (DQ), an agreed-upon DQ taxonomy evades…
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Process Activity Ontology Learning From Event Logs through Gamification
Abstract Process mining is concerned with deriving knowledge from process data as recorded in so-called event logs. The quality of event logs is a constraining factor in achieving reliable insights. Particular quality problems are posed by activity labels which are meant to be representative of organisational activities, but may take different manifestations (e.g. as a…