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ORCIDDaniel de Oliveira 0001
Daniel C. M. de Oliveira – Daniel Cardoso Moraes de Oliveira – Daniel Oliveira 0001
Person information
- affiliation: Fluminense Federal University, Niterói, Institute of Computing, Rio de Janeiro, Brazil
Other persons with the same name
- Daniel de Oliveira 0002 — Federal University of Santa Catarina, Department of Production and Systems Engineering, Brazil
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2020 – today
- 2021
[j56]Douglas E. M. de Oliveira, Fábio Porto, Cristina Boeres, Daniel de Oliveira:
Towards optimizing the execution of spark scientific workflows using machine learning-based parameter tuning. Concurr. Comput. Pract. Exp. 33(5) (2021)- [j55]André Nascimento, Vítor Silva, Aline Paes
, Daniel de Oliveira:
An incremental reinforcement learning scheduling strategy for data-intensive scientific workflows in the cloud. Concurr. Comput. Pract. Exp. 33(11) (2021) - [j54]Gaëtan Heidsieck, Daniel de Oliveira, Esther Pacitti, Christophe Pradal, François Tardieu, Patrick Valduriez:
Cache-aware scheduling of scientific workflows in a multisite cloud. Future Gener. Comput. Syst. 122: 172-186 (2021) - [j53]Maristela Terto de Holanda, Daniel Cardoso Moraes de Oliveira, Moacir Antonelli Ponti:
Frontmatter. J. Inf. Data Manag. 12(1) (2021) - [j52]Maristela Terto de Holanda, Daniel Cardoso Moraes de Oliveira, Moacir Antonelli Ponti:
Editorial. J. Inf. Data Manag. 12(1) (2021) - [j51]Maristela Terto de Holanda, Daniel Cardoso Moraes de Oliveira, Ronaldo dos Santos Mello:
Frontmatter. J. Inf. Data Manag. 12(2) (2021) - [j50]Maristela Terto de Holanda, Daniel Cardoso Moraes de Oliveira, Ronaldo dos Santos Mello:
Editorial. J. Inf. Data Manag. 12(2) (2021) - [j49]João V. O. Novaes, Lúcio F. D. Santos, Luiz Olmes Carvalho, Daniel de Oliveira, Marcos V. N. Bedo, Agma J. M. Traina, Caetano Traina Jr.:
J-EDA: A workbench for tuning similarity and diversity search parameters in content-based image retrieval. J. Inf. Data Manag. 12(2) (2021) - [j48]Leonardo S. Ramos, Fábio Porto, Daniel de Oliveira:
Managing Hypothesis of Scientific Experiments with PhenoManager. J. Inf. Data Manag. 12(2) (2021) - [j47]Maristela Terto de Holanda, Daniel Cardoso Moraes de Oliveira, Fábio Porto:
Frontmatter. J. Inf. Data Manag. 12(3) (2021) - [j46]Maristela Terto de Holanda, Daniel Cardoso Moraes de Oliveira, Fábio Porto:
Editorial. J. Inf. Data Manag. 12(3) (2021) - [j45]Camila R. Lopes, Lúcio F. D. Santos, Daniel L. Jasbick, Daniel de Oliveira, Marcos V. N. Bedo:
An empirical assessment of quality metrics for diversified similarity searching. J. Inf. Data Manag. 12(3) (2021) - [j44]Maristela Terto de Holanda, Daniel Cardoso Moraes de Oliveira, Thales Sehn Körting:
Frontmatter. J. Inf. Data Manag. 12(4) (2021) - [j43]Maristela Terto de Holanda, Daniel Cardoso Moraes de Oliveira, Thales Sehn Körting:
Editorial. J. Inf. Data Manag. 12(4) (2021) - [j42]Maria Luiza Furtuozo Falci, Andréa Magalhães Magdaleno, Aline Paes, Vanessa Braganholo, Daniel de Oliveira:
