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English Information

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Authors
# Name
1 Débora Pina(dbpina@cos.ufrj.br)
2 Liliane Kunstmann(lneves@cos.ufrj.br)
3 Marta Mattoso(marta@cos.ufrj.br)
4 Marcos Lage(mlage@ic.uff.br)
5 Daniel de Oliveira(danielcmo@ic.uff.br)

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Reference
# Reference
1 Blanco, G., Traina, A. J. M., Traina, C., Azevedo-Marques, P. M., Jorge, A. E. S., de Oliveira, D., Bedo, M. V. N. (2020). A superpixel-driven deep learning approach for the analysis of dermatological wounds. Computer Methods and Programs in Biomedicine, 183:105079.
2 Borges, G. C., dos Reis, J. C., and Medeiros, C. B. (2021). Addressing search in scientific open data repositories: A semantic metasearch platform. In BreSci, pages 81–88. SBC.
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6 Flemisch, B., Hermann, S., Herschel, M., Pflüger, D., Pleiss, J., Range, J., Roy, S., Takamoto, M., Uekermann, B. (2024). Research data management in simulation science: Infrastructure, tools, and applications. Datenbank-Spektrum, 24(2):97–105.
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12 Nilsback, M.-E. and Zisserman, A. (2006). A visual vocabulary for flower classification. In CVPR’06, volume 2, pages 1447–1454. IEEE.
13 Pina, D. Chapman, A., Kunstmann, L., de Oliveira, D., Mattoso, M. (2024). Dlprov: A data-centric support for deep learning workflow analyses. In DEEM’24, DEEM ’24, page 77–85, New York, NY, USA. ACM.
14 Pina, D., Kunstmann, L., Chapman, A., de Oliveira, D., & Mattoso, M. (2025). Dlprov: a suite of provenance services for deep learning workflow analyses. PeerJ Comp. Sci., 11:e2985.
15 Ravi, N., Chaturvedi, P., Huerta, E. A., Liu, Z., Chard, R., Scourtas, A., Schmidt, K. J., Chard, K., Blaiszik, B., Foster, I. (2022). Fair principles for ai models with a practical application for accelerated high energy diffraction microscopy. Scientific Data, 9(1):657.
16 Schackart III, K. E., Imker, H. J., and Cook, C. E. (2024). Detailed implementation of a reproducible machine learning-enabled workflow. Data Science Journal.
17 Schlegel, M. and Sattler, K.-U. (2023). Mlflow2prov: Extracting provenance from machine learning experiments. DEEM ’23, New York, NY, USA. ACM.
18 Waskita, A. A., Akbar, Z., Saleh, D. R., Kartika, Y. A., Indrawati, A. (2023). Open science progress: A literature assessment of open access articles. In IC3INA’22, page 271–275, New York, NY, USA. ACM.
19 Wilkinson, M. D. o. (2016). The fair guiding principles for scientific data management and stewardship. Scientific data, 3(1):1–9.