This study aimed to delineate the research area of nanocellulose by developing a procedure to retrieve relevant publications. The researchers:
1) Used keyword searches to identify an initial set of nanocellulose publications and located them within a publication classification system, which grouped publications into 428 research areas.
2) Analyzed the relevance of peripheral research areas and refined the initial publication set using text mining.
3) Selected the most relevant research areas based on concentration of nanocellulose publications.
This delineation procedure identified 12 main nanocellulose research topics and 2 nuclei areas, mapping the local and global structure of nanocellulose research.
Research is the continued search for truth using the scientific method. This presentation covers the research process, sampling, methods of data collection, normal curve, measures of central tendency, dispersion and the levels of evidence
Dr. Edward Kai-Hua Chow, JALA Associate Editor/Asia and National University of Singapore, shares his SLAS2013 JALA and JBS Authors Workshop presentation. Learn more about these leading peer-reviewed journals, and then see Ed's tips for publication beginning on slide 16.
In materials sciences, a large amount of research data is generated through a broad spectrum of different
experiments. As of today, experimental research data including meta-data in materials science is often
stored decentralized by the researcher(s) conducting the experiments without generally accepted standards
on what and how to store data. The conducted research and experiments often involve a considerable
investment from public funding agencies that desire the results to be made available in order to increase
their impact. In order to achieve the goal of citable and (openly) accessible materials science experimental
research data in the future, not only an adequate infrastructure needs to be established but the question of
how to measure the quality of the experimental research data also to be addressed. In this publication, the
authors identify requirements and challenges towards a systematic methodology to measure experimental
research data quality prior to publication and derive different approaches on that basis. These methods are
critically discussed and assessed by their contribution and limitations towards the set goals. Concluding, a
combination of selected methods is presented as a systematic, functional and practical quality measurement
and assurance approach for experimental research data in materials science with the goal of supporting
the accessibility and dissemination of existing data sets.
CitNetExplorer: A new software tool for analyzing and visualizing citation ne...Nees Jan van Eck
CitNetExplorer is a software tool for visualizing and analyzing citation networks of scientific publications. The tool allows citation networks to be imported directly from the Web of Science database. Citation networks can be explored interactively, for instance by drilling down into a network and by identifying clusters of closely related publications.
International collaboration in science the global map and the networkHan Woo PARK
박한우 교수가 공저자로 참여한 “전세계 과학자들의 국제협력에 대한 매핑과 네트워크 분석” 이 El professional de la información (SSCI 등재) 에 2010~2015년에 출판된 논문들 가운데 Google Scholar “톱 15 인용” 으로 선정됨. 따라서, 2016년 6월에 스페인 바르셀로나에서 개최되는 “사회과학과 인문학 학술지들에 대한 국제회의” (CRECS)에서 EPI-SCImago 콘텐스의 후보로 선정됨.
Leydesdorff, Loet; Wagner, Caroline S.; Park, Han-Woo; Adams, Jonathan (2013).“International collaboration in science: the global map and the network”. El profesional
de la información, v. 22, n. 1, pp. 87-94.
http://recyt.fecyt.es/index.php/EPI/article/view/epi.2013.ene.12
보낸 사람: "Tomàs Baiget" <baiget@gmail.com>
보냄: 2016년 2월 17일 오후 8:15
받는 사람: "Loet Leydesdorff" <loet@leydesdorff.net>, "Caroline Wagner" <cswagner@mac.com>, "Han Woo Park" <hanpark@ynu.ac.kr>, "Jonathan Adams" <jonathan.adams@thomsonreuters.com>
제목: Your article in the short list for EPI-SCImago Award
Dear authors of El profesional de la información
I am pleased to inform you that your article published in EPI is one that has received more citations in recent years, according to Google Scholar Citations.
Congratulations!
Therefore it is listed among the 15 finalists to receive the EPI-SCImago Award for the best article published in the period 2010-2015. I enclose the list.
All the articles are currently available in open access
.
The prize consists of a diploma and 3,000 euros, which will be presented during the 6th International conference on social sciences and humanities journals (CRECS), Barcelona, 5-6 May 2016.
The jury that will vote the articles, with more than 50 members, it is being established these days.
I will keep you informed.
Tomàs Baiget
, Director
http://www.elprofesionaldelainformacion.com
baiget@gmail.com
Tel.: +34-639 878 489
Research is the continued search for truth using the scientific method. This presentation covers the research process, sampling, methods of data collection, normal curve, measures of central tendency, dispersion and the levels of evidence
Dr. Edward Kai-Hua Chow, JALA Associate Editor/Asia and National University of Singapore, shares his SLAS2013 JALA and JBS Authors Workshop presentation. Learn more about these leading peer-reviewed journals, and then see Ed's tips for publication beginning on slide 16.
In materials sciences, a large amount of research data is generated through a broad spectrum of different
experiments. As of today, experimental research data including meta-data in materials science is often
stored decentralized by the researcher(s) conducting the experiments without generally accepted standards
on what and how to store data. The conducted research and experiments often involve a considerable
investment from public funding agencies that desire the results to be made available in order to increase
their impact. In order to achieve the goal of citable and (openly) accessible materials science experimental
research data in the future, not only an adequate infrastructure needs to be established but the question of
how to measure the quality of the experimental research data also to be addressed. In this publication, the
authors identify requirements and challenges towards a systematic methodology to measure experimental
research data quality prior to publication and derive different approaches on that basis. These methods are
critically discussed and assessed by their contribution and limitations towards the set goals. Concluding, a
combination of selected methods is presented as a systematic, functional and practical quality measurement
and assurance approach for experimental research data in materials science with the goal of supporting
the accessibility and dissemination of existing data sets.