Multimodal Provenance-based Analysis of Collaboration in Business Processes. J. Inf. Data Manag. 12(5) (2021) - [j41]Maristela Terto de Holanda, Daniel Cardoso Moraes de Oliveira, Ricardo da Silva Torres:
Frontmatter. J. Inf. Data Manag. 12(5) (2021) - [j40]Liliane N. O. Kunstmann, Débora B. Pina, Filipe Silva, Aline Paes, Patrick Valduriez, Daniel de Oliveira, Marta Mattoso:
Online Deep Learning Hyperparameter Tuning based on Provenance Analysis. J. Inf. Data Manag. 12(5) (2021) - [d2]Vinícius Salazar, João Cavalcante, Daniel de Oliveira, Fabiano L. Thompson, Marta Mattoso:
BioProv - A provenance library for bioinformatics workflows. J. Open Source Softw. 6(67): 3622 (2021) - [j39]Renan Souza, Vítor Silva, Alexandre A. B. Lima, Daniel de Oliveira, Patrick Valduriez, Marta Mattoso:
Distributed in-memory data management for workflow executions. PeerJ Comput. Sci. 7: e527 (2021) - [j38]Daniel Silva Junior, Esther Pacitti, Aline Paes, Daniel de Oliveira:
Provenance-and machine learning-based recommendation of parameter values in scientific workflows. PeerJ Comput. Sci. 7: e606 (2021) - [c98]Débora B. Pina, Liliane N. O. Kunstmann, Daniel de Oliveira, Patrick Valduriez, Marta Mattoso:
Provenance Supporting Hyperparameter Analysis in Deep Neural Networks. IPAW 2021: 20-38 - [c97]Marcelo N. Almeida, Rodolfo Alves de Oliveira, Luiz Olmes Carvalho, Gustavo Silva Semaan, Daniel de Oliveira, Lúcio F. D. Santos, Marcos V. N. Bedo:
HELIX: A data-driven characterization of Brazilian land snails. SBBD 2021: 319-324 - [c96]Lorenna Christ'na Nascimento, Marcos Lage, Daniel de Oliveira:
Um Estudo Sobre o Uso de Abordagens de Gerência de Dados em Sistemas de Análise Visual de Dados Espaço-Temporais. SBBD 2021: 361-366 - [i4]Renan Souza, Vítor Silva, Alexandre A. B. Lima, Daniel de Oliveira, Patrick Valduriez, Marta Mattoso:
Distributed In-memory Data Management for Workflow Executions. CoRR abs/2105.04720 (2021) - 2020
- [j37]Thaylon Guedes, Leonardo Araújo de Jesus, Kary A. C. S. Ocaña, Lúcia M. A. Drummond, Daniel de Oliveira:
Provenance-based fault tolerance technique recommendation for cloud-based scientific workflows: a practical approach. Clust. Comput. 23(1): 123-148 (2020) - [j36]Gustavo Blanco, Agma J. M. Traina, Caetano Traina Jr., Paulo M. Azevedo-Marques, Ana Elisa Serafim Jorge, Daniel de Oliveira, Marcos V. N. Bedo:
A superpixel-driven deep learning approach for the analysis of dermatological wounds. Comput. Methods Programs Biomed. 183 (2020) - [j35]Marcello W. M. Ribeiro, Alexandre A. B. Lima, Daniel de Oliveira:
OLAP parallel query processing in clouds with C-ParGRES. Concurr. Comput. Pract. Exp. 32(7) (2020) - [j34]Kary A. C. S. Ocaña, Marcelo Galheigo, Carla Osthoff, Luiz M. R. Gadelha Jr., Fábio Porto, Antônio Tadeu A. Gomes, Daniel de Oliveira, Ana Tereza Ribeiro de Vasconcelos:
BioinfoPortal: A scientific gateway for integrating bioinformatics applications on the Brazilian national high-performance computing network. Future Gener. Comput. Syst. 107: 192-214 (2020) - [j33]Vítor Silva, Leonardo Neves, Renan Souza, Alvaro L. G. A. Coutinho, Daniel de Oliveira, Marta Mattoso:
