Titlebook: Data Quality Management with Semantic Technologies; Christian Fürber Book 2016 Springer Fachmedien Wiesbaden 2016 Data Quality Problems.Da

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Comparative and International Educationhn et al., 2002, p. 184). From the consumer viewpoint, data quality can be defined as “data that are fit for use by data consumers” (Wang & Strong, 1996, p. 6) in analogy to the popular quality definition related to products and services by Juran (Juran, 1988, p. 2.2).

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https://doi.org/10.1007/978-1-4615-8936-5, one Semantic Web use case with data from DBpedia, and one use case that examines the capability of SDQM to automatically identify inconsistent data requirements. In the third part of the evaluation, SDQM is compared to a conventional data quality tool.

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ity software. Besides the framework, this thesis delivers important theoretical findings, namely a comprehensive typology of data quality problems, ten generic data requirement types, a requirement-centric data quality management process, and an analysis of related work. .978-3-658-12224-9978-3-658-12225-6

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