Some bibliometric procedures for analyzing and evaluating research fields

Nowadays, measuring the quality and quantity of the scientific production is an important necessity since almost every research assessment decision depends, to a great extent, upon the scientific merits of the involved researchers. To do that, many different indicators have been proposed in the literature. Two main bibliometric procedures to explore a research field have been defined: performance analysis and science mapping. On the one hand, performance analysis aims at evaluating groups of scientific actors (countries, universities, departments, researchers) and the impact of their activity on the basis of bibliographic data. On the other hand, the extraction of knowledge from the intellectual, social or conceptual structure of a research field could be done by means of science mapping analysis based on bibliographic networks. In this paper, we introduce some of the most important techniques and software tools to analyze the impact of a research field and its scientific structures. Particularly, four bibliometric indices (h, g, hg and q2), the h-classics approach to identify the classic papers of a research field and three free science mapping software tools (CitNetExplorer, SciMAT and VOSViewer) are shown

Characteristics of Classic Papers of Library and Information Science: A Scientometric Study

Classic papers are novel facilities of Google scholar. These papers were first developed by Google scholar in May 2017. Classic papers have been considered highly cited papers since last 10 years. Effective authors, institutions, universities, and countries on improving science can be identified by analyzing the papers. Therefore, this study aims to examine characteristics of classic papers of Library and Information Science (LIS). This study will use Scientometrics indicators. The study sample includes LIS classic papers. To gather the data, some databases such as Google scholar, Web of Science, and Scopus are applied. Excel and SPSS applications are used for descriptive and statistical analyses. The study data indicate that Scientometrics journal covers most classic papers on LIS (5 papers). 60% of the papers are written by more than one author. A paper of “Usage Pattern of Collaborating Tagging System” is highly cited paper of LIS with 3051 and 1308 citations on Google scholar and Scopus respectively. Analysis of authors’ affiliation shows that American universities and institutions play considerable role in LIS classic papers. The data of statistical tests indicate that there is a positive significant correlation between citations of classic papers of Google scholar, Scopus and Web of Science

Characteristics of Classic Papers of Library and Information Science: A Scientometric Study

Abstract Classic papers are novel facilities of Google scholar. These papers were first developed by Google scholar in May 2017. Classic papers have been considered highly cited papers since last 10 years. Effective authors, institutions, universities, and countries on improving science can be identified by analyzing the papers. Therefore, this study aims to examine characteristics of classic papers of Library and Information Science (LIS). This study will use Scientometrics indicators. The study sample includes LIS classic papers. To gather the data, some databases such as Google scholar, Web of Science, and Scopus are applied. Excel and SPSS applications are used for descriptive and statistical analyses. The study data indicate that Scientometrics journal covers most classic papers on LIS (5 papers). 60% of the papers are written by more than one author. A paper of “Usage Pattern of Collaborating Tagging System” is highly cited paper of LIS with 3051 and 1308 citations on Google scholar and Scopus respectively. Analysis of authors’ affiliation shows that American universities and institutions play considerable role in LIS classic papers. The data of statistical tests indicate that there is a positive significant correlation between citations of classic papers of Google scholar, Scopus and Web of Science

Fifty years of fuzzy research: A bibliometric analysis and a long-term comparative overview

This paper presents a general overview and a long-term comparison in fuzzy logic research published between 1965 and 2017, obtained via Web of Science. The paper analyzes the growth, impact, trends and regional localization of fuzzy re-search. Conventional, sophisticated among others bibliometric indicators have applies. It aggregates the information according to different levels and criteria including researchers, publications, institutions, or countries. A global perspective have been provided through comparisons of regional aggregates and compound annual growth rates that strengthen the indicators applied in this article. The results permit to visualize the influence, importance, evolution and performance of the fuzzy research as well its contribution to, and transversality with other fields. The findings show that China continues to be a leader in number of contributions. There has been a recent relative decline in the United States contributions overall. Asian and African contribu-tions to scientific literature have grown noticeably. The results also provide a framework for the use of indicators adjusted to specific contexts and relevant information for future research

Mapping Big Data into Knowledge Space with Cognitive Cyber-Infrastructure

Big data research has attracted great attention in science, technology, industry and society. It is developing with the evolving scientific paradigm, the fourth industrial revolution, and the transformational innovation of technologies. However, its nature and fundamental challenge have not been recognized, and its own methodology has not been formed. This paper explores and answers the following questions: What is big data? What are the basic methods for representing, managing and analyzing big data? What is the relationship between big data and knowledge? Can we find a mapping from big data into knowledge space? What kind of infrastructure is required to support not only big data management and analysis but also knowledge discovery, sharing and management? What is the relationship between big data and science paradigm? What is the nature and fundamental challenge of big data computing? A multi-dimensional perspective is presented toward a methodology of big data computing.Comment: 59 page

Multi Agent Systems in Logistics: A Literature and State-of-the-art Review

Based on a literature survey, we aim to answer our main question: “How should we plan and execute logistics in supply chains that aim to meet today’s requirements, and how can we support such planning and execution using IT?†Today’s requirements in supply chains include inter-organizational collaboration and more responsive and tailored supply to meet specific demand. Enterprise systems fall short in meeting these requirements The focus of planning and execution systems should move towards an inter-enterprise and event-driven mode. Inter-organizational systems may support planning going from supporting information exchange and henceforth enable synchronized planning within the organizations towards the capability to do network planning based on available information throughout the network. We provide a framework for planning systems, constituting a rich landscape of possible configurations, where the centralized and fully decentralized approaches are two extremes. We define and discuss agent based systems and in particular multi agent systems (MAS). We emphasize the issue of the role of MAS coordination architectures, and then explain that transportation is, next to production, an important domain in which MAS can and actually are applied. However, implementation is not widespread and some implementation issues are explored. In this manner, we conclude that planning problems in transportation have characteristics that comply with the specific capabilities of agent systems. In particular, these systems are capable to deal with inter-organizational and event-driven planning settings, hence meeting today’s requirements in supply chain planning and execution.supply chain;MAS;multi agent systems