Adding domain data to code profiling tools to debug workflow parallel execution. Future Gener. Comput. Syst. 110: 422-439 (2020) - [j32]Thaylon Guedes, Lucas Bertelli Martins, Maria Luiza Furtuozo Falci, Vítor Silva, Kary A. C. S. Ocaña, Marta Mattoso, Marcos V. N. Bedo, Daniel de Oliveira:
Capturing and Analyzing Provenance from Spark-based Scientific Workflows with SAMbA-RaP. Future Gener. Comput. Syst. 112: 658-669 (2020) - [j31]Yan Mendes, Daniel de Oliveira, Victor Ströele:
Polyflow: a Polystore-compliant Mechanism to Provide Interoperability to Heterogeneous Provenance Graphs. J. Inf. Data Manag. 11(3) (2020) - [d1]Vítor Silva, Vinícius Campos, Thaylon Guedes, José J. Camata, Daniel de Oliveira, Alvaro L. G. A. Coutinho, Patrick Valduriez, Marta Mattoso:
DfAnalyzer: Runtime dataflow analysis tool for Computational Science and Engineering applications. SoftwareX 12: 100592 (2020) - [j30]Gaëtan Heidsieck, Daniel de Oliveira, Esther Pacitti, Christophe Pradal, François Tardieu, Patrick Valduriez:
Efficient Execution of Scientific Workflows in the Cloud Through Adaptive Caching. Trans. Large Scale Data Knowl. Centered Syst. 44: 41-66 (2020) - [c95]Gaëtan Heidsieck, Daniel de Oliveira, Esther Pacitti, Christophe Pradal, François Tardieu, Patrick Valduriez:
Distributed Caching of Scientific Workflows in Multisite Cloud. DEXA (2) 2020: 51-65 - [c94]Carlos Gracioli Neto, Luciana Salgado, Victor Ströele, Daniel de Oliveira:
SigniFYIng APIs in the context of polystore systems: a case study with BigDAWG. IHC 2020: 57:1-57:6 - [c93]Bruno Lopes, Daniel de Oliveira:
Towards Failure Prediction in Scientific Workflows Using Stochastic Petri Nets and Dynamic Logic. QUATIC 2020: 449-456 - [c92]Renata Silva, Daniel Oliveira, Davi Pereira dos Santos, Lúcio F. D. Santos, Rodrigo Erthal Wilson, Marcos V. N. Bedo:
Criteria for choosing the number of dimensions in a principal component analysis: An empirical assessment. SBBD 2020: 145-150 - [c91]Lucas Tito, Cristina Motinha, Filipe Santiago, Kary A. C. S. Ocaña, Marcos V. N. Bedo, Daniel de Oliveira:
Xi-DL: um Sistema de Gerência de Data Lake para Monitoramento de Dados da Saúde. SBBD 2020: 151-156 - [c90]Maria Luiza Furtuozo Falci, Andréa Magalhães Magdaleno, Vanessa Braganholo, Aline Paes, Daniel de Oliveira:
Análise de Colaboração em Processos de Negócio por meio de SGBDs de Grafos e Dados de Proveniência Multimodais. SBBD 2020: 169-174 - [c89]Débora B. Pina, Liliane N. O. Kunstmann, Daniel de Oliveira, Patrick Valduriez, Marta Mattoso:
Uma abordagem para coleta e análise de dados de configurações em redes neurais profundas. SBBD 2020: 187-192 - [c88]Daniel L. Jasbick, Lúcio F. D. Santos, Daniel de Oliveira, Marcos V. N. Bedo:
Some Branches May Bear Rotten Fruits: Diversity Browsing VP-Trees. SISAP 2020: 140-154 - [c87]Elvismary Molina de Armas, Maristela Holanda, Daniel de Oliveira, Nalvo F. Almeida, Sérgio Lifschitz:
A Classification of de Bruijn Graph Approaches for De Novo Fragment Assembly. BSB 2020: 1-12 - [c86]Luiz Gustavo Dias, Marta Mattoso, Bruno Lopes, Daniel de Oliveira:
Experiencing DfAnalyzer for Runtime Analysis of Phylogenomic Dataflows. BSB 2020: 105-116 - [e1]Luis Antonio Brasil Kowada, Daniel de Oliveira:
Advances in Bioinformatics and Computational Biology - 12th Brazilian Symposium on Bioinformatics, BSB 2019, Fortaleza, Brazil, October 7-10, 2019, Revised Selected Papers. Lecture Notes in Computer Science 11347, Springer 2020, ISBN 978-3-030-46416-5 [contents]
2010 – 2019
- 2019
- [b1]Daniel C. M. de Oliveira, Ji Liu, Esther Pacitti:
Data-Intensive Workflow Management: For Clouds and Data-Intensive and Scalable Computing Environments. Synthesis Lectures on Data Management, Morgan & Claypool Publishers 2019 - [j29]Marcos Guerine, Murilo B. Stockinger, Isabel Rosseti, Luidi Gelabert Simonetti, Kary A. C. S. Ocaña, Alexandre Plastino, Daniel de Oliveira:
A provenance-based heuristic for preserving results confidentiality in cloud-based scientific workflows. Future Gener. Comput. Syst. 97: 697-713 (2019) - [c85]Kary A. C. S. Ocaña, Carla Osthoff, Micaella Coelho, Marcelo Galheigo, Isabela Canuto, Douglas E. M. de Oliveira, Daniel de Oliveira:
Performance Evaluation of Parallel Inference of Large Phylogenetic Trees in Santos Dumont Supercomputer: A Practical Approach. CARLA 2019: 448-463 - [c84]Wellington S. Silva, Daniel L. Jasbick, Rodrigo Erthal Wilson, Paulo M. Azevedo-Marques, Agma J. M. Traina, Lúcio F. D. Santos, Ana Elisa Serafim Jorge, Daniel de Oliveira, Marcos V. N. Bedo:
A Two-Phase Learning Approach for the Segmentation of Dermatological Wounds. CBMS 2019: 343-348 - [c83]Kary Ann del Carmen Ocaña Gautherot, Marcelo Galheigo, Carla Osthoff, Luiz M. R. Gadelha Jr., Antônio Tadeu A. Gomes, Daniel de Oliveira, Fábio Porto, Ana Tereza Ribeiro de Vasconcelos:
Towards a Science Gateway for Bioinformatics: Experiences in the Brazilian System of High Performance Computing. CCGRID 2019: 638-647 - [c82]Gaëtan Heidsieck, Daniel de Oliveira, Esther Pacitti, Christophe Pradal, François Tardieu, Patrick Valduriez:
Adaptive Caching for Data-Intensive Scientific Workflows in the Cloud. DEXA (2) 2019: 452-466 - [c81]Carlos Gracioli Neto, Amadeu Anderlin Neto, Marcos Kalinowski, Daniel Cardoso Moraes de Oliveira, Marta Sabou, Dietmar Winkler, Stefan Biffl:
Using Model Scoping with Expected Model Elements to Support Software Model Inspections: Results of a Controlled Experiment. ICEIS (2) 2019: 107-118 - [c80]Kary A. C. S. Ocaña, Thaylon Guedes, Daniel de Oliveira:
ArrOW: Experiencing a Parallel Cloud-Based De Novo Assembler Workflow. IPDPS Workshops 2019: 185-190 - [c79]André Nascimento, Victor Olimpio, Vítor Silva, Aline Paes, Daniel de Oliveira:
A Reinforcement Learning Scheduling Strategy for Parallel Cloud-Based Workflows. IPDPS Workshops 2019: 817-824 - [c78]Yan Mendes, Victor Ströele, Daniel de Oliveira, Kary A. C. S. Ocaña:
Análise Integrada de Grafos de Proveniência Heterogêneos por meio de uma Abordagem PolyStore. SBBD 2019: 73-84 - [c77]Daniel de Oliveira, Carlos Magno Abreu, Eduardo S. Ogasawara, Eduardo Bezerra, Leonardo Silva de Lima:
