Visualization Method for Decision-Making: A Case Study in Bibliometric Analysis

Data and information visualization have drawn an increasingly wide range of interest from several academic fields and industries. Concurrently, exploring a huge set of data to support feasible decisions needs an organized method of Multi-Criteria Decision Making (MCDM). The dramatic increasing of da...

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Main Authors: Roozbeh Haghnazar Koochaksaraei, Frederico Gadelha Guimarães, Babak Hamidzadeh, Sarfaraz Hashemkhani Zolfani
Format: Article
Language:English
Published: MDPI AG 2021-04-01
Series:Mathematics
Subjects:
Online Access:https://www.mdpi.com/2227-7390/9/9/940
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author Roozbeh Haghnazar Koochaksaraei
Frederico Gadelha Guimarães
Babak Hamidzadeh
Sarfaraz Hashemkhani Zolfani
author_facet Roozbeh Haghnazar Koochaksaraei
Frederico Gadelha Guimarães
Babak Hamidzadeh
Sarfaraz Hashemkhani Zolfani
author_sort Roozbeh Haghnazar Koochaksaraei
collection DOAJ
description Data and information visualization have drawn an increasingly wide range of interest from several academic fields and industries. Concurrently, exploring a huge set of data to support feasible decisions needs an organized method of Multi-Criteria Decision Making (MCDM). The dramatic increasing of data producing during the past decade makes visualization necessary as a presentation layer on the top of MCDM process. This study aims to propose an integrated strategy to rank the alternatives in the dataset, by combining data, MCDM methods, and visualization layers. In fact, the well designed combination of Information Visualization and MCDM provides a more user-friendly approach than the traditional methods. We investigate a case study in bibliometric analyses, which have become an important dimension and tool for evaluating the impact and performance of researchers, departments, and universities. Hence, finding the best and most reliable papers, authors, and publishers considering diverse criteria is one of the important challenges in science world. Therefore, this text is presenting a new strategy on the bibliometric dataset as a case study and it demonstrates that this strategy can be more meaningful for the end users than the current tools. Finally, the presented simulations illustrate the performance and utilization of this combination. In other words, the researchers of this study could design and implement a tool that overcomes the biggest challenges of data analyzing and ranking via a combination of MCDM and visualization methodologies that can provide a tremendous amount of insight and information from a massive dataset in an efficient way.
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spelling doaj.art-d8893c4dca9b499cb45002bfacf9d58b2023-11-21T16:49:30ZengMDPI AGMathematics2227-73902021-04-019994010.3390/math9090940Visualization Method for Decision-Making: A Case Study in Bibliometric AnalysisRoozbeh Haghnazar Koochaksaraei0Frederico Gadelha Guimarães1Babak Hamidzadeh2Sarfaraz Hashemkhani Zolfani3Department of Computer Science, George Washington University, Washington, DC 20052, USADepartment of Electrical Engineering, Federal University of Minas Gerais, Minas Gerais 31270-901, BrazilLibraries, University of Maryland, College Park, MD 20742, USASchool of Engineering, Catholic University of the North, Larrondo 1281, Coquimbo 1240000, ChileData and information visualization have drawn an increasingly wide range of interest from several academic fields and industries. Concurrently, exploring a huge set of data to support feasible decisions needs an organized method of Multi-Criteria Decision Making (MCDM). The dramatic increasing of data producing during the past decade makes visualization necessary as a presentation layer on the top of MCDM process. This study aims to propose an integrated strategy to rank the alternatives in the dataset, by combining data, MCDM methods, and visualization layers. In fact, the well designed combination of Information Visualization and MCDM provides a more user-friendly approach than the traditional methods. We investigate a case study in bibliometric analyses, which have become an important dimension and tool for evaluating the impact and performance of researchers, departments, and universities. Hence, finding the best and most reliable papers, authors, and publishers considering diverse criteria is one of the important challenges in science world. Therefore, this text is presenting a new strategy on the bibliometric dataset as a case study and it demonstrates that this strategy can be more meaningful for the end users than the current tools. Finally, the presented simulations illustrate the performance and utilization of this combination. In other words, the researchers of this study could design and implement a tool that overcomes the biggest challenges of data analyzing and ranking via a combination of MCDM and visualization methodologies that can provide a tremendous amount of insight and information from a massive dataset in an efficient way.https://www.mdpi.com/2227-7390/9/9/940data visualizationVIKORmulti-criteria decision makingrelational analyzingentity based visualizationbibliographic networks
spellingShingle Roozbeh Haghnazar Koochaksaraei
Frederico Gadelha Guimarães
Babak Hamidzadeh
Sarfaraz Hashemkhani Zolfani
Visualization Method for Decision-Making: A Case Study in Bibliometric Analysis
Mathematics
data visualization
VIKOR
multi-criteria decision making
relational analyzing
entity based visualization
bibliographic networks
title Visualization Method for Decision-Making: A Case Study in Bibliometric Analysis
title_full Visualization Method for Decision-Making: A Case Study in Bibliometric Analysis
title_fullStr Visualization Method for Decision-Making: A Case Study in Bibliometric Analysis
title_full_unstemmed Visualization Method for Decision-Making: A Case Study in Bibliometric Analysis
title_short Visualization Method for Decision-Making: A Case Study in Bibliometric Analysis
title_sort visualization method for decision making a case study in bibliometric analysis
topic data visualization
VIKOR
multi-criteria decision making
relational analyzing
entity based visualization
bibliographic networks
url https://www.mdpi.com/2227-7390/9/9/940
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AT sarfarazhashemkhanizolfani visualizationmethodfordecisionmakingacasestudyinbibliometricanalysis