DataWarp: Empowering Applications to Make Progress in the Face of Contradictory or Inconsistent Data

In modern systems data is distributed and replicated. Its ownership is also distributed amongst a variety of stakeholders with differing requirements and expectations. A consequence is applications inevitably find data they need is missing or contains contradictions and inconsistencies from time to time leaving them unable to progress within their domain. Techniques such as transactions can help but are not enough as they rely on being able to impose their own consistency rules on data and this isn´t always possible. What is required is an ability for applications to move forward despite the problems in local data by applying higher-level reasoning to that data. This paper describes DataWarp, a technique which empowers applications to make progress in such environments and illustrates its use to specify an efficient personal grid workflow scheduler.