S. Feng, J. Song, X. Bai, D. Wang, and G. Yu, A Web-Based Transformation System for Massive Scientific Data, WISE Workshops, pp.104-114, 2006.
DOI : 10.1007/11906070_10

J. Chamanara and B. König-ries, SciQL, Proceedings of the 5th Ph.D. workshop on Information and knowledge, PIKM '12
DOI : 10.1145/2389686.2389690

P. Prabhu, T. B. Jablin, A. Raman, Y. Zhang, J. Huang et al., A survey of the practice of computational science, State of the Practice Reports on, SC '11, pp.1-1912, 2011.
DOI : 10.1145/2063348.2063374

A. Ailamaki, V. Kantere, and D. Dash, Managing scientific data, Communications of the ACM, vol.53, issue.6, pp.68-78, 2010.
DOI : 10.1145/1743546.1743568

URL : http://dl.acm.org/ft_gateway.cfm?id=1743568&type=pdf

. Matlab, The Language of Technical Computing

G. Chen, S. Wu, R. Gu, Y. Xu, L. Xu et al., Cuicui Song, Data Prefetching for Scientific Workflow Based on Hadoop, Computer and Information Science Studies in Computational Intelligence, vol.2012, issue.429, pp.81-92, 2012.
DOI : 10.1007/978-3-642-30454-5_6

C. E. Rasmussen and C. K. Williams, Gaussian Processes in Machine Learning, 2006.
DOI : 10.1162/089976602317250933

URL : http://mlg.eng.cam.ac.uk/pub/pdf/Ras04.pdf

K. A?man and J. Kocijan, Application of Gaussian processes for black-box modelling of biosystems, ISA Transactions, vol.46, issue.4, pp.443-457, 2007.
DOI : 10.1016/j.isatra.2007.04.001

A. Grancharova, J. Kocijan, and T. A. Johansen, Explicit stochastic predictive control of combustion plants based on Gaussian process models, Automatica, vol.44, issue.6, pp.1621-1631, 2008.
DOI : 10.1016/j.automatica.2008.04.002

URL : http://www.itk.ntnu.no/ansatte/Johansen_Tor.Arne/Paper-Combustion_7.pdf

J. Kocijan, A. Girard, B. Banko, and R. Murray-smith, Dynamic systems identification with Gaussian processes, Mathematical and Computer Modelling of Dynamical Systems, vol.13, issue.4, pp.411-424, 2005.
DOI : 10.1162/089976600300014908

J. Kocijan, Dynamic GP models: an overview and recent developments, ASM'12 Proceedings of the 6th international conference on Applied Mathematics, pp.38-43, 2012.

D. Petelin, J. Kocijan, and A. Grancharova, On-line Gaussian process model for the prediction of the ozone concentration in the air, Proceedings of BAS, vol.64, issue.1, pp.117-124, 2011.

D. Petelin, A. Grancharova, and J. Kocijan, Evolving Gaussian process models for prediction of ozone concentration in the air. Simulation Modelling Practice and Theory, pp.68-80, 2013.

D. Marco and M. Jennings, Universal Meta Data Models, 2004.

A. Ailamaki, V. Kantere, and D. Dash, Managing scientific data, Communications of the ACM, vol.53, issue.6, pp.68-78, 2010.
DOI : 10.1145/1743546.1743568

URL : http://dl.acm.org/ft_gateway.cfm?id=1743568&type=pdf