CitNetExplorer: A new software tool for analyzing and visualizing citation ne...Nees Jan van Eck
CitNetExplorer is a software tool for visualizing and analyzing citation networks of scientific publications. The tool allows citation networks to be imported directly from the Web of Science database. Citation networks can be explored interactively, for instance by drilling down into a network and by identifying clusters of closely related publications.
International collaboration in science the global map and the networkHan Woo PARK
박한우 교수가 공저자로 참여한 “전세계 과학자들의 국제협력에 대한 매핑과 네트워크 분석” 이 El professional de la información (SSCI 등재) 에 2010~2015년에 출판된 논문들 가운데 Google Scholar “톱 15 인용” 으로 선정됨. 따라서, 2016년 6월에 스페인 바르셀로나에서 개최되는 “사회과학과 인문학 학술지들에 대한 국제회의” (CRECS)에서 EPI-SCImago 콘텐스의 후보로 선정됨.
Leydesdorff, Loet; Wagner, Caroline S.; Park, Han-Woo; Adams, Jonathan (2013).“International collaboration in science: the global map and the network”. El profesional
de la información, v. 22, n. 1, pp. 87-94.
http://recyt.fecyt.es/index.php/EPI/article/view/epi.2013.ene.12
보낸 사람: "Tomàs Baiget" <baiget@gmail.com>
보냄: 2016년 2월 17일 오후 8:15
받는 사람: "Loet Leydesdorff" <loet@leydesdorff.net>, "Caroline Wagner" <cswagner@mac.com>, "Han Woo Park" <hanpark@ynu.ac.kr>, "Jonathan Adams" <jonathan.adams@thomsonreuters.com>
제목: Your article in the short list for EPI-SCImago Award
Dear authors of El profesional de la información
I am pleased to inform you that your article published in EPI is one that has received more citations in recent years, according to Google Scholar Citations.
Congratulations!
Therefore it is listed among the 15 finalists to receive the EPI-SCImago Award for the best article published in the period 2010-2015. I enclose the list.
All the articles are currently available in open access
.
The prize consists of a diploma and 3,000 euros, which will be presented during the 6th International conference on social sciences and humanities journals (CRECS), Barcelona, 5-6 May 2016.
The jury that will vote the articles, with more than 50 members, it is being established these days.
I will keep you informed.
Tomàs Baiget
, Director
http://www.elprofesionaldelainformacion.com
baiget@gmail.com
Tel.: +34-639 878 489
This tutorial deals with two software tools: VOSviewer and CitNetExplorer. VOSviewer (www.vosviewer.com) is a freely available tool for constructing and visualizing bibliographic coupling, co-citation, co-authorship, and term co-occurrence networks. These networks can be constructed based on data downloaded from Web of Science or Scopus. CitNetExplorer (www.citnetexplorer.nl) is a freely available tool for analyzing and visualizing citation networks of publications.
The aim of the tutorial is to provide the participants with a basic knowledge of VOSviewer and CitNetExplorer. Given time constraints, it will not be possible to explore the two tools in a fully comprehensive way, but the tutorial will offer a thorough introduction into the most essential features of the tools. This should be sufficient for the participants to perform all basic analyses that can be done using VOSviewer and CitNetExplorer. In addition, it should allow the participants to independently explore the tools in more detail.
The lecturers are Nees Jan van Eck and Ludo Waltman, both affiliated to the Centre for Science and Technology Studies (CWTS) of Leiden University. Nees Jan and Ludo are the developers and VOSviewer and CitNetExplorer, and they therefore have an in-depth knowledge of both software tools. Nees Jan and Ludo regularly organize courses and workshops on VOSviewer and CitNetExplorer (see for instance www.cwts.nl/Bibliometric-Network-Analysis-and-Science-Mapping-Using-VOSviewer), so they have a lot of experience in training people in the use of these tools.
Network visualization: Fine-tuning layout techniques for different types of n...Nees Jan van Eck
An important issue in network visualization is the problem of obtaining a good layout for a network. For a given network, which may be either weighted or unweighted, the problem is to position the nodes in the network in a two-dimensional space in such a way that an attractive layout is obtained. Many layout techniques have been proposed [1]. In the visualization of bibliometric networks, multidimensional scaling and the layout technique of Kamada and Kawai [2] have for instance been used a lot. More recently, the VOS (visualization of similarities) layout technique [3], implemented in our VOSviewer software (www.vosviewer.com) [4], is often used for bibliometric network visualization.
There is no layout technique that is generally considered to give optimal results. One reason for this is that comparisons between layouts produced by different techniques involve a lot of subjectiveness. Someone may consider one layout to be more attractive than another, but someone else may have an opposite opinion on this. In addition, the attractiveness of a layout may depend on the type of visualization that is needed. For instance, some layouts may be more attractive for interactive visualizations (e.g., in a software tool with zooming functionality), while other layouts may be more attractive for static visualizations. Furthermore, different types of networks may benefit from different layout techniques.
In recent studies [5, 6], the idea of parameterized layout techniques has been introduced. Parameterized layout techniques produce different types of layouts depending on the values chosen for their parameters. In this research, we present a comprehensive study of a parameterized version of our VOS layout technique. Two parameters are included. Like in [5], these are referred to as attraction and repulsion parameters. We compare the layouts obtained for different parameter values. Comparisons are made both subjectively using the VOSviewer software (i.e., which layout do we find most appealing?) and more objectively using so-called meta-criteria [6, 7]. Sensitivity to local optima is taken into account as well. Comparisons are made for all important types of bibliometric networks, in particular co-authorship, citation, co-citation, bibliographic coupling, and co-occurrence networks. Both smaller and larger networks are considered.
