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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 (UFF), Institute of Computing, Niterói, RJ, Brazil
- affiliation (PhD 2012): Federal University of Rio de Janeiro (UFRJ), Rio de Janeiro, RJ, Brazil
Other persons with the same name
- Daniel de Oliveira 0002 — Federal University of Santa Catarina, Department of Production and Systems Engineering, Brazil
- Daniel Oliveira 0002
![[0000-0002-8752-3992]](https://dblp1.uni-trier.de/img/orcid-mark.12x12.png "0000-0002-8752-3992")
(aka: Daniel A. G. de Oliveira, Daniel Alfonso Gonçalves de Oliveira) — Federal University of Parana, Curitiba, Brazil - Daniel Oliveira 0003 (aka: Daniel José da Cunha Oliveira) — University of Minho, Centro ALGORITMI, Portugal
- Daniel Oliveira 0004 — University of Beira Interior, Covilha, Portugal
- Daniel Oliveira 0005 (aka: Daniel Tenório Martins de Oliveira) — Pontifical Catholic University of Rio de Janeiro, Informatics Department, Brazil
- Daniel Oliveira 0006 — Institute of Electronics and Telematics Engineering of Aveiro (IEETA), Portugal
- Daniel Oliveira 0007 — Federal University of Amazonas, Manaus, Brasil
- Daniel Oliveira 0008 — Coimbra Polytechnic - ISEC, Portugal
- Daniel Oliveira 0009 — Federal University of Bahia, Salvador, Brazil
- Daniel Oliveira 0010 — Fluminense Federal University, Niteroi, RJ, Brazil
- Daniel Oliveira 0011 — Instituto Superior Técnico, Department of Mathematics, Lisbon, Portugal
- Daniel Oliveira 0012 — University of Minho, Department of Information Systems, Braga, Portugal
- Daniel Oliveira 0013 — INESC-ID, Lisbon, Portugal (and 1 more)
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2020 – today
- 2023
[j65]Alan L. Nunes, Alba C. M. A. Melo, Claude Tadonki, Cristina Boeres, Daniel de Oliveira, Lúcia Maria de Assumpção Drummond:
Optimizing computational costs of Spark for SARS-CoV-2 sequences comparisons on a commercial cloud. Concurr. Comput. Pract. Exp. 35(18) (2023)- [j64]Claudio V. Ribeiro, Aline Paes, Daniel de Oliveira:
AIS-based maritime anomaly traffic detection: A review. Expert Syst. Appl. 231: 120561 (2023) - [j63]Daniel L. Jasbick, Lúcio F. D. Santos, Paulo M. Azevedo-Marques, Agma J. M. Traina, Daniel de Oliveira, Marcos V. N. Bedo:
Pushing diversity into higher dimensions: The LID effect on diversified similarity searching. Inf. Syst. 114: 102166 (2023) - [c111]Ygor Rolim, Danielly Alves, Flávia Clemente, Daniel de Oliveira:
NewsCollab: Fostering Data-driven Journalism with Crowdsourcing. CSCWD 2023: 1008-1013 - [c110]Vinícius Souza, Luiz Olmes Carvalho, Daniel de Oliveira, Marcos V. N. Bedo, Lúcio F. D. Santos:
Adding Result Diversification to kNN-Based Joins in a Map-Reduce Framework. DEXA (1) 2023: 68-83 - [c109]Lyncoln S. de Oliveira, Liliane N. O. Kunstmann, Débora B. Pina, Daniel de Oliveira, Marta Mattoso:
PINNProv: Provenance for Physics-Informed Neural Networks. SBAC-PADW 2023: 16-23 - [c108]Luiz Gustavo Dias, Bruno Lopes, Daniel de Oliveira:
MAESTRO: Uma Abordagem para a Composição e Análise de Workflows Baseados em Scripts por Meio de Ontologias. SBBD 2023: 256-268 - [c107]Raffael M. Paranhos, Marcos Lage, Daniel de Oliveira:
Uso de Grafos de Proveniência para Análise Temporal de Uso do Solo em Centros Urbanos: uma Abordagem Prática. SBBD 2023: 457-462 - [c106]Débora B. Pina, Adriane Chapman, Daniel de Oliveira, Marta Mattoso:
Deep Learning Provenance Data Integration: a Practical Approach. WWW (Companion Volume) 2023: 1542-1550 - [i6]Daniel da Silva Junior, Paulo Roberto dos S. Corval, Aline Paes, Daniel de Oliveira:
Datasets for Portuguese Legal Semantic Textual Similarity: Comparing weak supervision and an annotation process approaches. CoRR abs/2306.00007 (2023) - [i5]Carolina Veiga Ferreira de Souza, Suzanna Maria Bonnet, Daniel de Oliveira, Márcio Cataldi, Fabio Miranda, Marcos Lage:
ProWis: A Visual Approach for Building, Managing, and Analyzing Weather Simulation Ensembles at Runtime. CoRR abs/2308.05019 (2023) - 2022
- [j62]Murilo B. Stockinger, Marcos A. Guerine, Ubiratam de Paula Junior, Filipe Santiago, Yuri Frota, Isabel Rosseti, Alexandre Plastino, Daniel de Oliveira:
A Provenance-based Execution Strategy for Variant GPU-accelerated Scientific Workflows in Clouds. J. Grid Comput. 20(4): 36 (2022) - [j61]Bruno Cunha Sá, Gustavo Muller, Maicon Banni, Wagner Santos, Marcos Lage, Isabel Rosseti, Yuri Frota, Daniel de Oliveira:
PolRoute-DS: a Crime Dataset for Optimization-based Police Patrol Routing. J. Inf. Data Manag. 13(1) (2022) - [j60]Lorenna Christ'na Nascimento, Rodolfo P. Chagas, Marcos Lage, Daniel de Oliveira:
Beyond Click-and-View: a Comparative Study of Data Management Approaches for Interactive Visualization. J. Inf. Data Manag. 13(3) (2022) - [j59]Maristela Holanda, Daniel de Oliveira:
Editorial. J. Inf. Data Manag. 13(4) (2022) - [c105]Maicon Banni, Isabel Rosseti, Daniel de Oliveira:
HURRICANE: um Serviço para Gerência de Dados de Aplicações de Cidades Inteligentes. SBBD 2022: 151-163 - [c104]Annie Amorim, Nils Murrugarra-Llerena, Vítor Silva, Daniel de Oliveira, Aline Paes:
Modelagem de Tópicos em Textos Curtos: uma Avaliação Experimental. SBBD 2022: 254-266 - [c103]Lucas Bertelli, Victor Ströele, Javam C. Machado, Daniel de Oliveira:
Privacidade Diferencial em Sistemas Polystore: uma Abordagem Prática. SBBD 2022: 279-291 - [c102]Gustavo Decarlo, Daniel de Oliveira, Fábio Porto:
Otimização de Dataflows em Frameworks de Big Data por meio do Reúso de Dados. SBBD 2022: 367-372 - [c101]Lyncoln S. de Oliveira, Rômulo M. Silva, Liliane N. O. Kunstmann, Débora B. Pina, Daniel de Oliveira, Alvaro L. G. A. Coutinho, Marta Mattoso:
Dados de proveniência para redes neurais guiadas pela Física: o caso da equação eikonal. SBBD 2022: 373-378 - [c100]João Loureiro, Daniel de Oliveira:
ORBITER: um Arcabouço para Implantação Automática de Aplicações Big Data em Arquiteturas Serverless. SBBD 2022: 379-384 - [c99]Nicolas Atmatzides, Marcos V. N. Bedo, Daniel de Oliveira:
Adoção de SGBDs NoSQL em Empresas Brasileiras: um Levantamento Preliminar. SBBD 2022: 385-390 - 2021
- [j58]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) - [j57]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) - [j56]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) - [j55]Maristela Terto de Holanda, Daniel Cardoso Moraes de Oliveira, Moacir Antonelli Ponti:
Frontmatter. J. Inf. Data Manag. 12(1) (2021) - [j54]Maristela Terto de Holanda, Daniel Cardoso Moraes de Oliveira, Moacir Antonelli Ponti:
Editorial. J. Inf. Data Manag. 12(1) (2021) - [j53]Maristela Terto de Holanda, Daniel Cardoso Moraes de Oliveira, Ronaldo dos Santos Mello:
Frontmatter. J. Inf. Data Manag. 12(2) (2021) - [j52]Maristela Terto de Holanda, Daniel Cardoso Moraes de Oliveira, Ronaldo dos Santos Mello:
Editorial. J. Inf. Data Manag. 12(2) (2021) - [j51]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) - [j50]Leonardo S. Ramos, Fábio Porto, Daniel de Oliveira:
Managing Hypothesis of Scientific Experiments with PhenoManager. J. Inf. Data Manag. 12(2) (2021) - [j49]Maristela Terto de Holanda, Daniel Cardoso Moraes de Oliveira, Fábio Porto:
Frontmatter. J. Inf. Data Manag. 12(3) (2021) - [j48]Maristela Terto de Holanda, Daniel Cardoso Moraes de Oliveira, Fábio Porto:
Editorial. J. Inf. Data Manag. 12(3) (2021) - [j47]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) - [j46]Maristela Terto de Holanda, Daniel Cardoso Moraes de Oliveira, Thales Sehn Körting:
Frontmatter. J. Inf. Data Manag. 12(4) (2021) - [j45]Maristela Terto de Holanda, Daniel Cardoso Moraes de Oliveira, Thales Sehn Körting:
Editorial. J. Inf. Data Manag. 12(4) (2021) - [j44]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) - [j43]Maristela Terto de Holanda, Daniel Cardoso Moraes de Oliveira, Ricardo da Silva Torres:
Frontmatter. J. Inf. Data Manag. 12(5) (2021) - [j42]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) - [j41]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) - [j40]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) - [j39]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
- [j38]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) - [j37]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) - [j36]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) - [j35]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) - [j34]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) - [j33]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) - [j32]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) - [j31]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, ISBN 978-3-031-00744-6 - [j29]Marcos A. 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 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 Alves de 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]