A Science Gateway to Support Research in Spectral Graph Theory. SBBD 2019: 217-222 - [c76]Débora B. Pina, Liliane Neves, Aline Paes, Daniel de Oliveira, Marta Mattoso:
Análise de Hiperparâmetros em Aplicações de Aprendizado Profundo por meio de Dados de Proveniência. SBBD 2019: 223-228 - [c75]Daniel de Oliveira, Eduardo Rodrigues Duarte Neto, Serafim Costa, Paulo Roberto Pessoa Amora, Asley Caldas, Marco Horta, Ana Maria de Fillippis, Kary A. C. S. Ocaña, Vânia Maria P. Vidal, Javam C. Machado:
Um Estudo Comparativo de Mecanismos de Privacidade Diferencial sobre um Dataset de Ocorrências do ZIKV no Brasil. SBBD 2019: 253-258 - [c74]Yan Mendes, Regina M. M. Braga, Victor Ströele, Daniel de Oliveira:
Polyflow: A SOA for Analyzing Workflow Heterogeneous Provenance Data in Distributed Environments. SBSI 2019: 49:1-49:8 - [c73]Marcos V. N. Bedo, Paolo Ciaccia, Davide Martinenghi, Daniel de Oliveira:
A k-Skyband Approach for Feature Selection. SISAP 2019: 160-168 - [i3]Gustavo Blanco, Agma J. M. Traina, Caetano Traina Jr., Paulo M. Azevedo-Marques, Ana Elisa Serafim Jorge, Daniel de Oliveira, Marcos V. N. Bedo:
A superpixel-driven deep learning approach for the analysis of dermatological wounds. CoRR abs/1909.06264 (2019) - 2018
- [j28]Wellington Moreira de Oliveira, Daniel de Oliveira, Vanessa Braganholo:
Provenance Analytics for Workflow-Based Computational Experiments: A Survey. ACM Comput. Surv. 51(3): 53:1-53:25 (2018) - [j27]Marcos Vinicius Naves Bedo, Daniel de Oliveira, Agma J. M. Traina, Caetano Traina Jr.:
Beyond Hit-or-Miss: A Comparative Study of Synopses for Similarity Searching. J. Inf. Data Manag. 9(1): 36-51 (2018) - [j26]Thaylon Guedes, Vítor Silva, José J. Camata, Marcos V. N. Bedo, Marta Mattoso, Daniel C. M. de Oliveira:
Towards an Empirical Evaluation of Scientific Data Indexing and Querying. J. Inf. Data Manag. 9(1): 84-93 (2018) - [j25]Vítor Silva, Daniel de Oliveira, Marta Mattoso, Patrick Valduriez:
DfAnalyzer: Runtime Dataflow Analysis of Scientific Applications using Provenance. Proc. VLDB Endow. 11(12): 2082-2085 (2018) - [c72]Lúcio F. D. Santos, Gustavo Blanco, Daniel de Oliveira, Agma J. M. Traina, Caetano Traina Jr., Marcos V. N. Bedo:
Exploring Diversified Similarity with Kundaha. CIKM 2018: 1903-1906 - [c71]Vítor Lourenço, Paulo Mann, Artur Guimaraes, Aline Paes, Daniel de Oliveira:
Towards Safer (Smart) Cities: Discovering Urban Crime Patterns Using Logic-based Relational Machine Learning. IJCNN 2018: 1-8 - [c70]Vítor Silva, Renan Souza, José J. Camata, Daniel de Oliveira, Patrick Valduriez, Alvaro L. G. A. Coutinho, Marta Mattoso:
Capturing Provenance for Runtime Data Analysis in Computational Science and Engineering Applications. IPAW 2018: 183-187 - [c69]Daniel L. Jasbick, Thaylon Guedes, Rodolfo Oliveira, Lúcio F. D. Santos, Daniel de Oliveira, Marcos V. N. Bedo:
VP-Viewer: keeping Track of Your Query from a Vantage Point. SBBD Companion 2018: 5-10 - [c68]Thaylon Guedes, Vítor Silva, Marcos V. N. Bedo, Marta Mattoso, Daniel de Oliveira:
