@article {10.3844/jcssp.2019.1184.1194,
article_type = {journal},
title = {Meta-Analysis of Data Collect Methods},
author = {Tikito, Iman and El Arass, Mohammed and Souissi, Nissrine},
volume = {15},
number = {8},
year = {2019},
month = {Aug},
pages = {1184-1194},
doi = {10.3844/jcssp.2019.1184.1194},
url = {https://thescipub.com/abstract/jcssp.2019.1184.1194},
abstract = {Several organizations from different sectors depend increasingly on knowledge extracted from huge volumes of data generated by different sources, such as IoT, sensors and databases. At the core of data lifecycle, data reliability, analytics, security, scalability and use are important concerns. Coping with these issues in handling data requires understanding the challenges associated with it. Analysis process and storage devices have been widely studied. However, very few studies have explored the collect data phase.  In this study we aim to analyse more the collect phase of data lifecycle to provide an optimized and smart approach. This paper aim to provide the right method to follow in data collect phase within different domain according to client needs and requirements. It provides not only a detailed view of the main steps, but also based on a prior literature review on different existing methods. This allowed us subsequently to establish a correspondence with the SLR method on which we based our method. We use an explicit example to illustrate the steps of our method.},
journal = {Journal of Computer Science},
publisher = {Science Publications}
}