Abstract
Data integration has been an important area of research for several years. However, such systems suffer from one of the main drawbacks of database systems: the need to invest significant modeling effort upfront. Dataspace Support Platforms (DSSP) envision a system that offers useful services on its data without any setup effort, and improve with time in a pay-as-you-go fashion. We argue that in order to support DSSPs, the system needs to model uncertainty at its core. We describe the concepts of probabilistic mediated schemas and probabilistic mappings as enabling concepts for DSSPs.
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Sarma, A.D., Dong, X.(., Halevy, A.Y. (2009). Data Modeling in Dataspace Support Platforms. In: Borgida, A.T., Chaudhri, V.K., Giorgini, P., Yu, E.S. (eds) Conceptual Modeling: Foundations and Applications. Lecture Notes in Computer Science, vol 5600. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02463-4_8
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DOI: https://doi.org/10.1007/978-3-642-02463-4_8
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