Data perspectives of workflow schema evolution

Abstract

Purpose – Most literature on workflow (WF) adaptation considered the control flow correctness like absence of dead lock, live-lock, etc. during adaptation. The data aspect of WF adaptation like data flow, database schema changes and their correctness are less studied. When the WF schema is modified, their data flow and the database schema changes. The existing approaches used for adapting these data changes in the underlying database schema are time consuming and/or affect the old data persistence. The purpose of this paper is to concern the dynamic adaptation of the WF schema and implementing its data changes in the existing database schema. Design/methodology/approach – A conceptual framework developed to adapt on-the-fly, the concomitant data changes during WF adaptation. The framework consists a set of data schema compliance criteria (DSC) which identify the data changes that can be directly accommodated in the existing database schema. Data adaptation algorithm (DAA) is developed to handle the data changes that does not conform to the DSC in the existing database schema. Findings – In this approach the existing database schema is dynamically evolved without re-creating it, after WF schema adaptation. Therefore the WF schema changes can be implemented on-the-fly without stopping the running system. It also ensures the persistence of old data residing in the existing database. Originality/value – A novel approach developed to adapt the data changes in the existing database schema, without requiring recreation or migration the data. This automated consistency checking of data attribute changes in the database schema and implement them dynamically.