Supervision : Patrick BRÉZILLON

Context-oriented Scientific Workflow and its Application

The lack of flexibility is an inhibitor in the use of scientific workflow (SWF) systems to transform hypotheses into scientific discoveries.However, notable absences of methodology for modeling SWF in a uniform representation are seen , which results in the lack of user-oriented learning processes. A real use of SWF requires the introduction of the concept of “context”. Current failures are attributed to the lack of explicitness of context in SWF models, the insufficiency in making adaptive decisions, the incomplete SWF sharing mechanism. To address these problems, we proposed a Context-oriented Framework for Scientific WorkFlow (CoF4SWF) to make contexts explicit by Contextual Graphs in SWF lifecycle. We implemented CoF4SWF methodology by a functional prototype called Context-oriented SWF (CxSWF). Moreover, CxSWF prototype was testified through a real world application “virtual screening research on avian influenza H5N1 virus”. Finally, the results from twofold evaluation processes illustrated that initial hypotheses of the virtual screening application have been reached in principle. The main contributions of the thesis are: (i) A context-oriented methodology for studying SWF modeling; (ii) The identification of three approaches of making contexts explicit in SWF models; (iii) The investigation on the role of contextual graphs in SWF modeling. The originality of the thesis stands on: (1) Representing and modeling SWF flexibility with its contexts to enable adaptive decision making; (2) Making contexts as the status of knowledge to be built up for practice learning; and 3) Sharing of SWF model with its contexts as a complementary output for scientific discoveries.

2010-2018 Publications

• 2018
  • L. Chen, Th.‑M.‑T. Nguyen, G. PAN, J. JAKUBOWICZ, L. Liu, X. Fan, J. Li, Ch. Wang : “Complementary Base Station Clustering for Cost-Effective and Energy-Efficient Cloud-RAN”, Proceedings of the 14^th IEEE International Conference on Ubiquitous Intelligence and Computing (UIC 2017), San Francisco, CA, United States, (ISBN: 978-1-5386-0435-9) (2018)
• 2017
  • L. Chen, X. Fan, L. Wang, D. Zhang, Zh. Yu, J. Li, Th.‑M.‑T. Nguyen, G. PAN, Ch. Wang : “RADAR: road obstacle identification for disaster response leveraging cross-domain urban data”, Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, vol. 1 (4), pp. articleno.:130,pp1-23, (ACM) (2017)
• 2011
  • X. Fan : “Context-oriented Scientific Workflow and its Application”, thesis, phd defence 11/07/2011, supervision Brézillon, Patrick (2011)
  • X. Fan, P. Brézillon, R. Zhang, L. Li : “Contextualizing workflow in cooperative design”, 2011 15^th International Conference on Computer Supported Cooperative Work in Design, Lausanne, Switzerland, pp. 17-22, (IEEE) (2011)
  • X. Fan, P. Brézillon, R. Zhang, L. Li : “A context-based framework for improving decision making in scientific workflow”, 3^rd International Conference on Computer Research and Development, vol. 2, Shanghai, China, pp. 15-19, (IEEE Computer Society) (2011)
  • X. Fan, P. Brézillon, R. Zhang, L. Li : “Making context explicit towards decision support for a flexible scientific workflow system”, 2011 Workshop on Human-Centered Processes, vol. 696, CEUR-WS, Genoa, Italy, pp. 3-9, (CEUR) (2011)
• 2010
  • X. Fan, P. Brézillon, R. Zhang, L. Li : “Context-oriented scientific workflow system and its application in virtual screening”, Bridging the Socio-Technical Gap in Decision Support Systems. Challenges for the next Decade., Lisbon, Portugal, pp. 335-345 (2010)