Implementing a Digital Workspace based on Model Composition Architecture

Nisrine El Marzouki, Mohamed El Mehdi El Aissi, Yassine Loukili, Chaimae Ouali- Alami, Younes Lakhrissi, Oksana Nikiforiva

2021

Abstract

In the era of covid-19 and with the policy of confinement in order to overcome the pandemic of the coronavirus, telework is a mode of work organization, which has obvious virtues. It notably makes it possible to avoid tiredness and lost time in transport, to contribute to the fight against climate change by reducing pollution, to reduce fuel consumption and therefore to increase the purchasing power of households, and also to better organize his working time by staying at home. However, the use of Information and Communication Technologies (ICT) is a necessity, in this context digital workspaces are presented as a strong and powerful platform which implements several ready-to-use modules and also the possibility of adding blocks or what is called in digital workspace jargon a portlet. We will study in this article the architecture of Liferay digital workspace and its ability to present us reusable portlets, so we will refer to the composition of the models in the context of Model Driven Architecture in order to propose a complete and global prototype that meets the expected needs.

Paper Citation

in Harvard Style

El Marzouki N., El Aissi M., Loukili Y., Ouali- Alami C., Lakhrissi Y. and Nikiforiva O. (2021). Implementing a Digital Workspace based on Model Composition Architecture. In Proceedings of the 2nd International Conference on Big Data, Modelling and Machine Learning - Volume 1: BML, ISBN 978-989-758-559-3, pages 572-577. DOI: 10.5220/0010811600003101

in Bibtex Style

@conference{bml21,
author={Nisrine El Marzouki and Mohamed El Mehdi El Aissi and Yassine Loukili and Chaimae Ouali- Alami and Younes Lakhrissi and Oksana Nikiforiva},
title={Implementing a Digital Workspace based on Model Composition Architecture},
booktitle={Proceedings of the 2nd International Conference on Big Data, Modelling and Machine Learning - Volume 1: BML,},
year={2021},
pages={572-577},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010811600003101},
isbn={978-989-758-559-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 2nd International Conference on Big Data, Modelling and Machine Learning - Volume 1: BML,
TI - Implementing a Digital Workspace based on Model Composition Architecture
SN - 978-989-758-559-3
AU - El Marzouki N.
AU - El Aissi M.
AU - Loukili Y.
AU - Ouali- Alami C.
AU - Lakhrissi Y.
AU - Nikiforiva O.
PY - 2021
SP - 572
EP - 577
DO - 10.5220/0010811600003101