NESSHI and GEPHI: sociology of science as a breeding ground for tool building...Clement Levallois
Different options are available to share th tools created in the course of an academic project.
Among the options available, Gephi is single out for all the advantages it provides.
Applications of community detection in bibliometric network analysisNees Jan van Eck
In this talk, we focus on the analysis of bibliometric networks, and in particular on the detection of communities in these networks. We start by demonstrating VOSviewer, a popular software tool for visualizing bibliometric networks. We discuss the techniques used by VOSviewer for visualizing bibliometric networks and for detecting communities in these networks. We pay special attention to the close relationship between visualization and community detection, and we discuss the unified approach to visualization and community detection that is implemented in VOSviewer. We then shift our attention to community detection in very large citation networks, including millions of publications and hundreds of millions of citation relations. We show how community detection techniques can be used to construct highly detailed classification systems of science. We also discuss applications of such classification systems to science policy questions. Finally, we demonstrate CitNetExplorer, a new software tool in which community detection techniques are used to support the large-scale analysis of citation networks. We use CitNetExplorer to analyze the citation network of publications on network science and in particular on community detection.
A systematic empirical comparison of different approaches for normalizing cit...Nees Jan van Eck
We address the question how citation-based bibliometric indicators can best be normalized to ensure fair comparisons between publications from different scientific fields and different years. In a systematic large-scale empirical analysis, we compare a traditional normalization approach based on a field classification system with three source normalization approaches. We pay special attention to the selection of the publications included in the analysis. Publications in national scientific journals, popular scientific magazines, and trade magazines are not included. Unlike earlier studies, we use algorithmically constructed classification systems to evaluate the different normalization approaches. Our analysis shows that a source normalization approach based on the recently introduced idea of fractional citation counting does not perform well. Two other source normalization approaches generally outperform the classification-system-based normalization approach that we study. Our analysis therefore offers considerable support for the use of source-normalized bibliometric indicators.
Presentation on the occasion of the 60th anniversary of the Econometric Institute at Erasmus University Rotterdam. Rotterdam, The Netherlands, May 27, 2016.
VOSviewer and CitNetExplorer: Software tools for bibliometric analysis of s...Nees Jan van Eck
In this talk, an introduction is given into two software tools that have been developed for bibliometric analysis of scientific publications: VOSviewer (www.vosviewer.com) and CitNetExplorer (www.citnetexplorer.nl). VOSviewer is a popular tool that can be used for visualizing bibliometric networks of citation relations between publications, authors, and journals. In addition, the tool can be used for creating so-called term map visualizations based on a text mining analysis of the titles and abstracts of publications. The most important terms occurring in titles and abstract are identified and the co-occurrence relations between these terms are visualized. CitNetExplorer is a tool for the visualization and analysis of citation networks of scientific publications. The tool can be used to explore in detail how publications build on each other, as indicated by citation links. It is also possible to drill down into specific areas within a citation network, making it possible to perform micro-level analyses of the development of a particular area of research. In this talk, special attention will be paid to possible applications of VOSviewer and CitNetExplorer in humanities research, focusing in particular on the use of advanced text mining, network analysis, and visualization techniques for analyzing large quantities of textual data.
Nees Jan van Eck is a researcher at the Centre for Science and Technology Studies (CWTS) of Leiden University. His research focuses on the quantitative analysis of scientific research based on large amounts of bibliographic data and using sophisticated techniques from fields such as network analysis, statistics, and machine learning. Together with his colleague Ludo Waltman, Nees Jan has developed the VOSviewer and CitNetExplorer tools.
Bibliometric network analysis: Software tools, techniques, and an analysis o...Nees Jan van Eck
Presentation at the LCN2 seminar on November 27, 2015.
We provide an introduction into the research program on bibliometric network analysis at Leiden University’s Centre for Science and Technology Studies (CWTS). We demonstrate two popular software tools for bibliometric network analysis developed at CWTS: VOSviewer (www.vosviewer.com) and CitNetExplorer (www.citnetexplorer.nl). We also discuss the techniques that we have developed for network layout and community detection. Finally, we use bibliometric network analysis to study the field of network science and the contributions made to this field by researchers at Leiden University.
CitNetExplorer is a software tool for visualizing and analyzing citation networks of scientific publications. The tool allows citation networks to be imported directly from the Web of Science database. Citation networks can be explored interactively, for instance by drilling down into a network and by identifying clusters of closely related publications.
CWTS Leiden Ranking: An advanced bibliometric approach to university rankingNees Jan van Eck
The CWTS Leiden Ranking measures the scientific performance of 750 major universities worldwide. Using a sophisticated set of bibliometric indicators, the ranking aims to provide highly accurate measurements of the scientific impact of universities and of universities’ involvement in scientific collaboration. http://www.leidenranking.com
Increased access to the data generated is fuelling increased consumption and accelerating the cycle of discovery. But the successful integration and re-use of heterogeneous data from multiple providers and scientific domains is a major challenge within academia and industry, often due to incomplete description of the study details or metadata about the study. Using the BioSharing, ISA Commons and the STATistics Ontology (STATO) projects as exemplar community efforts, in this breakout session we will discuss the evolving portfolio of community-based standards and methods for structuring and curating datasets, from experimental descriptions to the results of analysis.
http://www.methodsinecologyandevolution.org/view/0/events.html#Data_workshop
Presentation at the Colloquium Research Information Systems and Science Classifications: Revisiting the NARCIS Classification, Museum Meermanno, The Hague, The Netherlands, September 28, 2018.