Análise Online de Dados de Proveniência e de Domínio de Aplicações Spark com SAMbA. SBBD Companion 2018: 17-22 - [c67]Daniel Silva Jr., Aline Paes, Esther Pacitti, Daniel de Oliveira:
FReeP: towards Parameter Recommendation in Scientific Workflows using Preference Learning. SBBD 2018: 211-216 - [c66]Patrick Valduriez, Marta Mattoso, Reza Akbarinia, Heraldo Borges, José J. Camata, Alvaro L. G. A. Coutinho, Daniel Gaspar, Noel Moreno Lemus, Ji Liu, Hermano Lustosa, Florent Masseglia, Fabrício Nogueira da Silva, Vítor Silva, Renan Souza, Kary A. C. S. Ocaña, Eduardo S. Ogasawara, Daniel de Oliveira, Esther Pacitti, Fábio Porto, Dennis E. Shasha:
Scientific Data Analysis Using Data-Intensive Scalable Computing: The SciDISC Project. LADaS@VLDB 2018: 1-8 - 2017
- [j24]Lidson Barbosa Jacob, Esteban Clua, Daniel de Oliveira:
Oh Gosh!! Why is this game so hard? Identifying cycle patterns in 2D platform games using provenance data. Entertain. Comput. 19: 65-81 (2017) - [j23]Anderson Marinho, Daniel de Oliveira, Eduardo S. Ogasawara, Vítor Silva, Kary A. C. S. Ocaña, Leonardo Murta, Vanessa Braganholo, Marta Mattoso:
Deriving scientific workflows from algebraic experiment lines: A practical approach. Future Gener. Comput. Syst. 68: 111-127 (2017) - [j22]Vítor Silva, José Leite, José J. Camata, Daniel de Oliveira, Alvaro L. G. A. Coutinho, Patrick Valduriez, Marta Mattoso:
Raw data queries during data-intensive parallel workflow execution. Future Gener. Comput. Syst. 75: 402-422 (2017) - [j21]Luan Teylo, Ubiratam de Paula Junior, Yuri Frota, Daniel de Oliveira, Lúcia M. A. Drummond:
A hybrid evolutionary algorithm for task scheduling and data assignment of data-intensive scientific workflows on clouds. Future Gener. Comput. Syst. 76: 1-17 (2017) - [j20]Wellington Moreira de Oliveira, Kary A. C. S. Ocaña, Daniel de Oliveira, Vanessa Braganholo:
Querying Provenance along with External Domain Data Using Prolog. J. Inf. Data Manag. 8(1): 3-18 (2017) - [j19]Vitor C. Neves, Daniel de Oliveira, Kary A. C. S. Ocaña, Vanessa Braganholo, Leonardo Murta:
Managing Provenance of Implicit Data Flows in Scientific Experiments. ACM Trans. Internet Techn. 17(4): 36:1-36:22 (2017) - [c65]Leonardo Araújo de Jesus, Lúcia M. A. Drummond, Daniel de Oliveira:
Eeny Meeny Miny Moe: Choosing the Fault Tolerance Technique for my Cloud Workflow. CARLA 2017: 321-336 - [c64]Augusto Romeiro, Kary A. C. S. Ocaña, Marcos Kalinowski, Daniel de Oliveira:
SciAgile: Aplicação de Metodologias Ágeis em Experimentos Científicos Baseados em Simulação. CIbSE 2017: 511-524 - [c63]Lucas Tito, Alexandre Estebanez, Andréa Magalhães Magdaleno, Daniel de Oliveira, Marcos Kalinowski:
A Systematic Mapping of Software Requirements Negotiation Techniques. ICEIS (2) 2017: 518-525 - [c62]Thaylon Guedes, Vítor Silva, José J. Camata, Marta Mattoso, Daniel de Oliveira:
Análise de Dados Científicos: uma Análise Comparativa de Dados de Simulações Computacionais. SBBD (Short Papers) 2017: 222-227 - [c61]Isabel Rosseti, Kary A. C. S. Ocaña, Daniel de Oliveira:
