Reconciling while tolerating disagreement in collaborative data sharing

In many data sharing settings, such as within the biological and biomedical communities, global data consistency is not always attainable: different sites' data may be dirty, uncertain, or even controversial. Collaborators are willing to share their data, and in many cases they also want to selectively import data from others -- but must occasionally diverge when they disagree about uncertain or controversial facts or values. For this reason, traditional data sharing and data integration approaches are not applicable, since they require a globally consistent data instance. Additionally, many of these approaches do not allow participants to make updates; if they do, concurrency control algorithms or inconsistency repair techniques must be used to ensure a consistent view of the data for all users. In this paper, we develop and present a fully decentralized model of collaborative data sharing, in which participants publish their data on an ad hoc basis and simultaneously reconcile ...

• Type: Conference
• Year: 2006
• Where: SIGMOD
• Authors: Nicholas E. Taylor, Zachary G. Ives
• Keywords: Collaborative Data Sharing, Consistent Data Instance, Data Sharing Settings, Database, SIGMOD 2006