This tutorial deals with two software tools: VOSviewer and CitNetExplorer. VOSviewer (www.vosviewer.com) is a freely available tool for constructing and visualizing bibliographic coupling, co-citation, co-authorship, and term co-occurrence networks. These networks can be constructed based on data downloaded from Web of Science or Scopus. CitNetExplorer (www.citnetexplorer.nl) is a freely available tool for analyzing and visualizing citation networks of publications.
The aim of the tutorial is to provide the participants with a basic knowledge of VOSviewer and CitNetExplorer. Given time constraints, it will not be possible to explore the two tools in a fully comprehensive way, but the tutorial will offer a thorough introduction into the most essential features of the tools. This should be sufficient for the participants to perform all basic analyses that can be done using VOSviewer and CitNetExplorer. In addition, it should allow the participants to independently explore the tools in more detail.
The lecturers are Nees Jan van Eck and Ludo Waltman, both affiliated to the Centre for Science and Technology Studies (CWTS) of Leiden University. Nees Jan and Ludo are the developers and VOSviewer and CitNetExplorer, and they therefore have an in-depth knowledge of both software tools. Nees Jan and Ludo regularly organize courses and workshops on VOSviewer and CitNetExplorer (see for instance www.cwts.nl/Bibliometric-Network-Analysis-and-Science-Mapping-Using-VOSviewer), so they have a lot of experience in training people in the use of these tools.
Network visualization: Fine-tuning layout techniques for different types of n...Nees Jan van Eck
An important issue in network visualization is the problem of obtaining a good layout for a network. For a given network, which may be either weighted or unweighted, the problem is to position the nodes in the network in a two-dimensional space in such a way that an attractive layout is obtained. Many layout techniques have been proposed [1]. In the visualization of bibliometric networks, multidimensional scaling and the layout technique of Kamada and Kawai [2] have for instance been used a lot. More recently, the VOS (visualization of similarities) layout technique [3], implemented in our VOSviewer software (www.vosviewer.com) [4], is often used for bibliometric network visualization.
There is no layout technique that is generally considered to give optimal results. One reason for this is that comparisons between layouts produced by different techniques involve a lot of subjectiveness. Someone may consider one layout to be more attractive than another, but someone else may have an opposite opinion on this. In addition, the attractiveness of a layout may depend on the type of visualization that is needed. For instance, some layouts may be more attractive for interactive visualizations (e.g., in a software tool with zooming functionality), while other layouts may be more attractive for static visualizations. Furthermore, different types of networks may benefit from different layout techniques.
In recent studies [5, 6], the idea of parameterized layout techniques has been introduced. Parameterized layout techniques produce different types of layouts depending on the values chosen for their parameters. In this research, we present a comprehensive study of a parameterized version of our VOS layout technique. Two parameters are included. Like in [5], these are referred to as attraction and repulsion parameters. We compare the layouts obtained for different parameter values. Comparisons are made both subjectively using the VOSviewer software (i.e., which layout do we find most appealing?) and more objectively using so-called meta-criteria [6, 7]. Sensitivity to local optima is taken into account as well. Comparisons are made for all important types of bibliometric networks, in particular co-authorship, citation, co-citation, bibliographic coupling, and co-occurrence networks. Both smaller and larger networks are considered.
NESSHI and GEPHI: sociology of science as a breeding ground for tool building...Clement Levallois
Different options are available to share th tools created in the course of an academic project.
Among the options available, Gephi is single out for all the advantages it provides.
Applications of community detection in bibliometric network analysisNees Jan van Eck
In this talk, we focus on the analysis of bibliometric networks, and in particular on the detection of communities in these networks. We start by demonstrating VOSviewer, a popular software tool for visualizing bibliometric networks. We discuss the techniques used by VOSviewer for visualizing bibliometric networks and for detecting communities in these networks. We pay special attention to the close relationship between visualization and community detection, and we discuss the unified approach to visualization and community detection that is implemented in VOSviewer. We then shift our attention to community detection in very large citation networks, including millions of publications and hundreds of millions of citation relations. We show how community detection techniques can be used to construct highly detailed classification systems of science. We also discuss applications of such classification systems to science policy questions. Finally, we demonstrate CitNetExplorer, a new software tool in which community detection techniques are used to support the large-scale analysis of citation networks. We use CitNetExplorer to analyze the citation network of publications on network science and in particular on community detection.
A systematic empirical comparison of different approaches for normalizing cit...Nees Jan van Eck
We address the question how citation-based bibliometric indicators can best be normalized to ensure fair comparisons between publications from different scientific fields and different years. In a systematic large-scale empirical analysis, we compare a traditional normalization approach based on a field classification system with three source normalization approaches. We pay special attention to the selection of the publications included in the analysis. Publications in national scientific journals, popular scientific magazines, and trade magazines are not included. Unlike earlier studies, we use algorithmically constructed classification systems to evaluate the different normalization approaches. Our analysis shows that a source normalization approach based on the recently introduced idea of fractional citation counting does not perform well. Two other source normalization approaches generally outperform the classification-system-based normalization approach that we study. Our analysis therefore offers considerable support for the use of source-normalized bibliometric indicators.
Presentation on the occasion of the 60th anniversary of the Econometric Institute at Erasmus University Rotterdam. Rotterdam, The Netherlands, May 27, 2016.
