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English Information

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Authors
# Name
1 Thiago Jordão(thiagojordao@id.uff.br)
2 Daniel de Oliveira(danielcmo@ic.uff.br)
3 Marcos Bedo(marcosbedo@id.uff.br)

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Reference
# Reference
1 Barros, P.V.S., Monteiro, J.M., Brayner, A., and Machado, J.C. (2024). Incorporando os requisitos e as restrições da lgpd ao projeto de banco de dados. In SBBD’24, pages 341–353. SBC.
2 Bauer, D., Giblin, C., Garcés-Erice, L., Pardon, N., Rooney, S., Toniato, E., and Urbanetz, P. (2022). Revisiting data lakes: the metadata lake. In Middleware’22, page 8–14, New York, NY, USA.
3 Becker, B. and Kohavi, R. (1996). Adult. UCI Machine Learning Repository. DOI:https://doi.org/10.24432/C5XW20.
4 Deshpande, A. (2021). Sypse: privacy-first data management through pseudonymization and partitioning. In CIDR, pages 1–8, Chaminade, CA.
5 Domingo-Ferrer, J. and Torra, V. (2005). Ordinal, continuous and heterogeneous k-anonymity through microaggregation. Data Mining and Knowledge Discovery, 11(2):195–212.
6 Dwork, C., McSherry, F., Nissim, K., and Smith, A. (2006). Calibrating noise to sensitivity in private data analysis. In TCC 2006, volume 3876, pages 265–284. Springer.
7 Francis, P., Probst-Eide, S., Obrok, P., Berneanu, C., Juric, S., and Munz, R. (2018). Diffixbirch: Extending diffix-aspen. arXiv preprint arXiv:1806.02075.
8 Giomi, M., Boenisch, F., Wehmeyer, C., and Tasnádi, B. (2023). A unified framework for quantifying privacy risk in synthetic data. Proceedings on Privacy Enhancing Technologies, 2023(2):312–328.
9 Machado, J. C. and Amora, P. R. (2021). The impact of privacy regulations on db systems. Journal of Information and Data Management, 12(5).
10 Machanavajjhala, A., Kifer, D., Gehrke, J., and Venkitasubramaniam, M. (2007). L-diversity: Privacy beyond k-anonymity. ACM Trans. Knowl. Discov. Data, 1(1):3–es.
11 Miguel, J., Pereira, M. J., Henriques, P., and Berón, M. (2019). Assuring data privacy with privas – a tool for data publishers. IADIS International Journal on Computer Science and Information Systems, 14(2):41–58.
12 Nargesian, F., Zhu, E., Miller, R. J., Pu, K. Q., and Arocena, P. C. (2019). Data lake management: Challenges and opportunities. Proc. VLDB Endow., 12(12):1986–1989.
13 Ogasawara, E., Paulino, C., Murta, L., Werner, C., and Mattoso, M. (2009). Experiment line: software reuse in scientific workflows. In Proc. of the SSDBM 2009, pages 264–272, Berlin. Springer.
14 Oreščanin, D., Hlupić, T., and Vrdoljak, B. (2024). Managing personal identifiable information in data lakes. IEEE access, 12:32164–32180.
15 Poulis, G., Gkoulalas-Divanis, A., Loukides, G., Skiadopoulos, S., and Tryfonopoulos, C. (2014). SECRETA: A system for evaluating and comparing relational and transaction anonymization algorithms. In EDBT’14, pages 620–623.
16 Prasser, F., Eicher, J., Spengler, H., Bild, R., and Kuhn, K.A. (2020). Flexible data anonymization using arx—current status and challenges ahead. Software: Pract. and Exp., 50(7):1277–1304.
17 Sweeney, L. (2002). k-anonymity: a model for protecting privacy. Int. J. Uncertain. Fuzziness Knowl.-Based Syst., 10(5):557–570.
18 Terrovitis, M., Liagouris, J., Mamoulis, N., and Skiadopoulos, S. (2012). Privacy preservation by disassociation. arXiv preprint arXiv:1207.0135.
19 Zigomitros, A., Casino, F., Solanas, A., and Patsakis, C. (2020). A survey on privacy properties for data publishing of relational data. Ieee Access, 8:51071–51099.