, Chiaroscuro: Transparency and Privacy for Massive Personal Time-Series Clustering. SIGMOD Conference, pp.779-794, 2015.
Query processing in multistore systems: an overview, International Journal of Cloud Computing, vol.5, issue.4, pp.309-346, 2016. ,
DOI : 10.1504/IJCC.2016.080903
URL : https://hal.archives-ouvertes.fr/hal-01289759
Data-Intensive Scalable Computing for Scientific Applications, Computing in Science & Engineering, vol.13, issue.6, pp.25-33, 2011. ,
DOI : 10.1109/MCSE.2011.73
In situ visualization and data analysis for turbidity currents simulation, Computers & Geosciences, vol.110, pp.23-31, 2018. ,
DOI : 10.1016/j.cageo.2017.09.013
URL : https://hal.archives-ouvertes.fr/lirmm-01620127
, Spatial Sequential Pattern Mining for Seismic Data. SBBD Conference, 2016.
Sequence Mining in Spatial-Time Series (Master Degree Dissertation, CEFET/RJ, 2017. ,
Computational Science and Big Data: Where are We Now? XLDB Workshop, 2014. ,
Kleese van Dam. Data-Intensive Science, 2013. ,
, Detecção de Anomalias no Transporte Rodoviário Urbano, Brazilian Symposium on Databases (SBBD), 2017.
Data science and prediction, Communications of the ACM, vol.56, issue.12, pp.64-73, 2013. ,
DOI : 10.1145/2500499
A proposal to apply inductive logic programming to self-healing problem in grid computing: How will it work?, Concurrency and Computation: Practice and Experience, vol.2, issue.2, pp.2118-2135, 2011. ,
DOI : 10.1007/BF00114265
Big Data, Simulations and HPC Convergence, 2016. ,
DOI : 10.1109/SC.2012.55
TARDIS: Optimal Execution of Scientific Workflows in Apache Spark, Int. Conf. on Big Data Analytics and Knowledge Discovery, vol.21, issue.5, pp.74-87, 2017. ,
DOI : 10.1007/s00778-012-0280-z
URL : https://hal.archives-ouvertes.fr/lirmm-01620060
The Fourth Paradigm ??? Data-Intensive Scientific Discovery, 2009. ,
DOI : 10.1007/978-3-642-33299-9_1
URL : https://digital.library.unt.edu/ark:/67531/metadc31516/m2/1/high_res_d/4th_paradigm_book_complete_lr.pdf
Enabling Data Recommendation in Scientific Workflow Based on Provenance, 2013 8th ChinaGrid Annual Conference, 2013. ,
DOI : 10.1109/ChinaGrid.2013.25
, Pre-processing and Indexing Techniques for Constellation Queries in Big Data. Int. Conf. on Big Data Analytics and Knowledge Discovery (DaWaK), pp.164-172, 2017.
Dynamic Worlkload-based Partitioning Algorithms for Continuously Growing Databases. Trans on Large-Scale Data and Knowledge- Centered Systems, pp.105-128, 2013. ,
Multi-objective scheduling of Scientific Workflows in multisite clouds, Future Generation Computer Systems, vol.63, pp.76-95, 2016. ,
DOI : 10.1016/j.future.2016.04.014
URL : https://hal.archives-ouvertes.fr/lirmm-01342203
Scientific Workflow Scheduling with Provenance Data in a Multisite Cloud, Trans. on Large-Scale Data-and Knowledge-Centered Systems (TLDKS), pp.80-112, 2017. ,
DOI : 10.1109/IPDPS.2007.370305
URL : https://hal.archives-ouvertes.fr/lirmm-01620224
, Parallel Computation of PDFs on Big Spatial Data Using Spark, 2018.
TARS: Na Extension of the Multi-dimensional Array Model, ER FORUM ? Conceptual Modeling, 2017. ,
, Towards In-transit Analysis on Supercomputing Environments, 2018.
Time series motif discovery: dimensions and applications, Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, vol.130, issue.2, pp.152-159, 2014. ,
DOI : 10.1111/j.1570-7458.2008.00812.x
Adaptive Normalization: A novel data normalization approach for non-stationary time series, The 2010 International Joint Conference on Neural Networks (IJCNN), pp.1-8, 2010. ,
DOI : 10.1109/IJCNN.2010.5596746
An Algebraic Approach for Datacentric Scientific Workflows, Proceedings of the VLDB Endowment (PVLDB), pp.1328-1339, 2011. ,
URL : https://hal.archives-ouvertes.fr/hal-00640431
Evaluation of methods to integrate analysis into a large-scale shock shock physics code, Proceedings of the 28th ACM international conference on Supercomputing, ICS '14, pp.83-92, 2014. ,
DOI : 10.1145/2597652.2597668
Principles of Distributed Database Systems ? Third Edition, 2011. ,
El Dick: P2P Techniques for Decentralized Applications. Synthesis Lectures on Data Management, 2012. ,
Managing hot metadata for scientific workflows on multisite clouds, 2016 IEEE International Conference on Big Data (Big Data), pp.390-397, 2016. ,
DOI : 10.1109/BigData.2016.7840628
URL : https://hal.archives-ouvertes.fr/hal-01395715
, Point Pattern Search in Big Data. Int. Conf. on Scientific and Statistical Database Management (SSDBM), 2018.
Logical and Relational Learning: From ILP to MRDM (Cognitive Technologies, 2008. ,
DOI : 10.1007/978-3-540-68856-3
Profile Diversity for Query Processing using User Recommendations, Information Systems, vol.48, pp.44-63, 2015. ,
DOI : 10.1016/j.is.2014.09.001
URL : https://hal.archives-ouvertes.fr/lirmm-01079523
Raw data queries during data-intensive parallel workflow execution, Future Generation Computer Systems, vol.75, pp.402-422, 2017. ,
DOI : 10.1016/j.future.2017.01.016
URL : https://hal.archives-ouvertes.fr/lirmm-01445219
DfAnalyzer: Runtime Dataflow Analysis of Scientific Applications using Provenance, Proceedings of the VLDB Endowment, 2018. ,
URL : https://hal.archives-ouvertes.fr/lirmm-01867887
Data Quality Prediction in Scientific Workflows, 2018. ,
Spark Scalability Analysis in a Scientific Workflow, Best Paper Award, 2017. ,
URL : https://hal.archives-ouvertes.fr/lirmm-01620161
Tracking of Online Parameter Fine-tuning in Scientific Workflows, Support of Large-Scale Science (WORKS), ACM/IEEE Supercomputing Conference, 2017. ,
URL : https://hal.archives-ouvertes.fr/lirmm-01620974
Data-intensive HPC: opportunities and challenges. Big Data and Extreme-scale computing (BDEC), 2015. ,
URL : https://hal.archives-ouvertes.fr/lirmm-01184018