Please use this identifier to cite or link to this item:
https://doi.org/10.21256/zhaw-18250| Publication type: | Article in scientific journal |
| Type of review: | Peer review (publication) |
| Title: | Feedback-based integration of the whole process of data anonymization in a graphical interface |
| Authors: | Meindl, Bernhard Templ, Matthias |
| et. al: | No |
| DOI: | 10.3390/a12090191 10.21256/zhaw-18250 |
| Published in: | Algorithms |
| Volume(Issue): | 12 |
| Issue: | 9 |
| Page(s): | 191 |
| Issue Date: | 2019 |
| Publisher / Ed. Institution: | MDPI |
| ISSN: | 1999-4893 |
| Language: | English |
| Subjects: | Anonymization; R-package; User interface; Feedback-system |
| Subject (DDC): | 005: Computer programming, programs and data |
| Abstract: | The interactive, web-based point-and-click application presented in this article, allows anonymizing data without any knowledge in a programming language. Anonymization in data mining, but creating safe, anonymized data is by no means a trivial task. Both the methodological issues as well as know-how from subject matter specialists should be taken into account when anonymizing data. Even though specialized software such as sdcMicro exists, it is often difficult for nonexperts in a particular software and without programming skills to actually anonymize datasets without an appropriate app. The presented app is not restricted to apply disclosure limitation techniques but rather facilitates the entire anonymization process. This interface allows uploading data to the system, modifying them and to create an object defining the disclosure scenario. Once such a statistical disclosure control (SDC) problem has been defined, users can apply anonymization techniques to this object and get instant feedback on the impact on risk and data utility after SDC methods have been applied. Additional features, such as an Undo Button, the possibility to export the anonymized dataset or the required code for reproducibility reasons, as well its interactive features, make it convenient both for experts and nonexperts in R – the free software environment for statistical computing and graphics – to protect a dataset using this app. |
| URI: | https://digitalcollection.zhaw.ch/handle/11475/18250 |
| Fulltext version: | Published version |
| License (according to publishing contract): | CC BY 4.0: Attribution 4.0 International |
| Departement: | School of Engineering |
| Organisational Unit: | Institute of Data Analysis and Process Design (IDP) |
| Appears in collections: | Publikationen School of Engineering |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| algorithms-12-00191-v2.pdf | 876.8 kB | Adobe PDF |  View/Open |
Show full item record
Meindl, B., & Templ, M. (2019). Feedback-based integration of the whole process of data anonymization in a graphical interface. Algorithms, 12(9), 191. https://doi.org/10.3390/a12090191
Meindl, B. and Templ, M. (2019) ‘Feedback-based integration of the whole process of data anonymization in a graphical interface’, Algorithms, 12(9), p. 191. Available at: https://doi.org/10.3390/a12090191.
B. Meindl and M. Templ, “Feedback-based integration of the whole process of data anonymization in a graphical interface,” Algorithms, vol. 12, no. 9, p. 191, 2019, doi: 10.3390/a12090191.
MEINDL, Bernhard und Matthias TEMPL, 2019. Feedback-based integration of the whole process of data anonymization in a graphical interface. Algorithms. 2019. Bd. 12, Nr. 9, S. 191. DOI 10.3390/a12090191
Meindl, Bernhard, and Matthias Templ. 2019. “Feedback-Based Integration of the Whole Process of Data Anonymization in a Graphical Interface.” Algorithms 12 (9): 191. https://doi.org/10.3390/a12090191.
Meindl, Bernhard, and Matthias Templ. “Feedback-Based Integration of the Whole Process of Data Anonymization in a Graphical Interface.” Algorithms, vol. 12, no. 9, 2019, p. 191, https://doi.org/10.3390/a12090191.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.