Data integration heterogeneity

Schema matching aims at identifying semantic correspondences between metadata structures or models, such as database schemas, XML message formats, and ontologies. Solving such match problems is a key task in numerous application fields, particularly to support data exchange, schema evolution, and virtually all kinds of data integration. Unfortunately, the typically high degree of semantic heterogeneity reflected in different schemas makes schema matching an inherently complex task. Hence, most current systems still require the manual specification of semantic correspondences, e.g., with the help of a GUI. While such an approach is appropriate for...

As motivated in the introduction, in data integration, there exists a set of heterogeneous, independent sources that contain related data. To have these sources be queried efficiently, a mediated schema can be created. Because these sources are independent, heterogeneous, and often change rapidly, it is not possible to then import all of the data into the mediated schema. Instead, the users query the mediated schema, and then the system translates the queries over the mediated schema into queries over the sources. 

The theme for transparent access to multidimensional heterogeneous data is the foundation for other themes for combinatorial analysis and online collaboration. In other words, data integration for transparent access to multidimensional heterogeneous data is the foundation for biomedical informatics to enable undirected data mining for knowledge discovery. With undirected data mining, combinatorial analysis can be used for developing a hypothesis and statistical analysis for validation of the hypothesis. 

The challenges for data integration for clinical genomics are these the data to be accessed are multidimensional and heterogeneous, the majority of data are unstructured and exist in natural language text, the data contains personal information that is subject to statutory requirements for protection of privacy, the ownerships of data lie with multiple stakeholders in multiple organizations,... 

Serral, E., Mordinyi, R., Kovalenko, O., Winkler, D., BifB, S. Evaluation of semantic data storages for integrating heterogenous disciplines in automation systems engineering. In Proceedings of the 39th Annual Conference of Industrial Electronics Society Conference (lECON 2013), pp. 6858-6865. IEEE (2013)... 

Data integration. Both MDE and Semantic Web communities provide mechanisms for creating and maintaining mappings to integrate heterogeneous data sources, in particular, links between schemas and between instances (Oberle 2014). 

Another school has also developed and attempted to understand the functional dependence of adsorption on heterogeneous surfaces on the vapor pressure and temperature. Various empirical or semiempirical equations were proposed [24-26] and used later to represent experimental data and to evaluate EADF by inverting Eq. (1), which belongs to the class of linear Fredholm integrals of the first kind [27]. 

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