Models and data engineering

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• 作者：Ladjel Bellatreche^a ; ^{bellatreche@ensma.fr}Author Vitae ; Yamine Ait Ameur^b ; ^{yamine@enseeiht.fr}Author Vitae ; George Angelos Papadopoulos^c ; ^{george@cs.ucy.ac.cy}Author Vitae
• 关键词：Modelling ; Ontologies ; Formal methods ; Engagement systems ; Data warehouses ; Clustering ; Model and data stores
• 刊名：Future Generation Computer Systems
• 出版年：2017
• 出版时间：May 2017
• 年：2017
• 卷：70
• 期：Complete
• 页码：1-3
• 全文大小：471 K
• 卷排序：70

文摘

Data and models are two well established communities that are continuously contributing in new challenges in different research domains including cyber–physical systems (Yoo and Shon, 2016 [1]), cloud computing (Jararweh et al., 2016 [2]), service oriented applications, social networks (Yahyaoui et al., 2013 [3]), big data (with its five Vs characteristics: Volume, Variety, Velocity, Veracity and Value) (Hsu, 2014), etc. The success story of data and models communities is mainly based on the availability of foundations relying on formal methods (Hassan et al., 2016), modelling methods (Ameur et al., 2014), storage systems and platforms (Liu et al., 2015 [7]), advanced optimization structures, benchmarking, scalability, etc. These foundations are usually associated with tools and commercial and academic systems.The selected papers for this special issue address a variety of topics and concerns in models and data fields, including advanced databases, engagement systems, embedded and complex systems, etc.