Reference : Raising Time Awareness in Model-Driven Engineering

	Document type :	Scientific congresses, symposiums and conference proceedings : Paper published in a book
	Discipline(s) :	Engineering, computing & technology : Computer science
	Focus Areas :	Computational Sciences
	To cite this reference:	http://hdl.handle.net/10993/32738

Title :	Raising Time Awareness in Model-Driven Engineering
Language :	English
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) >]
Publication date :	Sep-2017
Main document title :	2017 ACM/IEEE 20th International Conference on Model Driven Engineering Languages and Systems
Publisher :	Springer
Pages :	181-188
Peer reviewed :	Yes
Audience :	International
ISBN :	978-1-5386-3492-9
Event name :	ACM/IEEE 20th International Conference on Model Driven Engineering Languages and Systems
Event date :	17-09-2017 to 22-09-2017
Event organizer :	University of Texas at Austin, Texas (USA)
Event place (city) :	Texas
Event country :	US
Keywords :	[en] 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.
Target :	Researchers ; Professionals ; Students
Permalink :	http://hdl.handle.net/10993/32738
DOI :	10.1109/MODELS.2017.11

	File(s) associated to this reference
	Fulltext file(s): File Commentary Version Size Access Open access models2017-vision-author-preprint.pdf Author preprint 172.17 kB View/Open

All documents in ORBi^lu are protected by a user license.

 

University of Luxembourg Library |  Feedback |  Legal notices Site Map