Abstract
The integration of data stemming from heterogeneous sources is an issue that has challenged computer science research for years - not to say decades. Therefore, many methods, frameworks and tools were and are still being developed that all promise to solve the integration of data. This work describes those which we think are most promising by relating them to each other. Since our focus is on scientific applications, we consider important properties within this domain such as data provenance. However, aspects like the extensibility of an approach are also considered. © 2010 Springer-Verlag Berlin Heidelberg.
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CITATION STYLE
Roth, B., Volz, B., & Hecht, R. (2010). Data integration systems for scientific applications. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6428 LNCS, pp. 110–118). https://doi.org/10.1007/978-3-642-16961-8_26
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