An asynchronous collaborative reconciliation model based on data provenance. (13th June 2017) - de Almeida, Dayse Silveira; Hara, Carmem Satie; Ciferri, Ricardo Rodrigues; de Aguiar Ciferri, Cristina Dutra
Summary: Reconciliation is the process of providing a consistent view of the data imported from different sources. Despite some efforts reported in the literature for providing data reconciliation solutions with asynchronous collaboration, the challenge of reconciling data when multiple users work asynchronously over local copies of the same imported data has received less attention. In this paper, we propose AcCORD, an asynchronous collaborative data reconciliation model based on data provenance. AcCORD is innovative because it supports applications in which all users are required to agree on the data values to provide a single consistent view to all of them, as well as applications that allow users to disagree on the data values to keep in their local copies but promote collaboration by sharing integration decisions. We also introduce a decision integration propagation method that keeps users from taking inconsistent decisions over data items present in several sources. Further, different policies based on data provenance are proposed for solving conflicts among multiusers' integration decisions. Our experimental analysis shows that AcCORD is efficient and effective. It performs well, and the results highlight its flexibility by generating either a single integrated view or different local views. We have also conducted interviews with end users to analyze the proposed policies and feasibility of the multiuser reconciliation. They provide insights with respect to acceptability, consistency, correctness, time‐saving, and satisfaction. Copyright © 2017 John Wiley & Sons, Ltd.