Towards preserving results confidentiality in cloud-based scientific workflows. WORKS@SC 2017: 6:1-6:9 - [p3]Rafaelli de C. Coutinho, Yuri Frota, Kary A. C. S. Ocaña, Daniel de Oliveira, Lúcia M. A. Drummond:
Mirror Mirror on the Wall, How Do I Dimension My Cloud After All? Cloud Computing, 2nd Ed. 2017: 27-58 - [p2]Ary Henrique M. de Oliveira, Daniel de Oliveira, Marta Mattoso:
Clouds and Reproducibility: A Way to Go to Scientific Experiments? Cloud Computing, 2nd Ed. 2017: 127-151 - 2016
- [j18]Vítor Silva, Daniel de Oliveira, Patrick Valduriez, Marta Mattoso:
Analyzing related raw data files through dataflows. Concurr. Comput. Pract. Exp. 28(8): 2528-2545 (2016) - [j17]Ji Liu, Esther Pacitti, Patrick Valduriez, Daniel de Oliveira, Marta Mattoso:
Multi-objective scheduling of Scientific Workflows in multisite clouds. Future Gener. Comput. Syst. 63: 76-95 (2016) - [j16]Rafaelli de C. Coutinho, Yuri Frota, Kary A. C. S. Ocaña, Daniel de Oliveira, Lúcia M. A. Drummond:
A Dynamic Cloud Dimensioning Approach for Parallel Scientific Workflows: a Case Study in the Comparative Genomics Domain. J. Grid Comput. 14(3): 443-461 (2016) - [c60]Rafael Mayo-García, José J. Camata, José M. Cela, Danilo Costa, Alvaro L. G. A. Coutinho, Daniel Fernández-Galisteo, Carmen Jiménez, Vadim Kourdioumov, Marta Mattoso, Thomas Miras, José A. Moríñigo, Jorge Navarro, Philippe O. A. Navaux, Daniel de Oliveira, Manuel Aurelio Rodriguez Pascual, Vítor Silva, Renan Souza, Patrick Valduriez:
Enhancing Energy Production with Exascale HPC Methods. CARLA 2016: 233-246 - [c59]Wellington Moreira de Oliveira, Paolo Missier, Kary A. C. S. Ocaña, Daniel de Oliveira, Vanessa Braganholo:
Analyzing Provenance Across Heterogeneous Provenance Graphs. IPAW 2016: 57-70 - [c58]Gustavo Tallarida, Kary A. C. S. Ocaña, Aline Paes, Vanessa Braganholo, Daniel de Oliveira:
Gerência de Incerteza em Bancos de Dados de Proveniência de Workflows de Bioinformática. SBBD 2016: 181-186 - [c57]Vítor N. Lourenço, Paulo Mann, Aline Paes, Daniel Oliveira:
SiAPP: Um Sistema para Análise de Ocorrências de Crimes Baseado em Aprendizado Lógico-Relacional [SiAPP: An Information System for Crime Analytics Based on Logical Relational Learning]. SBSI 2016: 168-175 - [c56]Leonardo S. Ramos, Kary A. C. S. Ocaña, Daniel Oliveira:
Um Sistema de Informação para Gerência de Projetos Científicos baseados em Simulações Computacionais [An IS for Managing Scientific Projects]. SBSI 2016: 216-223 - [c55]Vítor Silva, Leonardo Neves, Renan Souza, Alvaro L. G. A. Coutinho, Daniel de Oliveira, Marta Mattoso:
Integrating Domain-Data Steering with Code-Profiling Tools to Debug Data-Intensive Workflows. WORKS@SC 2016: 59-63 - 2015
- [j15]Rafaelli de C. Coutinho, Lúcia M. A. Drummond, Yuri Frota, Daniel de Oliveira:
Optimizing virtual machine allocation for parallel scientific workflows in federated clouds. Future Gener. Comput. Syst. 46: 51-68 (2015) - [j14]Marta Mattoso, Jonas Dias, Kary A. C. S. Ocaña, Eduardo S. Ogasawara, Flavio Costa, Felipe Horta, Vítor Silva, Daniel de Oliveira:
Dynamic steering of HPC scientific workflows: A survey. Future Gener. Comput. Syst. 46: 100-113 (2015) - [c54]Aline Paes, Daniel de Oliveira:
