scholarly journals POURQUOI MANAGEMENT & DATA SCIENCE ABANDONNE L’ÉVALUATION EN DOUBLE AVEUGLE ?

2021 ◽  
Author(s):  
AMÉLIE CLAUZEL ◽  
Olivier MAMAVI ◽  
CAROLINE RICHÉ ◽  
ROMAIN ZERBIB
Keyword(s):  
Data Science ◽  
Publish Or Perish

La globalisation du secteur académique, conjuguée à une accélération sans précédent de la transformation digitale, implique de repenser en profondeur le rôle des revues scientifiques (Mamavi et Zerbib, 2020). C’est en tout cas la conviction de Management & Data Science, une plateforme ouverte de création et de diffusion de la connaissance sur le thème de la transformation digitale. Management & Data Science offre une alternative concrète à la logique du “publish or perish” (Mamavi et Zerbib, 2019) en permettant une reconnaissance de nos auteurs via les altmetrics. La ligne éditoriale de notre revue défend un positionnement fondé sur la rigueur, la pertinence, la vitesse et l'impact alternatif. Management & Data Science estime qu'une étude peut être qualifiée de scientifique dès lors qu'elle répond à au moins deux critères fondamentaux : la transparence et la reproductibilité. Or, le double aveugle ne nous semble pas ici constituer un moyen incontournable pour évaluer ces deux critères.

Model-Based Clustering and Classification for Data Science

2019 ◽  
Author(s):  
Charles Bouveyron ◽  
Gilles Celeux ◽  
T. Brendan Murphy ◽  
Adrian E. Raftery
Keyword(s):  
Data Science ◽  
Model Based Clustering ◽  
Model Based ◽  
Clustering And Classification

Publish or Perish: Tips on Surviving the Journal Review Process

2006 ◽  
Author(s):  
George V. Gushue ◽  
Lisa Y. Flores
Keyword(s):  
Review Process ◽  
Journal Review ◽  
Publish Or Perish

Publish or perish. Cause e conseguenze di un paradigma

2014 ◽  
pp. 9-25 ◽  
Author(s):  
Gloria Origgi ◽  
Giovanni B. Ramello ◽  
Francesco Silva
Keyword(s):  
Publish Or Perish

Issues in security and privacy of big data

2018 ◽  
Vol 7 (12) ◽  
pp. 1
Author(s):  
Shaveta Bhatia
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Approximate Method ◽  
Biomedical Research ◽  
Cyber Security ◽  
Data Science ◽  
Third Party ◽  
Security And Privacy ◽  
Security Threats ◽  
The Third

 The epoch of the big data presents many opportunities for the development in the range of data science, biomedical research cyber security, and cloud computing. Nowadays the big data gained popularity.  It also invites many provocations and upshot in the security and privacy of the big data. There are various type of threats, attacks such as leakage of data, the third party tries to access, viruses and vulnerability that stand against the security of the big data. This paper will discuss about the security threats and their approximate method in the field of biomedical research, cyber security and cloud computing.

Use of data science in the renewable energy resources

2017 ◽  
Author(s):  
Predrag Stolić ◽  
◽  
Danijela Milošević ◽  
Zoran Stević ◽  
◽  
...  
Keyword(s):  
Renewable Energy ◽  
Data Science ◽  
Energy Resources ◽  
Renewable Energy Resources ◽  
Use Of Data

About digital transformation of the transport industry in Russia

2020 ◽  
Vol 19 (3) ◽  
pp. 95-105
Author(s):  
Natalia V. Vysotskaya ◽  
T. V. Kyrbatskaya
Keyword(s):  
Artificial Intelligence ◽  
Business Model ◽  
Data Science ◽  
Digital Transformation ◽  
Digital Culture ◽  
Blockchain Technology ◽  
Community Approach ◽  
Non Linear ◽  
Transport Industry ◽  
Artificial Intelligence Systems

The article is devoted to the consideration of the main directions of digital transformation of the transport industry in Russia. It is proposed in the process of digital transformation to integrate the community approach into the company's business model using blockchain technology and methods and results of data science; complement the new digital culture with a digital team and new communities that help management solve business problems; focus the attention of the company's management on its employees and develop those competencies in them that robots and artificial intelligence systems cannot implement: develop algorithmic, computable and non-linear thinking in all employees of the company.

Debatte: Publish or Perish?

MedienJournal ◽  
2017 ◽  
Vol 38 (4) ◽  
pp. 62-72
Author(s):  
Robert M. Bichler
Keyword(s):  
Publish Or Perish

Data Mining and Statistics in Data Science

2019 ◽  
Vol 5 (30) ◽  
pp. 960-968
Author(s):  
Güner Gözde KILIÇ
Keyword(s):  
Data Mining ◽  
Data Science
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