Evaluating Data Quality for Integration of Data Sources

Abstract : Data can be looked upon as a type of model (on the instance level), as illustrated e.g., in the product models in CAD and PLM-systems. In this paper we use a specialization of a general framework for assessing quality of models to be able to evaluate the combined quality of data for the purpose of investigating potential challenges when doing data integration across different sources. A practical application of the framework from assessing the potential quality of different data sources to be used together in a collaborative work environment is used for illustrating the usefulness of the framework for this purpose. An assessment of specifically relevant knowledge sources (including the characteristics of the tools used for accessing the data) has been done. This has indicated opportunities, but also challenges when trying to integrate data from different data sources typically used by people in different roles in an organization.
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Communication dans un congrès
Wil Aalst; John Mylopoulos; Michael Rosemann; Michael J. Shaw; Clemens Szyperski; Janis Grabis; Marite Kirikova; Jelena Zdravkovic; Janis Stirna. 6th The Practice of Entrprise Modeling (PoEM), Nov 2013, Riga, Latvia. Springer, Lecture Notes in Business Information Processing, LNBIP-165, pp.39-53, 2013, The Practice of Enterprise Modeling. 〈10.1007/978-3-642-41641-5_4〉
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John Krogstie. Evaluating Data Quality for Integration of Data Sources. Wil Aalst; John Mylopoulos; Michael Rosemann; Michael J. Shaw; Clemens Szyperski; Janis Grabis; Marite Kirikova; Jelena Zdravkovic; Janis Stirna. 6th The Practice of Entrprise Modeling (PoEM), Nov 2013, Riga, Latvia. Springer, Lecture Notes in Business Information Processing, LNBIP-165, pp.39-53, 2013, The Practice of Enterprise Modeling. 〈10.1007/978-3-642-41641-5_4〉. 〈hal-01474754〉

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