Model-Driven Engineering; Analytics; Big Data; Temporal Data; Internet of Things
Abstract :
[en] The conviction that big data analytics is a key for the success of modern businesses is growing deeper, and the mobilisation of companies into adopting it becomes increasingly important. Big data integration projects enable companies to capture their relevant data, to efficiently store it, turn
it into domain knowledge, and finally monetize it. In this context, historical data, also called temporal data, is becoming increasingly available and delivers means to analyse the history of applications, discover temporal patterns, and predict future trends. Despite the fact that most data that today’s applications are dealing with is inherently temporal current approaches, methodologies, and environments for developing these applications don’t provide sufficient support for handling time. We
envision that Model-Driven Engineering (MDE) would be an appropriate ecosystem for a seamless and orthogonal integration of time into domain modelling and processing. In this paper, we investigate the state-of-the-art in MDE techniques and tools in order to identify the missing bricks for raising time-awareness in MDE and outline research directions in this emerging domain.
Disciplines :
Computer science
Author, co-author :
Benelallam, Amine; University of Rennes 1, IRISA, INRIA Centre Rennes
Hartmann, Thomas ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Mouline, Ludovic ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Fouquet, François ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Bourcier, Johann; University of Rennes 1, IRISA, INRIA Centre Rennes
Barais, Olivier; University of Rennes 1, IRISA, INRIA Centre Rennes
Le Traon, Yves ; University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC)
External co-authors :
yes
Language :
English
Title :
Raising Time Awareness in Model-Driven Engineering
Publication date :
September 2017
Event name :
ACM/IEEE 20th International Conference on Model Driven Engineering Languages and Systems
Event organizer :
University of Texas at Austin, Texas (USA)
Event place :
Texas, United States
Event date :
17-09-2017 to 22-09-2017
Audience :
International
Main work title :
2017 ACM/IEEE 20th International Conference on Model Driven Engineering Languages and Systems
J. E. Rivera, J. R. Romero, and A. Vallecillo, "Behavior, time and viewpoint consistency: Three challenges for mde," in International Conference on Model Driven Engineering Languages and Systems. Springer, 2008, pp. 60-65.
E. Bousse, J. Corley, B. Combemale, J. Gray, and B. Baudry, "Supporting efficient and advanced omniscient debugging for xdsmls," in Proc. of the 8th Int. Conf. on SLE. ACM, 2015, pp. 137-148.
B. Kanso and S. Taha, "Temporal constraint support for ocl," in Proc. of the 5th Int. Conf. on SLE. Springer, 2012, pp. 83-103.
M. Koegel and J. Helming, "Emfstore: a model repository for emf models," in Proc. of the 32nd ACM/IEEE Int. Conf. on Software Engineering-Volume 2. ACM, 2010, pp. 307-308.
J. E. Rivera, A. Vallecillo, and F. Durán, "e-motions: A graphical approach for modeling timedependent behavior of domain specific languages," 2009.
A. P. Iyer, L. E. Li, T. Das, and I. Stoica, "Time-evolving graph processing at scale," in Proc. of the 4th Int. Workshop GRADES. ACM, 2016, pp. 5:1-5:6.
W. Han, Y. Miao, K. Li, M. Wu, F. Yang, L. Zhou, V. Prabhakaran, W. Chen, and E. Chen, "Chronos: A graph engine for temporal graph analysis," in Proc. of the 9th EuroSys Conf. ACM, 2014, pp. 1:1-1:14.
T. Hartmann, F. Fouquet, G. Nain, B. Morin, J. Klein, and Y. L. Traon, "Reasoning at runtime using time-distorted contexts: A models@ run.time based approach," in The 26th Int. Conf. SEKE, Jul. 2014, pp. 586-591.
T. Hartmann, "Enabling model-driven live analytics for cyber-physical systems: The case of smart grids," Ph.D. dissertation, University of Luxembourg, 2016.
T. Hartmann, F. Fouquet, J. Klein, Y. L. Traon, A. Pelov, L. Toutain, and T. Ropitault, "Generating realistic smart grid communication topologies based on real-data," in 2014 IEEE Int. Conf. on SmartGrid-Comm, Nov 2014, pp. 428-433.
J. Clifford and D. S. Warren, "Formal semantics for time in databases," ACM Trans. Database Syst., vol. 8, no. 2, pp. 214-254, Jun 1983.
E. Rose and A. Segev, "Toodm: A temporal object-oriented data model with temporal constraints," Lawrence Berkeley Lab., CA (United States), Tech. Rep., 1991.
M. Kaufmann, A. A. Manjili, P. Vagenas, P. M. Fischer, D. Kossmann, F. Färber, and N. May, "Timeline index: A unified data structure for processing queries on temporal data in sap hana," in Proc. of the 2013 Int. Conf. on Management of Data. ACM, 2013, pp. 1173-1184.
V. Kostakos, "Temporal graphs," Physica A: Statistical Mechanics and its Applications, vol. 388, no. 6, pp. 1007-1023, 2009.
W. Han, Y. Miao, K. Li, M. Wu, F. Yang, L. Zhou, V. Prabhakaran, and E. Chen, "Chronos: a graph engine for temporal graph analysis," in Proc. of the 9th Conf. on Comp. Sys. ACM, 2014, pp. 1-14.
Y. Miao, W. Han, K. Li, M. Wu, F. Yang, L. Zhou, V. Prabhakaran, E. Chen, and W. Chen, "Immortalgraph: A system for storage and analysis of temporal graphs," Trans. Storage, vol. 11, no. 3, pp. 14:1-14:34, Jul. 2015.
