The role of process metadata and data quality perceptions in decision making: an empirical framework and investigation

The quality of the data used in decision-making tasks has important implications for the outcome of these tasks.
Data quality researchers have defined various dimensions for measuring data quality, such as accuracy, currency, and completeness. Such measurements are intrinsic to the data itself and do not take into account contextual factors related to the decision-maker or the decision-task. However, recent research suggests that data quality, when assessed by the decisionmakers who use it, is not necessarily perceived as intrinsic, but as subjective and context-dependent. This research investigates the provision of process metadata - an abstracted description of how datasets are acquired, processed, stored, and delivered – as a mechanism that affects the end-user’s assessment of data quality. In this study we develop a model for understanding the associations of both perceptions of intrinsic data quality and process metadata with the outcome of a datadriven decision task. An exploratory test of the model suggests that both data quality perceptions and the associated process metadata have beneficial effects on outcomes, when mediated by decision-making process efficiency. The model developed in this study and the preliminary empirical results highlight the value of embedding quality and process metadata in computer-supported decision environments to facilitate assessment of data quality.