Abstract
Data integration systems (DIS) are devoted to providing information by integrating and transforming data extracted from external sources. Examples of DIS are the mediators, data warehouses, federations of databases, and web portals. Data quality is an essential issue in DIS as it concerns the confidence of users in the supplied information. One of the main challenges in this field is to offer rigorous and practical means to evaluate the quality of DIS. In this sense, DIS reliability intends to represent its capability for providing data with a certain level of quality, taking into account not only current quality values but also the changes that may occur in data quality at the external sources. Simulation techniques constitute a non-traditional approach to data quality evaluation, and more specifically for DIS reliability. This chapter presents techniques for DIS reliability evaluation by applying simulation techniques in addition to exact computation models. Simulation enables some important drawbacks of exact techniques to be addressed: the scalability of the reliability computation when the set of data sources grows, and modeling data sources with inter-related (non independent) quality properties.
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In the solution given in this work we do not differentiate between “quality factor” and “quality dimension.”
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Marotta, A., Cancela, H., Peralta, V., Ruggia, R. (2010). Reliability Models for Data Integration Systems. In: Faulin, J., Juan, A., Martorell, S., Ramírez-Márquez, JE. (eds) Simulation Methods for Reliability and Availability of Complex Systems. Springer Series in Reliability Engineering. Springer, London. https://doi.org/10.1007/978-1-84882-213-9_6
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