VOSviewer and CitNetExplorer: Software tools for bibliometric analysis of s...Nees Jan van Eck
In this talk, an introduction is given into two software tools that have been developed for bibliometric analysis of scientific publications: VOSviewer (www.vosviewer.com) and CitNetExplorer (www.citnetexplorer.nl). VOSviewer is a popular tool that can be used for visualizing bibliometric networks of citation relations between publications, authors, and journals. In addition, the tool can be used for creating so-called term map visualizations based on a text mining analysis of the titles and abstracts of publications. The most important terms occurring in titles and abstract are identified and the co-occurrence relations between these terms are visualized. CitNetExplorer is a tool for the visualization and analysis of citation networks of scientific publications. The tool can be used to explore in detail how publications build on each other, as indicated by citation links. It is also possible to drill down into specific areas within a citation network, making it possible to perform micro-level analyses of the development of a particular area of research. In this talk, special attention will be paid to possible applications of VOSviewer and CitNetExplorer in humanities research, focusing in particular on the use of advanced text mining, network analysis, and visualization techniques for analyzing large quantities of textual data.
Nees Jan van Eck is a researcher at the Centre for Science and Technology Studies (CWTS) of Leiden University. His research focuses on the quantitative analysis of scientific research based on large amounts of bibliographic data and using sophisticated techniques from fields such as network analysis, statistics, and machine learning. Together with his colleague Ludo Waltman, Nees Jan has developed the VOSviewer and CitNetExplorer tools.
Bibliometric network analysis: Software tools, techniques, and an analysis o...Nees Jan van Eck
Presentation at the LCN2 seminar on November 27, 2015.
We provide an introduction into the research program on bibliometric network analysis at Leiden University’s Centre for Science and Technology Studies (CWTS). We demonstrate two popular software tools for bibliometric network analysis developed at CWTS: VOSviewer (www.vosviewer.com) and CitNetExplorer (www.citnetexplorer.nl). We also discuss the techniques that we have developed for network layout and community detection. Finally, we use bibliometric network analysis to study the field of network science and the contributions made to this field by researchers at Leiden University.
CitNetExplorer is a software tool for visualizing and analyzing citation networks of scientific publications. The tool allows citation networks to be imported directly from the Web of Science database. Citation networks can be explored interactively, for instance by drilling down into a network and by identifying clusters of closely related publications.
CWTS Leiden Ranking: An advanced bibliometric approach to university rankingNees Jan van Eck
The CWTS Leiden Ranking measures the scientific performance of 750 major universities worldwide. Using a sophisticated set of bibliometric indicators, the ranking aims to provide highly accurate measurements of the scientific impact of universities and of universities’ involvement in scientific collaboration. http://www.leidenranking.com
Increased access to the data generated is fuelling increased consumption and accelerating the cycle of discovery. But the successful integration and re-use of heterogeneous data from multiple providers and scientific domains is a major challenge within academia and industry, often due to incomplete description of the study details or metadata about the study. Using the BioSharing, ISA Commons and the STATistics Ontology (STATO) projects as exemplar community efforts, in this breakout session we will discuss the evolving portfolio of community-based standards and methods for structuring and curating datasets, from experimental descriptions to the results of analysis.
http://www.methodsinecologyandevolution.org/view/0/events.html#Data_workshop
Presentation at the Colloquium Research Information Systems and Science Classifications: Revisiting the NARCIS Classification, Museum Meermanno, The Hague, The Netherlands, September 28, 2018.
Presentation made on December 7th 2016 during ICADL'16
Full text can be found at http://link.springer.com/chapter/10.1007/978-3-319-49304-6_12
Extended version can be found at https://arxiv.org/abs/1609.01415
Ten basic guidelines for conducting and publishing a meta-analysis.pptxPubrica
To systematically search published studies, use various bibliographic databases like PubMed, Embase, The Cochrane Central Register of Controlled Trials, Scopus, Web of Science, and Google Scholar. Specific databases like BIOSIS, CINAHL, PsycINFO, Sociological Abstracts, and EconLit can help identify additional articles and data.
Read more @ https://pubrica.com/academy/meta-analysis/ten-basic-guidelines-for-conducting-and-publishing-a-meta-analysis/
The CSO Classifier: Ontology-Driven Detection of Research Topics in Scholarly...Angelo Salatino
Classifying research papers according to their research topics is an important task to improve their retrievability, assist the creation of smart analytics, and support a variety of approaches for analysing and making sense of the research environment. In this paper, we present the CSO Classifier, a new unsupervised approach for automatically classifying research papers according to the Computer Science Ontology (CSO), a comprehensive ontology of re-search areas in the field of Computer Science. The CSO Classifier takes as input the metadata associated with a research paper (title, abstract, keywords) and returns a selection of research concepts drawn from the ontology. The approach was evaluated on a gold standard of manually annotated articles yielding a significant improvement over alternative methods.
Experimental method of Educational Research.Neha Deo
experimental method is the most challenging method of the Educational research. In the experimental method different functional & factorial designs can be used. One has to think over the internal & external validity of the experiment also.In this presentation all these things are discussed in details.
Research Paper Writing For Microbiology In UK.pptxJohn William
This research paper writing service is tailored to microbiology students in the United Kingdom. Our skilled writers will work with you to create a high-quality, evidence-based research paper writing for microbiology In UK that fulfills the scientific community's exacting requirements. We ensure that your paper will be comprehensive, entertaining, and properly written based on our years of experience and thorough understanding of microbiology.
A data-intensive assessment of the species abundance distributionElita Baldridge
Doctoral defense for Elita Baldridge from the Weecology lab at Utah State University. Slides for the talk (defense_pres.pdf) and a transcript are available on GitHub with the analysis code to fully reproduce the analyses presented. In addition, a fully closed captioned video of the talk is available on YouTube.
https://github.com/weecology/sad-comparison
https://www.youtube.com/watch?v=tkXUD0MSRCo#t=202
Tom Dexheimer, Ph.D.
