Data measurement in research information systems: metrics for the evaluation of data quality

Author:

Azeroual Otmane,Saake Gunter,Wastl Jürgen

Publisher

Springer Science and Business Media LLC

Subject

Library and Information Sciences,Computer Science Applications,General Social Sciences

Reference22 articles.

1. Apel, D., Behme, W., Eberlein, R., & Merighi, C. (2015). Successfully control data quality: Practice solutions for business intelligence projects, 3rd, Revised and Extended Edition. Heidelberg: dpunkt.verlag.

2. Azeroual, O., & Abuosba, M. (2017). Improving the data quality in the research information systems. International Journal of Computer Science and Information Security, 15(11), 82–86.

3. Azeroual, O., Saake, G., & Abuosba, M. (2018a). Data quality measures and data cleansing for research information systems. Journal of Digital Information Management, 16(1), 12–21.

4. Azeroual, O., Saake, G., & Schallehn, E. (2018b). Analyzing data quality issues in research information systems via data profiling. International Journal of Information Management, 41(8), 50–56. https://doi.org/10.1016/j.ijinfomgt.2018.02.007 .

5. Batini, C., & Scannapieco, M. (2006). Data quality—Concepts methodologies and techniques. Heidelberg: Springer.

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