Abstract
The G-Lorep project of the European Chemistry Thematic Network (ECTN), based on a federation of distributed repositories of Molecular Science Learning Objects, leverages at present a “hybrid” centralized/distributed architecture in which the central node hosts a shared database. The shared database deals only with the task of managing metadata to the end of synchronizing the information made available to the federation members at regular time intervals. In order to avoid missed synchronization (in the case of the failure of the central node) a scheme distributing the nodes, adopting a PaaS (Platform as a Service) strategy and ensuring network security, is implemented and related performances are evaluated. The efficiency of the developed new architecture of the federation is measured for a set of Molecular Science Learning Objects developed within some European distributed computing initiatives and adopted for the Theoretical Chemistry and Computational Modeling European Master and Doctoral joint courses. The evolution of the proposed Learning Objects is discussed also in view of the development of the Molecular Simulator Enabled Cloud Services (MOSEX) pilot project.
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References
Tasso, S., Pallottelli, S., Bastianini, R., Lagana, A.: Federation of distributed and collaborative repositories and its application on science learning objects. In: Murgante, B., Gervasi, O., Iglesias, A., Taniar, D., Apduhan, B.O. (eds.) ICCSA 2011. LNCS, vol. 6784, pp. 466–478. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-21931-3_36
Tasso, S., Pallottelli, S., Ferroni, M., Bastianini, R., Laganà, A.: Taxonomy management in a federation of distributed repositories: a chemistry use case. In: Murgante, B., et al. (eds.) ICCSA 2012. LNCS, vol. 7333, pp. 358–370. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-31125-3_28
Tasso, S., Pallottelli, S., Rui, M., Laganá, A.: Learning objects efficient handling in a federation of science distributed repositories. In: Murgante, B., et al. (eds.) ICCSA 2014. LNCS, vol. 8579, pp. 615–626. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-09144-0_42
Pallottelli, S., Tasso, S., Rui, M., Laganà, A., Kozaris, I.: Exchange of learning objects between a learning management system and a federation of science distributed repositories. In: Gervasi, O., et al. (eds.) ICCSA 2015. LNCS, vol. 9156, pp. 371–383. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-21407-8_27
Laganà, A., Gervasi, O., Tasso, S., Perri, D., Franciosa, F.: The ECTN virtual education community prosumer model for promoting and assessing chemical knowledge. In: Gervasi, O., et al. (eds.) ICCSA 2018. LNCS, vol. 10964, pp. 533–548. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-95174-4_42
Laganà, A., Terstyanszky, G., Krüger, J.: Open molecular science for the open science cloud. In: Gervasi, O., et al. (eds.) ICCSA 2017. LNCS, vol. 10406, pp. 29–43. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-62398-6_3
Laganà, A., et al.: From computer assisted to grid empowered teaching and learning activities in higher level chemistry education. In: Eilks, I., Byers, B. (eds.) Innovative Methods of Teaching and Learning Chemistry in Higher Education Royal Society of Chemistry (2009). ISBN 978-1-84755-958-6
Foster, I., Kesselman, C. (eds.): The Grid: Blueprint for a New Computing Infrastructure. Morgan Kaufmann Publishers, San Francisco (1999)
Foster, I., Kesselman, C., Tuecke, S.: The anatomy of the grid: enabling scalable virtual organisations. Int. J. Supercomput. Appl. 15(3), 200–222 (2001)
Storchi, L., Tarantelli, F., Laganà, A.: Computing molecular energy surfaces on a grid. In: Gavrilova, M., et al. (eds.) ICCSA 2006. LNCS, vol. 3980, pp. 675–683. Springer, Heidelberg (2006). https://doi.org/10.1007/11751540_71
Gervasi, O., Laganà, A.: SIMBEX: a portal for the a priori simulation of crossed beam experiments. Future Gener. Comput. Syst. 20(5), 703–716 (2004)
Laganà, A., Costantini, A., Gervasi, O., Faginas Lago, N., Manuali, C., Rampino, S.: COMPCHEM: progress towards GEMS a grid empowered molecular simulator and beyond. J. Grid Comput. 8(4), 571–586 (2010)
Rampino, S., Pirani, F., Laganà, A., Garcia, E.: A study of the impact of long range interactions on the N + N\(_2\) reactivity using GEMS. Int. J. Web Grid Serv. 6, 196–212 (2010)
Laganà, A., Parker, G.A.: Chemical Reactions Basic Theory and Computing. Springer, Heidelberg (2018). ISBN 978-3-319-62355-9
Moriconi, A., Pasqua, S., Squarta, G., Laganà, A.: Chemical reactions learning objects. VIRT&L-COMM.14.2018.4. http://services.chm.unipg.it/ojs/index.php/virtlcomm/article/view/191
Franzoni, V., Tasso, S., Pallottelli, S., Perri, D.: Sharing linkable learning objects between a content management system and a learning management system with the use of metadata and a taxonomy assistant for categorization. LNCS (in press)
Franzoni, V., Mencacci, M., Mengoni, P., Milani, A.: Semantic heuristic search in collaborative networks: measures and contexts. In: Proceedings - 2014 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Workshops, WI-IAT 2014, vol. 1, pp. 187–217 (2014). https://doi.org/10.1109/WI-IAT.2014.27
Tasso, S., Gervasi, O., Locchi, A., Sabbatini, F.: Hahai: computational thinking in primary schools. In: Misra, S., et al. (eds.): ICCSA 2019, LNCS, vol. 11620, pp. 287–298 (2019, in press)
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Tasso, S., Pallottelli, S., Gervasi, O., Sabbatini, F., Franzoni, V., Laganà, A. (2019). Cloud and Local Servers for a Federation of Molecular Science Learning Object Repositories. In: Misra, S., et al. Computational Science and Its Applications – ICCSA 2019. ICCSA 2019. Lecture Notes in Computer Science(), vol 11624. Springer, Cham. https://doi.org/10.1007/978-3-030-24311-1_26
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