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A publicação pode ser exportada nos seguintes formatos: referência da APA (American Psychological Association), referência do IEEE (Institute of Electrical and Electronics Engineers), BibTeX e RIS.

Exportar Referência (APA) 
Costa, C. J. & Aparício, J. T. (2020). POST-DS: A methodology to boost data science. In Rocha, A., Perez, B. E., Penalvo, F. G., del Mar Miras, M., & Goncalves, R. (Ed.), 2020 15th Iberian Conference on Information Systems and Technologies (CISTI). Sevilla: IEEE.
Exportar Referência (IEEE) 
C. M. Costa and J. T. Aparicio,  "POST-DS: A methodology to boost data science", in 2020 15th Iberian Conf. on Information Systems and Technologies (CISTI), Rocha, A., Perez, B. E., Penalvo, F. G., del Mar Miras, M., & Goncalves, R., Ed., Sevilla, IEEE, 2020
Exportar BibTeX 
@inproceedings{costa2020_1715001570758,
	author = "Costa, C. J. and Aparício, J. T.",
	title = "POST-DS: A methodology to boost data science",
	booktitle = "2020 15th Iberian Conference on Information Systems and Technologies (CISTI)",
	year = "2020",
	editor = "Rocha, A., Perez, B. E., Penalvo, F. G., del Mar Miras, M., & Goncalves, R.",
	volume = "",
	number = "",
	series = "",
	doi = "10.23919/CISTI49556.2020.9140932",
	publisher = "IEEE",
	address = "Sevilla",
	organization = "",
	url = "https://ieeexplore.ieee.org/xpl/conhome/9137058/proceeding"
}
Exportar RIS 
TY  - CPAPER
TI  - POST-DS: A methodology to boost data science
T2  - 2020 15th Iberian Conference on Information Systems and Technologies (CISTI)
AU  - Costa, C. J.
AU  - Aparício, J. T.
PY  - 2020
SN  - 2166-0727
DO  - 10.23919/CISTI49556.2020.9140932
CY  - Sevilla
UR  - https://ieeexplore.ieee.org/xpl/conhome/9137058/proceeding
AB  - As the importance of data science is increasing, the number of projects involving data science and machine learning is rising either in quantity or in complexity. It is essential to employ a methodology that may contribute to the improvement of the outputs. In this context, it is crucial to identify possible approaches. And an overview of the evolution of data mining process models and methodologies is given for context. And the analysis showed that the methodologies covered were not complete. So, a new approach is proposed to tackle this problem. POST-DS (Process Organization and Scheduling electing Tools for Data Science) is a process-oriented methodology to assist the management of data science projects. This approach is not supported only in the process but also in the organization scheduling and tool selection.
ER  -