Data Integration and Contextual Knowledge Engineering

Data integration represents a critical process supporting the essential characteristics of information systems within the enterprise ecosystem. The ultimate objective is to offer a unified accessible environment for decision-making and operational purposes, where information persists in one single place and is always up-to-date. Achieving the levels and thresholds of integration and interoperability needed to fulfil these objectives involves paying particular attention to the quality of data. Integrating a number of data sources often involves some level of reconciliation between the data structures and data semantics of the sources themselves, which can result in inconsistencies within the integrated dataset when the quality of the data is neglected. In this light, the principles of data governance can be applied to ensure the quality of integrated data, as well as the tracking of provenance information to permit traceability.