This paper presents a new map representing the structure of all of science, based on journal articles, including both the natural and social sciences. Similar to cartographic maps of our world, the map of science provides a bird's eye view of today's scientific landscape. It can be used to visually identify major areas of science, their size, similarity, and interconnectedness. In order to be useful, the map needs to be accurate on a local and on a global scale. While our recent work has focused on the former aspect, this paper summarizes results on how to achieve structural accuracy. Eight alternative measures of journal similarity were applied to a data set of 7,121 journals covering over 1 million documents in the combined Science Citation and Social Science Citation Indexes. For each journal similarity measure we generated two-dimensional spatial layouts using the force-directed graph layout tool, VxOrd. Next, mutual information values were calculated for each graph at different clustering levels to give a measure of structural accuracy for each map. The best co-citation and inter-citation maps according to local and structural accuracy were selected and are presented and characterized. These two maps are compared to establish robustness. The inter-citation map is more » then used to examine linkages between disciplines. Biochemistry appears as the most interdisciplinary discipline in science. « less

Mapping the backbone of science.

The Internet of Things (IoT) realizes a vision where billions of interconnected devices are deployed just about everywhere, from inside our bodies to the most remote areas of the globe. As the IoT will soon pervade every aspect of our lives and will be accessible from anywhere, addressing critical IoT security threats is now more important than ever. Traditional approaches where security is applied as an afterthought and as a "patch" against known attacks are insufficient. Indeed, next-generation IoT challenges will require a new secure-by-design vision, where threats are addressed proactively and IoT devices learn to dynamically adapt to different threats. To this end, machine learning and software-defined networking will be key to provide both reconfigurability and intelligence to the IoT devices. In this paper, we first provide a taxonomy and survey the state of the art in IoT security research, and offer a roadmap of concrete research challenges related to the application of machine learning and software-defined networking to address existing and next-generation IoT security threats.

Securing the Internet of Things in the Age of Machine Learning and Software-defined Networking

The smart sustainable city (SSC) is a concept created in response to problems and challenges arising from rapid urbanization. This is a relatively new term that is developing dynamically, which is confirmed by the growing number of publications over recent years. For this reason, this article presented an up-to-date comprehensive bibliometric analysis to describe and assess the scientific landscape of smart and sustainable cities literature. The analysis was based on two bibliographic sources—the Web of Science Core Collection and the Scopus database. It covers publications on the SSC, as well as documents describing the smart city (SC) and the sustainable city (SuC) concepts separately. VOSviewer and Biblioshiny were selected as software tools for the bibliometric analysis. Based on the descriptive bibliometric analysis, quantity and quality indicators were determined separately for the SC, SuC, and SSC concepts, while the network analysis mapped and covered the level of multi-faceted scientific cooperation in the field of the SSC research. The analysis results were intended to familiarize scholars and practitioners with the most prolific authors, sources, institutions, and countries in the analyzed scientific field, to identify the most influential research channels and impact from authors, sources, countries, and research topics, to determine major clusters of the SSC research and also to provide valuable information for further investigation.

https://www.mdpi.com/2071-1050/12/3/779/pdf

Scientific Landscape of Smart and Sustainable Cities Literature: A Bibliometric Analysis

A comprehensive bibliometric analysis of entrepreneurship and crisis literature published from 1984 to 2020

Dendritic epidermal T cells (DETC) are a group of immune cells expressing canonical γδ TCR in the murine epidermis. Similar to γδ T cells in the human epidermis, DETC serve an important barrier cell in the skin and participate in skin immune surveillance, immune regulation, skin homeostasis, tissue protection, and other activities. Since its discovery in 1983, research on DETC has grown rapidly and unevenly. To evaluate DETC research trends and map the DETC knowledge structure, we have applied bibliometric methods and techniques. A total of 384 DETC-related articles obtained from the Scopus database published between 1983 and 2019 were analyzed using indicators of publication and citation metrics, country and international cooperation, author and co-authorship, and keyword co-occurrence cluster. The present research status, the emerging global trends and the future development direction are also visualized and discussed. In summary, this study provides novel and useful data for the DETC research scientific community, and will help researchers explore DETC more intuitively and effectively.

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Bibliometric Analysis of Dendritic Epidermal T Cell (DETC) Research From 1983 to 2019.

Smart cities have been a global concern in recent years, involving comprehensive scientific research. To obtain a structural overview and assist researchers in making insights into the characteristics of smart cities research, bibliometric analysis was carried out in this paper. With the application of the bibliometric analysis software VOSviewer and CiteSpace, 4409 smart cities were identified by the core collection of the Web of Science in publications between 1998 and 2019 and used in the analysis of this paper. Concretely, this research visually demonstrates a comprehensive overview of the field relating to smart cities in terms of the production of regular publications, main domain of smart cities researchers, most influential countries (institutions, sources and authors), and interesting research directions in the smart city researches. We also present the research collaboration among countries (regions), organizations and authors based on a series of cooperation analyses. The bibliometric analysis of the existing work provided a valuable and seminal reference for researchers and practitioners in smart cities-related research communities.

https://www.mdpi.com/2071-1050/11/13/3606/pdf

Xing-Rong Guo

Papers

Bibliometric Analysis on Smart Cities Research

A bibliometric analysis and visualization of blockchain