Return to SciDISC (2017-2019) with LNCC, UFRJ, UFF, CEFET (Brazil)

SciDISC publications

[Khatibi 2017] A. Khatibi, F. Porto, J. Rittmeyer, E. Ogasawara, P. Valduriez, D. Shasha. Pre-processing and Indexing Techniques for Constellation Queries in Big Data. Int. Conf. on Big Data Analytics and Knowledge Discovery (DaWaK), 164-172, 2017.

[Liu 2017] J. Liu, E. Pacitti, P. Valduriez, M. Mattoso. Scientific Workflow Scheduling with Provenance Data in a Multisite Cloud. Trans. on Large-Scale Data- and Knowledge-Centered Systems (TLDKS), 33: 80-112, 2017.

[Pineda-Morales 2017] L. Pineda-Morales, J. Liu, A. Costany, E Pacitti, G. Antoniu, P. Valduriez, M. Mattoso. Efficient Scheduling of Scientific Workflows using Hot Metadata in a Multisite Cloud. BDA : Conf. sur la Gestion de Données — Principes, Technologies et Applications, 2017.

[Camata 2017] J. Camata, V. Silva, P. Valduriez, M. Mattoso, A. Coutinho. In Situ Visualization and Data Analysis for Turbidity Currents Simulation. Computers & Geosciences, 110, pp.23 – 31, 2017.

[Campisano 2017], R. Campisano, Sequence Mining in Spatial-Time Series (Master Degree Dissertation), CEFET/RJ, 2017.

[Cruz 2017], A.B. Cruz, J. Ferreira, B. Monteiro, R. Coutinho, F. Porto, E. Ogasawara, Detecção de Anomalias no Transporte Rodoviário Urbano, Brazilian Symposium on Databases (SBBD), 2017.

[Hermano 2017] H. Lustosa, F. Porto, N. Lemus, P. Valduriez, TARS: Na Extension of the Multi-dimensional Array Model, ER FORUM – Conceptual Modeling : Research In Progress, Valencia, 2017

[Porto 2017] F. Porto, A. Khatibi, J. Nobre, E. Ogasawara, P. Valduriez, D. Shasha. Constellation Queries over Big Data. CoRR abs/1703.02638, 2017.

[Gaspar 2017] D. Gaspar, F. Porto, R. Akbarinia, E. Pacitti, TARDIS: Optimal Execution of Scientific Workflows in Apache Spark. Int. Conf. on Big Data Analytics and Knowledge Discovery (DaWaK), 74-87, 2017.

[Silva 2017] V. Silva, J. Leite, J. Camata, D. de Oliveira, A. Coutinho, P. Valduriez, M. Mattoso. Raw data queries during data-intensive parallel workflow execution. Future Generation Computer Systems, Elsevier, 75: 402-422, 2017.

[Silva Jr 2017] D. Silva Jr., A. Paes, E. Pacitti, D. Oliveira. Data Quality Prediction in Scientific Workflows. In preparation. 2017

[Souza 2017a] R. Souza, V. Silva, P. Miranda, A. Lima, P. Valduriez, M. Mattoso. Spark Scalability Analysis in a Scientific Workflow. Brazilian Symposium on Databases (SBBD), Best Paper Award, 2017.

[Souza 2017b] R. Souza, V. Silva, J. Camata, A. Coutinho, P. Valduriez, M. Mattoso. Tracking of Online Parameter Fine-tuning in Scientific Workflows. Workshop on Workflows in Support of Large-Scale Science (WORKS), ACM/IEEE Supercomputing Conference, 2017.

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