H. Shen, Interactive notebooks: Sharing the code, Nature, vol.515, issue.7525, pp.151-152, 2014.
DOI : 10.1038/515151a

M. Ragan-kelley, F. Perez, B. Granger, T. Kluyver, P. Ivanov et al., The jupyter/ipython architecture: a unified view of computational research, from interactive exploration to communication and publication, p.7

A. Tsaregorodtsev, M. Bargiotti, N. Brook, A. C. Ramo, G. Castellani et al., DIRAC: a community grid solution, Journal of Physics: Conference Series, vol.119, issue.6, 2008.
DOI : 10.1088/1742-6596/119/6/062048
URL : https://hal.archives-ouvertes.fr/in2p3-00186997

M. Hedges, A. Hasan, and T. Blanke, Management and preservation of research data with iRODS, Proceedings of the ACM first workshop on CyberInfrastructure: information management in eScience , CIMS '07, pp.17-22
DOI : 10.1145/1317353.1317358

C. Pradal, S. Dufour-kowalski, F. Boudon, C. Fournier, and C. Godin, OpenAlea: a visual programming and component-based software platform for plant modelling, Functional Plant Biology, vol.35, issue.10, pp.751-760, 2008.
DOI : 10.1071/FP08084

J. Goecks, A. Nekrutenko, and J. Taylor, Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences, Genome Biology, vol.11, issue.8, pp.11-86, 2010.
DOI : 10.1186/gb-2010-11-8-r86

B. Ludäscher and I. Altintas, On providing declarative design and programming constructs for scientific workflows based on process networks, 2003.

C. Pradal, C. Fournier, P. Valduriez, and S. Cohen-boulakia, OpenAlea, Proceedings of the 27th International Conference on Scientific and Statistical Database Management, SSDBM '15, p.11
DOI : 10.1145/2791347.2791365
URL : https://hal.archives-ouvertes.fr/hal-00831801

V. Curcin and M. Ghanem, Scientific workflow systems - can one size fit all?, 2008 Cairo International Biomedical Engineering Conference, pp.1-9
DOI : 10.1109/CIBEC.2008.4786077

A. A. Lahcen and D. Parigot, A Lightweight Middleware for Developing P2P Applications with Component and Service-Based Principles, 2012 IEEE 15th International Conference on Computational Science and Engineering, pp.9-16
DOI : 10.1109/ICCSE.2012.12
URL : https://hal.archives-ouvertes.fr/lirmm-00757105

E. Ogasawara, J. Dias, D. Oliveira, F. Porto, P. Valduriez et al., An algebraic approach for data-centric scientific workflows, Proc. of VLDB Endowment, pp.1328-1339, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00640431

D. Hardt, The oauth 2.0 authorization framework, 2012.
DOI : 10.17487/rfc6749

P. Guo, CDE: A Tool for Creating Portable Experimental Software Packages, Computing in Science & Engineering, vol.14, issue.4, pp.32-35, 2012.
DOI : 10.1109/MCSE.2012.36

G. Sandve, A. Nekrutenko, J. Taylor, and E. Hovig, Ten Simple Rules for Reproducible Computational Research, PLoS Computational Biology, vol.8, issue.10
DOI : 10.1371/journal.pcbi.1003285

L. Moreau and P. Missier, Prov-dm: The prov data model, 2013.

J. D. Hunter, Matplotlib: A 2D Graphics Environment, Computing in Science & Engineering, vol.9, issue.3, pp.90-95, 2007.
DOI : 10.1109/MCSE.2007.55

E. Navon, O. Miller, and A. Averbuch, Color image segmentation based on adaptive local thresholds, Image and Vision Computing, vol.23, issue.1, pp.69-85, 2005.
DOI : 10.1016/j.imavis.2004.05.011

S. Sural, G. Qian, and S. Pramanik, Segmentation and histogram generation using the HSV color space for image retrieval, Proceedings. International Conference on Image Processing, p.589
DOI : 10.1109/ICIP.2002.1040019

D. Comaniciu and P. Meer, Mean shift: A robust approach toward feature space analysis, Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.24, pp.603-619, 2002.