Manager, MSU Assay Development and Drug Repurposing Core
Michigan State University
Drug Discovery Interdisciplinary Event May 14, 2015
Open science framework – Jeff Spies, Centre for Open Science
Active research from lab to publication – Simon Coles, University of Southampton
Managing active research in the university – Robin Rice, University of Edinburgh
Making research available: FAIR principles and Force 11 - David De Roure, Oxford e-Research Centre
Jisc and CNI conference, 6 July 2016
1. A delineating procedure to retrieve
publication data in research areas – the case
of nanocellulose
Dr. Douglas Milanez
Centre for Technological Information in Materials/Federal University of São Carlos/Brazil
Dr. Ed Noyons
Centre for Science and Technology Studies /Leiden University/The Netherlands
15th International Conference on Scientometrics and
Informetrics- Stambul, 2015
2. The challenge to delineate
scientific research areas
• What is a research area, a field, discipline, topic?
• Global or local delineation?
• Classification systems indispensable tool
– Structure and dynamics of scientific fields
– “As old as science”
• Database classification
– Journal assignment
– Multidisciplinary/ general journals?
1
3. The challenge to delineate
scientific research areas
• Classification systems publication-level
initiatives:
– Text Similarity (Boyack et al., 2011)
• Medline database (2.15 million publications)
• More precise than the Medical Subject Headings
– Citation approach (Waltman & van Eck, 2012)
• Web of Science database (SCI and SSCI)
• Clustering algorithm and further criteria
• Labels extracted by text mining titles an abstracts
2
This study aims at proposing a delineation
procedure to retrieve publication data to
represent research areas
5. 4
Nanocellulose
• Sustainable nanomaterial
– Any natural sources
– Bacterial fermentation
• Two types
– cellulose nanofibrils
– cellulose nanocrystals
• Great potential for innovation
– Composite materials
– Packing material
– Electronic devices
– Texturizing agent
– Medical devices
6. From Wikipedia, the free encyclopedia
Nanocellulose is a term referring to nano-structured
cellulose.
This may be either cellulose nanofibers (CNF) also called
microfibrillated cellulose (MFC), nanocrystalline
cellulose (NCC), or bacterial nanocellulose, which refers
to nano-structured cellulose produced by bacteria.
5
7. But …
• There is no subject category to define nanocellulose
• The area is difficult to capture by keywords:
– Too narrow
– Too broad
6
8. Proposed approach
(a bit local and global)
• Use keyword search;
• Define core set: seed publications;
• Locate these seeds in classification;
• Check results;
• Define area by selection clusters from classification.
7
9. • Overall delineation procedure
8
Methodology
• Establishing a search
expression
• Web of Science
online database
Initial set of
publication
• CWTS Publication-
level classification
system
• Lowest level
Prior research
areas retrieving • Cluster content
analysis
• Cleaning terms
establishment
Cleaning initial
set of publication
• Final set of
publication
• Selecting relevant
research areas
Final retrieving
and selection
12. Initial set of nanocellulose publications
(seeds)
• Terms found on literature and from expert suggestions
• Web of Science
• Search expression:
11
("bacterial cellulos*") OR ("cellulos* crystal*") OR ("cellulos* nanocrystal*") OR
("cellulos* whisker*") OR ("cellulos* microcrystal*") OR ("cellulos* nanowhisker*")
OR ("nanocrystal* cellulos*") OR ("cellulos* nano-whisker*") OR ("cellulos* nano-
crystal*") OR ("nano-crystal cellulos*") OR ("cellulos* micro-crystal*") OR
("cellulos* microfibril*") OR ("microfibril* cellulos*") OR ("cellulos* nanofibril*") OR
("nanofibril* cellulos*") OR ("micro-fibril* cellulos*") OR ("nano-fibril* cellulos*")
OR ("cellulos* micro-fibril*") OR ("cellulos* nano-fibril*") OR ("cellulos*
nanofiber*") OR ("nanocellulos*") OR ("cellulos* nanoparticle*") OR ("nano-
cellulos*") OR ("nanoparticl* cellulos*") OR ("nanosiz* cellulos*") OR ("cellulos*
nanofill*") OR ("nano-siz* cellulos*") OR ("cellulos* nano-fiber*") OR ("cellulos*
nano-particle*") OR ("cellulos* nano-fill*") OR ("nano-particl* cellulos*"))
13. 12
Prior retrieve of nanocellulose research
areas
0
250
500
750
1000
1250
1500
1750
2000
2250
2500
2750
3000
0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500 525 550
NumberofPublications
Cluster (1- 533)
533
research
areas!
• 80% of clusters contained less than
three publications from the initial core
• Which clusters are relevant?
14. What information do we have per
cluster?
A. Number of publications in a cluster;
B. Number of publications retrieved by search strategy
(seed set);
