loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Mohamed Cherradi 1 ; Anass El Haddadi 2 and Hayat Routaib 2

Affiliations: 1 Data science and competitive intelligence (DSCI). Applied Sciences Laboratory ENSAH/UAE. Al Hoceima - Morocco., Morocco ; 2 Data science and competitive intelligence (DSCI). Applied Sciences Laboratory ENSAH/UAE. Al Hoceima - Morocco

Keyword(s): Data Lake, Metadata management, Big Data, Ontology, Covid-19.

Abstract: The coronavirus pandemic has radically changed the way we live. It has had a major impact on all areas. Researchers around the world are redoubling their efforts to explore solutions to this pandemic. In this context, many researchers attest to the driving role of technologies in the management and resolution of this global health crisis. To allow specialists in the field to better understand the key factors that influence the rapid spread of this epidemic, the establishment of a data lake information system is a major challenge for analyzing heterogeneous data to make effective decisions. This study aims to take advantage of the power of this massive amount of heterogeneous data to construct a data lake system as one of the expected information systems for many organizations. To meet this need, this paper proposes a new approach for data lakes based on dynamic ontologies to manage different data types regardless of their format. In addition to this, we have designed a friendly inter face for the digitalization of hospital operations and a dashboard for visualization of the statistics of the covid19. (More)

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 216.73.216.123

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Cherradi, M., El Haddadi, A. and Routaib, H. (2022). Moroccan Data Lake Healthcare Analytics for Covid-19. In Proceedings of the 2nd International Conference on Big Data, Modelling and Machine Learning - BML; ISBN 978-989-758-559-3, SciTePress, pages 232-238. DOI: 10.5220/0010731700003101

@conference{bml22,
author={Mohamed Cherradi and Anass {El Haddadi} and Hayat Routaib},
title={Moroccan Data Lake Healthcare Analytics for Covid-19},
booktitle={Proceedings of the 2nd International Conference on Big Data, Modelling and Machine Learning - BML},
year={2022},
pages={232-238},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010731700003101},
isbn={978-989-758-559-3},
}

TY - CONF

JO - Proceedings of the 2nd International Conference on Big Data, Modelling and Machine Learning - BML
TI - Moroccan Data Lake Healthcare Analytics for Covid-19
SN - 978-989-758-559-3
AU - Cherradi, M.
AU - El Haddadi, A.
AU - Routaib, H.
PY - 2022
SP - 232
EP - 238
DO - 10.5220/0010731700003101
PB - SciTePress

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic