scholarly journals Discovering Research Collaboration Networks from Scientific Digital Libraries and Repositories

2015 ◽  
Vol 53 (2(106)) ◽  
pp. 7-17
Author(s):  
Mieczysław Muraszkiewicz ◽  
Henryk Rybiński ◽  
Piotr Szczepański
Keyword(s):  
Network Analysis ◽  
Digital Libraries ◽  
Research Collaboration ◽  
Formal Model ◽  
Collaboration Networks ◽  
Research Institutions ◽  
Analysis Techniques ◽  
University Of Technology ◽  
Scientific Institutions ◽  
Practical Model

PURPOSE: The purpose of the study is to outline a practical model for discovering research collaboration networks on the basis of data and information stored in scientific digital libraries and repositories. The discovered relationships between researchers, projects, scientific institutions and other scientific entities are used for identifying collaboration networks of researchers and research institutions interested in or working on a given subject. Afterwards, such networks can be subject to various types of network analysis in order to get in-depth knowledge on the networks and their components. APPROACH/METHODS: The method adopted in the study is twofold, that is: (i) it takes into consideration the way of discovering collaboration networks by means of simple tools that have been implemented within the ΩΨR system developed at Warsaw University of Technology; (ii) it develops an outline of a formal model of research collaboration networks that takes into account the specificity of scientific digital libraries and repositories and includes the network analysis techniques for discovering knowledge residing/hidden in the networks. RESULTS AND CONCLUSIONS: The outcome of the research is the outline of a formal model of research collaboration networks that includes: (i) a discovery mechanism for identifying thematically related scientists, projects, research institutions, and other scientific entities; and (ii) a set of network analysis methods for getting in-depth knowledge residing in the networks. The model is implementable and scalable in terms of functionality it offers and the network analysis techniques it includes. The model is founded on a solid ground, which is the ΩΨR system functionality to discover simple collaboration networks, and it is being used for enhancing the ΩΨR system. ORIGINALITY/VALUE: The value of the research is the outline of a general research collaboration networks model that: (i) can help identify, build, and analyse research communities, and thereby increases the scope, value and impact of scientific endeavours on science and society; (ii) is used for enhancing the ΩΨR system.

scholarly journals Social network analysis of biomedical research collaboration networks in a CTSA institution

2014 ◽  
Vol 52 ◽  
pp. 130-140 ◽  
Author(s):  
Jiang Bian ◽  
Mengjun Xie ◽  
Umit Topaloglu ◽  
Teresa Hudson ◽  
Hari Eswaran ◽  
...  
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Biomedical Research ◽  
Research Collaboration ◽  
Collaboration Networks

scholarly journals Mapping the collaboration networks of biomedical research in Southeast Asia

2015 ◽  
Author(s):  
Vincent Schubert R Malbas
Keyword(s):  
Network Analysis ◽  
Southeast Asia ◽  
Biomedical Research ◽  
Research Collaboration ◽  
Research Network ◽  
Collaboration Networks ◽  
Health Issues ◽  
Group Influence ◽  
Regional Collaboration ◽  
Bibliographic Records

Collaboration forms an integral aspect of global research endeavors, where co-authorship derived from bibliographic records provides the building block for mapping research collaboration networks. Bibliometric techniques and social network analysis tools were applied to measure the scope and depth of collaboration in biomedical research in Southeast Asia during the period 2005-2009. In particular, centrality scores and draw network maps were calculated for both country and institutional levels of aggregation. In the field of biomedical research, Thailand and Singapore are the most productive and collaborative countries in Southeast Asia during the period studied. Using network analysis, there was strong correlation of research productivity by a country or institution with the number of collaboration and its group influence, and weak correlation with maximal data flow within the research network. There were specific clusters of connected institutions in subnetworks for neoplasm, diabetes, and tuberculosis research. Given the observed frequency of regional collaboration in Southeast Asia, in comparison to foreign collaboration, it is argued that increasing the number of collaborations within Southeast Asia will help advance the region’s efforts on domestic and regional health issues.

scholarly journals Mapping the collaboration networks of biomedical research in Southeast Asia

2015 ◽  
Author(s):  
Vincent Schubert R Malbas
Keyword(s):  
Network Analysis ◽  
Southeast Asia ◽  
Biomedical Research ◽  
Research Collaboration ◽  
Research Network ◽  
Collaboration Networks ◽  
Health Issues ◽  
Group Influence ◽  
Regional Collaboration ◽  
Bibliographic Records

Collaboration forms an integral aspect of global research endeavors, where co-authorship derived from bibliographic records provides the building block for mapping research collaboration networks. Bibliometric techniques and social network analysis tools were applied to measure the scope and depth of collaboration in biomedical research in Southeast Asia during the period 2005-2009. In particular, centrality scores and draw network maps were calculated for both country and institutional levels of aggregation. In the field of biomedical research, Thailand and Singapore are the most productive and collaborative countries in Southeast Asia during the period studied. Using network analysis, there was strong correlation of research productivity by a country or institution with the number of collaboration and its group influence, and weak correlation with maximal data flow within the research network. There were specific clusters of connected institutions in subnetworks for neoplasm, diabetes, and tuberculosis research. Given the observed frequency of regional collaboration in Southeast Asia, in comparison to foreign collaboration, it is argued that increasing the number of collaborations within Southeast Asia will help advance the region’s efforts on domestic and regional health issues.

scholarly journals Quantitative Dynamics Effects of Belt and Road Economies Trade Using Structural Gravity and Neural Networks

SAGE Open ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 215824402110326
Author(s):  
Koffi Dumor ◽  
Li Yao ◽  
Jean-Paul Ainam ◽  
Edem Koffi Amouzou ◽  
Williams Ayivi
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Network Analysis ◽  
Bilateral Trade ◽  
Belt And Road Initiative ◽  
Neural Network Analysis ◽  
Analysis Techniques ◽  
Belt And Road ◽  
The Impact ◽  
Trade Partners

Recent research suggests that China’s Belt and Road Initiative (BRI) would improve the bilateral trade between China and its partners. This article uses detailed bilateral export data from 1990 to 2017 to investigate the impact of China’s BRI on its trade partners using neural network analysis techniques and structural gravity model estimations. Our main findings suggest that the BRI countries would raise exports by a modest 5.053%. This indicates that export and network upgrades should be considered from economic and policy perspectives. The results also show that neural networks is more robust compared with structural gravity framework.

scholarly journals Visualization of clinical teaching citations using social network analysis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Hakimeh Hazrati ◽  
Shoaleh Bigdeli ◽  
Seyed Kamran Soltani Arabshahi ◽  
Vahideh Zarea Gavgani ◽  
Nafiseh Vahed
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Research Collaboration ◽  
Clinical Teaching ◽  
Clustering Coefficient ◽  
Knowledge Network ◽  
Research Network ◽  
Centrality Measures ◽  
The Usa

Abstract Background Analyzing the previous research literature in the field of clinical teaching has potential to show the trend and future direction of this field. This study aimed to visualize the co-authorship networks and scientific map of research outputs of clinical teaching and medical education by Social Network Analysis (SNA). Methods We Identified 1229 publications on clinical teaching through a systematic search strategy in the Scopus (Elsevier), Web of Science (Clarivate Analytics) and Medline (NCBI/NLM) through PubMed from the year 1980 to 2018.The Ravar PreMap, Netdraw, UCINet and VOSviewer software were used for data visualization and analysis. Results Based on the findings of study the network of clinical teaching was weak in term of cohesion and the density in the co-authorship networks of authors (clustering coefficient (CC): 0.749, density: 0.0238) and collaboration of countries (CC: 0.655, density: 0.176). In regard to centrality measures; the most influential authors in the co-authorship network was Rosenbaum ME, from the USA (0.048). More, the USA, the UK, Canada, Australia and the Netherlands have central role in collaboration countries network and has the vertex co-authorship with other that participated in publishing articles in clinical teaching. Analysis of background and affiliation of authors showed that co-authorship between clinical researchers in medicine filed is weak. Nineteen subject clusters were identified in the clinical teaching research network, seven of which were related to the expected competencies of clinical teaching and three related to clinical teaching skills. Conclusions In order to improve the cohesion of the authorship network of clinical teaching, it is essential to improve research collaboration and co-authorship between new researchers and those who have better closeness or geodisk path with others, especially those with the clinical background. To reach to a dense and powerful topology in the knowledge network of this field encouraging policies to be made for international and national collaboration between clinicians and clinical teaching specialists. In addition, humanitarian and clinical reasoning need to be considered in clinical teaching as of new direction in the field from thematic aspects.

scholarly journals Data Stewardship – addressing disciplinary data management needs

2018 ◽  
Author(s):  
Marta Teperek ◽  
Maria J. Cruz ◽  
Ellen Verbakel ◽  
Jasmin K. Böhmer ◽  
Alastair Dunning
Keyword(s):  
Data Management ◽  
Common Denominator ◽  
Management Support ◽  
Research Institutions ◽  
Multidisciplinary Research ◽  
University Of Technology ◽  
Address Data ◽  
Subject Specific ◽  
Data Stewardship ◽  
The Common

One of the biggest challenges for multidisciplinary research institutions which provide data management support to researchers is addressing disciplinary differences1. Centralised services need to be general enough to cater for all the different flavours of research conducted in an institution. At the same time, focusing on the common denominator means that subject-specific differences and needs may not be effectively addressed. In 2017, Delft University of Technology (TU Delft) embarked on an ambitious Data Stewardship project, aiming to comprehensively address data management needs across a multi-disciplinary campus. In this practice paper, we describe the principles behind the Data Stewardship project at TU Delft, the progress so far, we identify the key challenges and explain our plans for the future.

scholarly journals Women and universities in El País (1977-2011): A methodological proposal for use of the ITCS for historical analysis

2019 ◽  
Vol 8 (1) ◽  
pp. 009
Author(s):  
Carlos G. Figuerola ◽  
Tamar Groves ◽  
Francisco J. Rodríguez
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Text Mining ◽  
Historical Analysis ◽  
Historical Research ◽  
Software Systems ◽  
Practical Case ◽  
Computer Tools ◽  
Analysis Techniques

The practice of historical research in recent years has been substantially affected by the emergence of the so-called digital humanities. New computer tools have been appearing, software systems capable of processing vast quantities of information in ways that until recently were inconceivable. Text mining and social network analysis techniques are sophisticated instruments that can help render a more enriching reading of the available data and draw useful conclusions. We reflect on this in the first part of this article, and then apply these tools to a practical case: quantifying and identifying the women who appear in university-related articles in the newspaper El País from its founding until 2011.

scholarly journals The university e-libraries: The foreign experience

2019 ◽  
pp. 77-89
Author(s):  
D. Gribkov
Keyword(s):  
Digital Libraries ◽  
Digital Collections ◽  
Knowledge Database ◽  
Foreign Experience ◽  
University Of Technology ◽  
Information Center ◽  
Service Oriented ◽  
Digital Formats ◽  
The University ◽  
Quality Policy

The experience of foreign digital libraries of the universities of Marburg (Germany), Chalmers (Sweden) and Graz (Austria) is discussed. The structure of the libraries being reviewed comprises six key elements of DELOS conceptual model, i. e. content, users, functionality, quality, policy, and architecture. The Marburg University Library cooperates with many German libraries and possesses vast collections and resources of various types, both it owns and shares with other libraries. The e-library of Chalmers University of Technology is based on the service-oriented Central Knowledge Database comprising paper and digital collections of full texts and metadata being administered with data import-export applications on the Discovery platform. The Graz Library is the bibliographic and information center; it supports scientific research and learning with literature in printed and digital formats, and preserves the cultural heritage in natural sciences and technology. Based on the review of the mentioned digital libraries, the author concludes that Russian libraries must study the foreign experience to develop the model of an inter-university digital library.

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