C. Number of publications from seed per cluster.
13
15. First results
• Two clusters Nuclei research topics
– Contained 56.3% of the seed nanocellulose set;
– Their (automated) labels relate to nanocellulose terms
• Cellulose Nanocrystals and Cellulose Nanofibrils
• Bacterial Cellulose (type of cellulose nanocrystal)
Analysis of the nanocellulose pub. on peripheral clusters
14
NucleiPeripheral
16. Analyzing the relevance of the peripheral
research areas
• approach: check if an article was focusing on
nanocellulose or not:
– Reading each title (and abstract if needed)
– Nanocellulose should be the main subject
– Only articles from the seed set of nanocellulose publications
included on the cluster were checked
– A total of 20 peripheral clusters were checked
15
17. Percentage of noise of core-nanocellulose
publications on peripheral research areas
0,0
5,0
10,0
15,0
20,0
25,0
30,0
35,0
40,0
45,0
50,0
0,0
10,0
20,0
30,0
40,0
50,0
60,0
70,0
80,0
90,0
100,0
5.1.21
5.1.4
13.19.17
13.6.2
13.19.3
13.6.1
9.13.4
13.6.33
13.6.43
13.6.7
18.5.4
13.6.17
13.6.22
13.6.12
13.6.9
13.6.31
13.6.29
1.33.9
13.18.1
13.11.41
Percentageproportion
Percentageofnoisepublications
Research area
Left Axis Right Axis
16
Extremely
noised
research
areas
18. Improving the initial seed set of
nanocellulose publications
• Selecting terms from title and abstract:
text mining approach
• VOSviewer
• Terms to ‘clean’ the first set of
nanocellulose publications:
17
"gene" OR "xyloglucan" OR "microtubule" OR "*cyto*" OR "kinesi" OR "tubulin" OR
"*cell wall*" OR "spindle" OR "phragmoplast" OR "mitosis" OR "preprophase" OR
"phenotype" OR "*plant growth*" OR "meiosi" OR "*lignin distribution*" OR
"delignification" OR "hemicellulose" OR "saccharification" OR "ethanol yield" OR
"lignocellulos*" OR "glucosidase" OR "xylanase"
19. Effect of cleaning the initial set of
nanocellulose publications
• Checking performed on peripheral research topics
18
0
20
40
60
80
100
120
140
160
5.1.21
5.1.4
13.19.17
13.6.2
13.19.3
13.6.1
9.13.4
13.6.33
13.6.43
13.6.7
18.5.4
13.6.17
13.6.22
13.6.12
13.6.9
13.6.31
13.6.29
1.33.9
13.18.1
13.11.41
Numberofpublications
Research areas
Before cleaning After cleaning
Research
areas
related to
biology
20. Effect of cleaning the initial set of
nanocellulose publications
• Checking performed on nuclei research topics
19
0,0 1,0 2,0 3,0 4,0 5,0 6,0
"*cell wall*"
"*cyto*"
"*lignin distribution*"
"*plant growth*"
"delignification"
"ethanol yield"
"gene"
"glucosidase"
"hemicellulose"
"kinesi"
"lignocellulos*"
"meiosi"
"microtubule"
"mitosis"
"phenotype"
"phragmoplast"
"preprophase"
"saccharification"
"spindle"
"tubulin"
"xylanase"
"xyloglucan"
Percentage decrease
13.6.3
13.6.11
Cleaning
terms
The cleaning step
did not affected
significatively the
nuclei research
areas
21. Independence test
• Effect of cleaning procedure on the top five authors
• They are important researchers in the subject of nanocellulose
• Relevant authors to nanocellulose research
• Their position as the top authors did not changed at all
– Except for author E, who went down to the seventh position
20
Author
Number of publication Decrease (%)
Before After Overall Nuclei
A 87 78 -10,3 -6,33
B 51 40 -21,6 -14,9
C 50 43 -14 0
D 50 39 -22 -18,2
E 48 29 -39,6 -26,5
22. Final retrieving
• 2,600 nanocellulose publications (core-
nanocellulose)
– 428 research areas
– 81.0% clusters with one or two publications from the core-
nanocellulose
• Are they relevant?
• Selecting relevant research areas
– Pareto Principle (or 80/20 rule)
– Research areas with one or two publications not considered
• 85 clusters
21
23. 22
Selecting relevant research areas
• Pareto Principle:
0,0
10,0
20,0
30,0
40,0
50,0
60,0
70,0
80,0
90,0
100,0
0 10 20 30 40 50 60 70 80 90
Cumulativepercentagenumber
Reserch areas
12
Research
Topics
24. 23
Map of the Nanocellulose
main research topics
(local map of globally identified topics, c.f. Boyack)
Nuclei areas
25. • Delineating scientific fields is a complex task:
– Boundaries are not frequently well established since scientific studies
– More and more exchange of knowledge between scientists from
different disciplines is involved.
• Our approach retrieves and delineates the nuclei and the
peripheral research areas concerning nanocellulose
research
24
Conclusion and next steps
26. • Study the knowledge flow from peripheral research
topics to the nuclei areas.
• Map how they provide the necessary knowledge to face
nanocellulose current challenges and how country and
scientific institutions are contributing to this evolution.
25
Conclusion and next steps
Ed
The idea of this slide is to introduce the challenge to delineate scientific research areas.
I did not include any animation.
Suggestion:
You could start saying that classification system is always a subject to scientist as they like to categorize their research on a main area, such as chemistry, materials, engineering, etc. And it is as old as science.
Then, the link is that the databases have initiatives to classify science using the journal assignment, but this approach has the drawback of not dealing properly with multidisciplinary journals.
And currently, science has become more and more complex and interdisciplinary. For instance, how can we classify nanotechnology or biotechnology?
Ed
The idea here is to affirm that there area initiatives to classify the research areas using publication-level initiatives.
I included the CWTS approach and other one that we have cited in our article.
Both approaches were applied to a huge amount of papers indexed on databases.
The link to the animation is that few bibliometric research aimed at perform an analysis to a specific topic or subject.
This slide aims at presenting the subject: nanocellulose.
What is important to know to understand the analysis further present on the slides:
We can obtain nanocellulose from natural sources such as trees, natural fibers and agricultural waste
Basically, we have two types of nanocellulose and they differ on the degree of crystallinity. Cellulose nanocrystals are more crystalline than nanofibrils
The nanomaterial is interesting to innovation on new materials and devices
You can also say that nanocellulose was the main topic of my thesis, and this is an strategic nanomaterial for Brazil, as we can found a wide variety of sources for nanocellulose.
If you have any question, please, contact me.
