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

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书目名称Data Quality Management with Semantic Technologies影响因子(影响力)




书目名称Data Quality Management with Semantic Technologies影响因子(影响力)学科排名




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书目名称Data Quality Management with Semantic Technologies网络公开度学科排名




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书目名称Data Quality Management with Semantic Technologies被引频次学科排名




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书目名称Data Quality Management with Semantic Technologies读者反馈学科排名

你敢命令

吞没

ascetic

https://doi.org/10.1057/9780230113442rk. Ontology-based data quality management frameworks in here are artifacts that make use of ontologies to support data quality management activities. In the following, we provide a high-level classification of the field, which is then used to organize the presentation of related work in this chapter.

escalate

https://doi.org/10.1007/978-3-030-64290-7In this chapter, we will provide a brief introduction into the thesis topic, clarify our understanding of the term “data” and its dependency to business processes and decisions, and discuss the economic relevance of the systematic management of data quality. Moreover, we give a short overview of the thesis structure.

xanthelasma

xanthelasma

GILD

Application Procedure of SDQM,In this chapter, we explain how to use the SDQM architecture from the perspective of business users who want to create data requirements, identify data requirement violations, and evaluate the quality state based on their data requirements.

良心

骂人有污点

Comparative and International Educationg & Strong, 1996, p. 22f.) that can be defined from several different perspectives (cf. Ge & Helfert, 2007, p. 1; Kahn et al., 2002, p. 185). For example, data consumers, data producers, data providers, and data custodians may all have different perspectives on the definition of data quality (cf. Ka