U. Khurana and A. Deshpande, "Storing and analyzing historical graph data at scale," in Proc. of the 19th Int. Conf. on EDBT, Bordeaux, France, Mar 2016, pp. 65-76.
R. Cheng, J. Hong, A. Kyrola, Y. Miao, X. Weng, M. Wu, F. Yang, L. Zhou, F. Zhao, and E. Chen, "Kineograph: Taking the pulse of a fast-changing and connected world," in Proc. of the 7th ACM EuroSyS. ACM, 2012, pp. 85-98.
N. Ferry, F. Chauvel, A. Rossini, B. Morin, and A. Solberg, "Managing multi-cloud systems with cloudmf," in Proc. of the 2th Nordic Symposium NordiCloud. ACM, 2013, pp. 38-45.
C. Vidal, C. Fernández-Sánchez, J. Díaz, and J. Pérez, "A modeldriven engineering process for autonomic sensor-Actuator networks," Int. Journal of Distributed Sensor Networks, vol. 11, no. 3, 2015.
N. Harrand, F. Fleurey, B. Morin, and K. E. Husa, "Thingml: a language and code generation framework for heterogeneous targets," in Proc. of the 19th Int. Conf. on MODELS. ACM, 2016, pp. 125-135.
S. Spaccapietra, C. Parent, and E. Zimanyi, "Modeling time from a conceptual perspective," in Proc. of the 7th ACM Int. Conf CIKM. ACM, 1998, pp. 432-440.
A. Artale, R. Kontchakov, V. Ryzhikov, and M. Zakharyaschev, "A cookbook for temporal conceptual data modelling with description logics," ACM Trans. on Comp. Logic, vol. 15, no. 3, pp. 1-50, 2014.
A. Artale, C. Parent, and S. Spaccapietra, "Evolving objects in temporal information systems," Annals of Mathematics and Artificial Intelligence, vol. 50, no. 1, pp. 5-38, 2007.
H. Gregersen and C. S. Jensen, "Temporal entity-relationship models-A survey," IEEE TKDE, vol. 11, no. 3, pp. 464-497, 1999.
A. Hamie, R. Mitchell, and J. Howse, "Time-based constraints in the object constraint language," Technical Report CMS-00-01, University of Brighton, Tech. Rep., 2000.
S. Conrad and K. Turowski, "Temporal ocl: Meeting specification demands for business components," Unified modeling language: Systems analysis, design and development issues, pp. 151-166, 2001.
A. Benelallam, A. Gómez, G. Sunyé, M. Tisi, and D. Launay, "Neo4EMF, A Scalable Persistence Layer for EMF Models," in In Proc. of the 10th European Conf. on ECMFA. Springer, 2014, pp. 230-241.
A. Gómez, A. Benelallam, and M. Tisi, "Decentralized Model Persistence for Distributed Computing," in Proc. of 3rd BigMDE Workshop, vol. 1406. CEUR Workshop Proc., July 2015.
A. Gómez, M. Tisi, G. Sunyé, and J. Cabot, "Map-based transparent persistence for very large models," in In Proc of the Int. Conf. on FASE. Springer, 2015, pp. 19-34.
"CDO Model Repository," 2014. [Online]. Available: http://www. eclipse.org/cdo/
K. Barmpis and D. Kolovos, "Hawk: Towards a Scalable Model Indexing Architecture," in Proc. of the Workshop on Scalability in Model Driven Engineering. ACM, 2013, p. 6.
T. Hartmann, F. Fouquet, G. Nain, B. Morin, J. Klein, O. Barais, and Y. L. Traon, "A native versioning concept to support historized models at runtime," in The 17th Int. Conf. MODELS, Valencia, Spain, September 28-October 3, 2014. 2014, 2014, pp. 252-268.
G. Blair, R. B. France, and N. Bencomo, "Models@ run.time," Computer, vol. 42, pp. 22-27, 2009.
B. Morin, O. Barais, J.-M. Jezequel, F. Fleurey, and A. Solberg, "Models@ run.time to support dynamic adaptation," Computer, vol. 42, no. 10, pp. 44-51, Oct. 2009.
A. Campos, J. Mozzino, and A. Vaisman, "Towards temporal graph databases," arXiv preprint arXiv:1604.08568, 2016.
V. Z. Moffitt and J. Stoyanovich, "Towards a distributed infrastructure for evolving graph analytics," in Proc. of the 25th Int. Conf. on World Wide Web, WWW 2016, Montreal, Canada, April 11-15, 2016, Companion Volume, 2016, pp. 843-848.
G. Daniel, G. Sunyé, A. Benelallam, M. Tisi, Y. Vernageau, A. Gómez, and J. Cabot, "NeoEMF: a Multi-database Model Persistence Framework for Very Large Models," in Proc. of the 19th Int. Conf. MoDELS, (Demo track), Oct 2016, pp. 1-7.
S. Huang, J. Cheng, and H. Wu, "Temporal graph traversals: Definitions, algorithms, and applications," arXiv preprint, 2014.
Neo4j Corp., "Cypher," April, 2017, URL: https://www.neo4j.com/.
W. Dou, D. Bianculli, and L. Briand, "OCLR: A More Expressive, Pattern-Based Temporal Extension of OCL," in In Proc. of the 10th European Conf. ECMFA. Springer Int. Publishing, 2014, pp. 51-66.
C. Chatfield, The analysis of time series: an introduction. CRC press, 2016.