Ed
The idea of this slide is to explain how the overall delineation procedure was conducted. It is important to highlight this is an interactive procedure.
You can focus on the white box, because the following slides will detail the methodology:
1) Determine an initial set of publication concerning the theme of interest
2) Prior retrieval of nanocellulose research areas
3) Analysis of retrieved research area and cleaning of the initial set
4) Final retrieval and selection of relevant nanocellulose research areas.
This slide and the next one explains the idea of our methodology.
Each sphere correspond to an article clustered using the CWTS approach and published by Waltman & van Eck, 2012
We want to find which cluster contains a nanocellulose-related publication.
This slide and the previous one explains the idea of our methodology.
Each sphere correspond to an article clustered using the CWTS approach and published by Waltman & van Eck, 2012
We want to find which cluster contains a nanocellulose-related publication and then evaluate which of this clusters selected are relevant to nanocellulose.
A search expression was developed considering several terms and synonyms recommended by experts and found in nanocellulose literature (Klemm et al., 2011; Milanez et al., 2013; Siqueira et al., 2010; Siró & Plackett, 2010), as can be seen from Table 1. The search expression encompassed different words that refer to cellulose nanocrystals, cellulose nanofibrils, and bacterial cellulose as well as other generic forms, such as nanocellulose, cellulose nanoparticles, and cellulose nanofiller. The search was conducted in March 31th 2014 in the online Web of Science database (topic search).
The idea of this slide is to present the prior retrieve process.
I think it is important to state that the number of publication from the X axis refers to the number of publication contained in each clusters, which includes nanocellulose publications
533 clusters were retrieved. The largest one contains 2,751 pub. while the smallest one contained 50 pub., as a criteria of the CWTS classification system.
Which are relevant?
The idea of this slide is to present the prior retrieve process.
Two clusters highlighted since they cluster more nanocellulose publication that the others and it was interesting that their labels reveled that they talk about types of nanocellulose .
It also says that nanocellulose has two important fields to describe it as a topic of research
However 80% of the retrieved research area clustered less than 3 pub.
And the important thing is: an evaluation of all research area retrieved would be too labour intensive, thus we made a selection of relevant clusters.
You can say that I (as a Dr. in Materials Science and Engineering) could judge whether the article focused on nanocellulose or not.
As cellulose is part from a complex of biological system, nanocellulose appeared in many studies. However, in many, the nanomaterial was not the focus.
As to the 20 peripheral research topics whose nanocellulose set of publication were evaluated, no direct correlation was observed between the proportional relevance of each clusters and the percentage of noise, according to Figure 5. Four research topics had a high percentage (>70%) of ‘noisy’ publications mainly focusing on biological issues of plants, ethanol production, and enzymes aspects, not having the nanomaterial as a final object of research.
The cleaning step focused on the first four cluster that were classified as extremely noised.
Since the first four clusters were used to select the cleaning terms, the cleaning affected them highly. Two of them were even eliminated. Furthermore, other peripheral clusters had their nanocellulose publication coverage diminished.
Half of the 22 terms we used to clean the nanocellulose search strategy did not affect the coverage of core-nanocellulose publications in the nuclei research areas, as depicted in Figure 4. To the other half, none term could reduce the coverage in more than 5%. The terms that influenced research area 13.6.4 the most were “*cell wall*” and “hemicelluloses” while “*cyto*”, “gene” and “*cell wall*” were the ones that decreased the most core-nanocellulose coverage in cluster 13.6.11. Overall, research topic 13.6.11 had its core-nanocellulose publication reduced in 17.5% while the decrease to cluster 13.6.3 was 10.2%. Nonetheless, both clusters still concentrated publication from the core-nanocellulose after the cleaning tasks (the proportion was 74.0% to research area 13.6.3 and 72.1% to 13.6.11). Therefore, they still had the status of nuclei research areas.
An independency test was conducted to evaluate the effectiveness of the procedure proposed. The test involved retrieving the number of publication from the top five authors before and after cleaning and selecting the relevant research areas. The percentage decreases of their overall number of publication and from their main cluster were verified.
We introduce here the Pareto Principle (or 80/20 rule). This principle states that “roughly 80% of the effects come from 20% of the causes” (Juran & Godfrey, 1998) and is found in bibliometric and library studies (Gupta, 1989; Kao, 2009; Stephens, Hubbard, Pickett, & Kimball, 2013). We hypothesize that 80% of the core set will be assigned to 20% of the areas. To reach these relevant research areas, the steps below were carried out:
1)The research areas were listed in descending order of the total number of publications from the core-nanocellulose;
2)Research topics with one or two publications from the core-nanocellulose were excluded. This yields 85 research areas remaining;
3)The representativeness of each research area was calculated by the number of publication of the core-nanocellulose of that cluster divided by 2,200 (which is the total of publication found in the 85 remaining research areas);
4)The cumulative percentage number of publications from the core-nanocellulose was obtained summing the values from the step before, as can be seen from Figure 3. The number of research to be assessed was those where the cumulative percentage number of publication reach approximately 80%.
We found that twelve research areas covered the required 80%, which means 14.1% of the total of 85 research topics. We do not claim that our selecting procedure was perfect, but a quick analysis of the chosen research topics showed themes currently found in nanocellulose literature.
According to Waltman and van Eck (2012), the lowest research area contain 50 publications, consequently, cluster with less than 1% of proportion were not account.
Figure 6 presents a map with these research topics (nodes). These themes appears frequently in nanocellulose-focused studies .The map positions the topics on the basis of their citation relations. The closer two topics, the more frequent the citation traffic between them. The node labels match the main content of the clusters. Moreover, all selected clusters had their set of nanocellulose publication evaluated in the cleaning task.