J. Liu, E. Pacitti, P. Valduriez, and M. Mattoso, A Survey of Data-Intensive Scientific Workflow Management, Journal of Grid Computing, vol.1, issue.Webserver-Issue, pp.1-37, 2015.
DOI : 10.1007/s10723-015-9329-8
URL : https://hal.archives-ouvertes.fr/lirmm-01144760

I. Foster, Y. Zhao, I. Raicu, and S. Lu, Cloud Computing and Grid Computing 360-Degree Compared, 2008 Grid Computing Environments Workshop, pp.1-10, 2008.
DOI : 10.1109/GCE.2008.4738445

J. Yu and R. Buyya, A Taxonomy of Workflow Management Systems for Grid Computing, Journal of Grid Computing, vol.15, issue.5???6, pp.171-200, 2005.
DOI : 10.1007/s10723-005-9010-8

G. C. Fox and D. Gannon, Workflow in grid systems, 2006.

M. T. Ozsu and P. Valduriez, Principles of distributed database systems, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00483354

F. Tardieu and R. Tuberosa, Dissection and modelling of abiotic stress tolerance in plants, Current Opinion in Plant Biology, vol.13, issue.2, pp.206-212, 2010.
DOI : 10.1016/j.pbi.2009.12.012

R. T. Furbank and M. Tester, Phenomics ??? technologies to relieve the phenotyping bottleneck, Trends in Plant Science, vol.16, issue.12, pp.635-644, 2011.
DOI : 10.1016/j.tplants.2011.09.005

D. Houle, D. R. Govindaraju, and S. Omholt, Phenomics: the next challenge, Nature Reviews Genetics, vol.11, issue.113, pp.855-866, 2010.
DOI : 10.1038/nrg2897

F. Fiorani and U. Schurr, Future Scenarios for Plant Phenotyping, Annual Review of Plant Biology, vol.64, issue.1, pp.267-291, 2013.
DOI : 10.1146/annurev-arplant-050312-120137

S. Dhondt, N. Wuyts, and D. Inzé, Cell to whole-plant phenotyping: the best is yet to come, Trends in Plant Science, vol.18, issue.8, pp.428-439, 2013.
DOI : 10.1016/j.tplants.2013.04.008

D. Turi, P. Missier, C. Goble, D. De-roure, and T. Oinn, Taverna workflows: Syntax and semantics, in: e-Science and Grid Computing, pp.441-448

P. M. Kelly, P. D. Coddington, and A. L. Wendelborn, Lambda calculus as a workflow model, Concurrency and Computation: Practice and Experience, vol.8, issue.1, pp.1999-2017, 2009.
DOI : 10.1002/cpe.1448

J. Brandt, M. Bux, and U. Leser, A functional language for large scale scientific data analysis, BeyongMR, ICDT/EDBT Workshop

J. Montagnat, B. Isnard, T. Glatard, K. Maheshwari, and M. B. Fornarino, A data-driven workflow language for grids based on array programming principles, Proceedings of the 4th Workshop on Workflows in Support of Large-Scale Science, WORKS '09, p.7
DOI : 10.1145/1645164.1645171
URL : https://hal.archives-ouvertes.fr/hal-00677806

D. Rogers, I. Harvey, T. Truong-huu, K. Evans, T. Glatard et al., Bundle and Pool Architecture for Multi-Language, Robust, Scalable Workflow Executions, Journal of Grid Computing, vol.5, issue.1, pp.457-480, 2013.
DOI : 10.1007/s10723-013-9267-2
URL : https://hal.archives-ouvertes.fr/hal-00832221

S. Cohen-boulakia and U. Leser, Search, adapt, and reuse, ACM SIGMOD Record, vol.40, issue.2, pp.6-16, 2011.
DOI : 10.1145/2034863.2034865
URL : https://hal.archives-ouvertes.fr/inria-00638043

Z. Bao, S. Cohen-boulakia, S. B. Davidson, A. Eyal, and S. Khanna, Differencing Provenance in Scientific Workflows, 2009 IEEE 25th International Conference on Data Engineering, pp.808-819
DOI : 10.1109/ICDE.2009.103
URL : https://hal.archives-ouvertes.fr/inria-00542336

P. Groth, M. Luck, and L. Moreau, A Protocol for Recording Provenance in Service-Oriented Grids, Principles of Distributed Systems, pp.124-139, 2005.
DOI : 10.1007/11516798_9

O. Biton, S. Cohen-boulakia, S. B. Davidson, and C. S. Hara, Querying and Managing Provenance through User Views in Scientific Workflows, 2008 IEEE 24th International Conference on Data Engineering, pp.1072-1081, 2008.
DOI : 10.1109/ICDE.2008.4497516

S. Cohen-boulakia, J. Chen, P. Missier, C. Goble, A. Williams et al., Distilling structure in Taverna scientific workflows: a refactoring approach, BMC Bioinformatics, vol.15, issue.Suppl 1, pp.15-27, 2014.
DOI : 10.1186/1471-2105-15-S1-S12
URL : https://hal.archives-ouvertes.fr/hal-00926827

A. Chapman and H. Jagadish, Issues in building practical provenance systems, IEEE Data Eng. Bull, vol.30, pp.38-43, 2007.

F. S. Chirigati, D. Shasha, and J. Freire, ReproZip, Proceedings of the 2016 International Conference on Management of Data, SIGMOD '16
DOI : 10.1145/2882903.2899401