Running Multi-relational Data Mining Processes in the Cloud: A Practical Approach for Social Networks. CARLA 2015: 3-18 - [c53]Kary A. C. S. Ocaña, Vítor Silva, Daniel de Oliveira, Marta Mattoso:
Data Analytics in Bioinformatics: Data Science in Practice for Genomics Analysis Workflows. e-Science 2015: 322-331 - [c52]Ubiratam de Paula Junior, Lúcia M. A. Drummond, Daniel de Oliveira, Yuri Frota, Valmir Carneiro Barbosa:
Handling flash-crowd events to improve the performance of web applications. SAC 2015: 769-774 - [c51]Rachel Castro, Renan Souza, Vítor Silva, Kary A. C. S. Ocaña, Daniel de Oliveira, Marta Mattoso:
Uma Abordagem para Publicação de Dados de Proveniência de Workflows Científicos na Web Semântica. SBBD (Short Papers) 2015: 111-116 - [c50]Daniel de Oliveira, Vítor Silva, Marta Mattoso:
How Much Domain Data Should Be in Provenance Databases? TaPP 2015 - [i2]Ubiratam de Paula Junior, Daniel de Oliveira, Yuri Frota, Valmir Carneiro Barbosa, Lúcia M. A. Drummond:
Detecting and Handling Flash-Crowd Events on Cloud Environments. CoRR abs/1510.03913 (2015) - 2014
- [j13]João Roberto de Toledo Quadros, Daniel de Oliveira, Ambrozio Queiroz, Eduardo S. Ogasawara, Carlos Schocair:
Towards a UML-based Reference Model for Blended Learning. Int. J. Recent Contributions Eng. Sci. IT 2(3): 15-22 (2014) - [c49]Rafaelli de C. Coutinho, Lúcia M. A. Drummond, Yuri Frota, Daniel de Oliveira, Kary A. C. S. Ocaña:
Evaluating Grasp-based cloud dimensioning for comparative genomics: A practical approach. CLUSTER 2014: 371-379 - [c48]Flavio Costa, Daniel de Oliveira, Marta Mattoso:
Towards an Adaptive and Distributed Architecture for Managing Workflow Provenance Data. eScience Workshops 2014: 79-82 - [c47]Kary A. C. S. Ocaña, Daniel de Oliveira, Vítor Silva, Silvia Benza, Marta Mattoso:
Exploiting the Parallel Execution of Homology Workflow Alternatives in HPC Compute Clouds. ICSOC Workshops 2014: 336-350 - [c46]Flavio Costa, Vítor Silva, Daniel de Oliveira, Kary A. C. S. Ocaña, Marta Mattoso:
Towards Supporting Provenance Gathering and Querying in Different Database Approaches. IPAW 2014: 254-257 - [c45]Wellington Moreira de Oliveira, Daniel de Oliveira, Vanessa Braganholo:
Experiencing PROV-Wf for Provenance Interoperability in SWfMSs. IPAW 2014: 294-296 - [c44]Kary A. C. S. Ocaña, Silvia Benza, Daniel de Oliveira, Jonas Dias, Marta Mattoso:
Exploring Large Scale Receptor-Ligand Pairs in Molecular Docking Workflows in HPC Clouds. IPDPS Workshops 2014: 536-545 - [c43]Vítor Silva, Daniel de Oliveira, Marta Mattoso:
Exploratory Analysis of Raw Data Files through Dataflows. SBAC-PAD (Workshops) 2014: 114-119 - [c42]Wellington Moreira de Oliveira, Vitor C. Neves, Kary A. C. S. Ocaña, Leonardo Murta, Daniel de Oliveira, Vanessa Braganholo:
Captura e Consulta a Dados de Proveniência Retrospectiva Implícita Intra-Atividade. SBBD 2014: 37-46 - [c41]Daniel de Oliveira, Flavio Costa, Vítor Silva, Kary A. C. S. Ocaña, Marta Mattoso:
Debugging Scientific Workflows with Provenance: Achievements and Lessons Learned. SBBD 2014: 67-76 - [c40]