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English Information

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Authors
# Name
1 Gustavo Tallarida(gustavotallarida@id.uff.br)
2 Kary Ocaña(karyann@lncc.br)
3 Aline Paes(alinepaes@ic.uff.br)
4 Vanessa Braganholo (vanessa@ic.uff.br)
5 Daniel de Oliveira(danielcmo@ic.uff.br)

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Reference
# Reference
1 Ahola, V., Aittokallio, T., Vihinen, M. and Uusipaikka, E. (2008). Model-based prediction of sequence alignment quality. Bioinformatics (Oxford, England), v. 24, n. 19, p. 2165–2171.
2 Boulos, J., Dalvi, N., Mandhani, B., et al. (2005). MYSTIQ: A System for Finding More Answers by Using Probabilities. In Int. Conf. Management of Data (SIGMOD), pp. 891-893.
3 Chapman, A., Blaustein, B. and Elsaesser, C. (2010). Provenance-based Belief. In Workshop on the Theory and Practice of Provenance (TaPP). p. 11.
4 Costa, F., Silva, V., De Oliveira, D., et al. (2013). Capturing and Querying Workflow Runtime Provenance with PROV: A Practical Approach. In EDBT/ICDT Workshops, pp. 282-289.
5 De Oliveira, D., Silva, V. and Mattoso, M. (2015). How Much Domain Data Should Be in Provenance Databases? In Workshop on Theory and Practice of Provenance (TaPP).
6 Freire, J., Koop, D., Santos, E. and Silva, C. T. (2008). Provenance for Computational Tasks: A Survey. Computing in Science Engineering, v. 10, n. 3, p. 11–21.
7 Gonçalves, J. C. de A. R., Oliveira, D. De, Ocaña, K. A. C. S., Ogasawara, E. and Mattoso, M. (2012). Using Domain-Specific Data to Enhance Scientific Workflow Steering Queries. In International Provenance and Annotation Workshop (IPAW), pp. 152–167.
8 Huang, J., Antova, L., Koch, C. and Olteanu, D. (2009). MayBMS: A Probabilistic Database Management System. In Int. Conf. Management of Data (SIGMOD), pp. 1071-1071.
9 Idika, N., Varia, M. and Phan, H. (2013). The Probabilistic Provenance Graph. In IEEE Security and Privacy Workshops (SPW), pp 34-41.
10 Mattoso, M., Werner, C., Travassos, G. H., et al. (2010). Towards supporting the life cycle of large scale scientific experiments. Int. Journal of Business Process Integration and Management, v. 5, n. 1, p. 79.
11 Moreau, L., Clifford, B., Freire, J., et al. (2011). The Open Provenance Model core specification (v1.1). Future Generation Computer Systems, v. 27, n. 6, p. 743–756.
12 Moreau, L. and Missier, P. (2013). The PROV Data Model and Abstract Syntax Notation. W3C Recommendation.
13 Ocaña, K. A. C. S., Oliveira, D. De, Ogasawara, E., et al. (2011). SciPhy: A Cloud-Based Workflow for Phylogenetic Analysis of Drug Targets in Protozoan Genomes. In Advances in Bioinformatics and Computational Biology, pp. 66-70.
14 Ogasawara, E., Dias, J., Oliveira, D., et al. (2011). An Algebraic Approach for Data-Centric Scientific Workflows. Proc. of the Int. Conf. on Very Large Data Bases (PVLDB), v. 4, n. 12, p. 1328–1339.
15 Re, C. and Suciu, D. (2007). Management of Data with Uncertainties. In Conference on Information and Knowledge Management (CIKM), pp. 3-8.
16 Simmhan, Y. L., Plale, B. and Gannon, D. (2008). Query capabilities of the Karma provenance framework. Concurrency and Computation: Practice and Experience, v. 20, n. 5, p. 441–451.