Category Archives: Science mapping

Empirical Panorama: Renewable Energy Cooperation Between Brazil and India (book chapter)

This chapter, Empirical Panorama: Renewable Energy Cooperation Between Brazil and India, which presents the main results obtained by the research and is divided into five sections. The first one presents data on the international acts signed jointly by Brazil and India concerning renewable energy. It also provides an analysis of documents resulting from the South-South meetings mainly regarding the participation of these two countries in multilateral groups. The second section tackles the renewable energy policies that have been established by Brazil and India in a period of over forty years. The third section brings the results of the scientific and technological mapping of Brazil and India based on the analysis of scientific publications. Furthermore, the patents filed by Brazil and India in renewables were mapped and a comparison was made between the scientific and technological production of both countries showing the main partnerships established between them. The fourth section presents the competitiveness indicators of the two countries based on the analysis of the competitiveness reports in a ten-year period: the indicators were compiled, compared and analyzed to identify elements that could promote or limit cooperation between Brazil and India. The fifth section presents the results of the primary research carried out with professionals from the academic, technical and political areas who work in one or more of these areas: energy, renewable energy, politics, international cooperation and international relations. All the data presented in the empirical panorama refer to the time period from 1945 to 2017/2018.

https://doi.org/10.1007/978-981-16-4877-9_5

Author(s): Arrais de Miranda Mousinho
Organization(s): Federal Institute of Education, Science and Technology (IFBA)
Source: Brazil-India Renewable Energy Cooperation
Year: 2021

Mapping the tuberculosis scientific landscape among BRICS countries: A bibliometric and network analysis (FULL-TEXT)

The five BRICS countries bear 49% of the world’s TB burden and they are committed to ending tuberculosis. This paper maps the scientific landscape related to TB research in BRICS. During the period 1993–2016, there were 38,315 peer-reviewed, among them, there were 11,018 (28.7%) articles related by one or more authors in a BRICS: India 38.7%; China 23.8%; South Africa 21.1%; Brazil 13.0%; and Russia 4.5% (The total was greater than 100% because our criterion was all papers with at least one author in a BRICS). Among the BRICS, there was greater interaction between India and South Africa and organizations in India and China had the highest productivity; however, South African organizations had more interaction with countries outside the BRICS. Publications by and about BRICS generally covered all research areas, especially those in India and China covered all research areas, although Brazil and South Africa prioritized infectious diseases, microbiology, and the respiratory system. An overview of BRICS scientific publications and interactions highlighted the necessity to develop a BRICS TB research plan to increase efforts and funding to ensure that basic science research successfully translates into products and policies to help end the TB epidemic. The bubble charts were generated by VantagePoint and the networks by the Gephi 0.9.1 software (Gephi Consortium 2010) from co-occurrence matrices produced in VantagePoint. The Fruchterman-Reingold algorithm provided the networks’ layout.

For FULL-TEXT see https://doi.org/10.1590/0074-02760190342

Author(s): Kamaiaji Castor, Fabio Batista Mota, Roseli Monteiro da Silva, Bernardo Pereira Cabral, Ethel Leonor Maciel, Isabela Neves de Almeida, Denise Arakaki-Sanchez, Kleydson Bonfim Andrade, Vadim Testov, Irina Vasilyeva, Yanlin Zhao, Hui Zhang, Manjula Singh, Raghuram Rao, Srikanth Tripathy, Glenda Gray, Nesri Padayatchi, Niresh Bhagwandin, Soumya Swaminathan, Tereza Kasaeva, Afrânio Kritski
Organization(s): Fundação Oswaldo Cruz-Fiocruz; Ministério da Saúde, Programa Nacional de Controle da Tuberculose; National Medical Research Centre of Pthtisiopulmonology and Infection Diseases, MoH; National Centre for Tuberculosis Control and Prevention, China CDC; University of KwaZulu-Natal
Source: Memórias do Instituto Oswaldo Cruz
Year: 2020

From Research to Industry: A Quantitative and Qualitative Analysis of Science-Technology Transferences and Emergence Patterns in Bioremediation

This article uses text mining techniques to determine the time lag of knowledge transfer between research activity and technology development in bioremediation, complementing these with advanced visualization techniques in order to extract patterns that could be of interest for decision making in this field. The emergence patterns in this field have been identified and a method based on subject-action-object (SAO) semantic structure is proposed for characterizing such patterns, using 2-word tuples. Our results show that technology developments in heavy metal bioremediation swiftly follow scientific advances, as opposed to developments in bioremediation of organic chemical components. The science mapping reveals three distinct areas: 1) heavy metal remediation and phytoremediation; 2) aerobic and anaerobic remediation of chemical elements; and 3) bioremediation techniques for treating specific contamination sources such as oil. The emergence analysis points at activities involving energy recovery by bioremediation, and shows an increasing amount of technologies involving specific strains of microorganisms, which could gain significant traction in this field in an estimated time horizon of ten years. Our SAO approach, tested on the data sample corresponding to these strains, proves to be useful for characterizing the emerging technologies when applied to instrumental concepts.

10.1109/TEM.2019.2936364

Author(s): Gaizka Garechana, Rosa Rio-Belver, Enara Zarrabeitia,  Izaskun Alvarez-Meaza

Organization(s): University of the Basque Country

Source: IEEE Transactions on Engineering Management

Year: 2019

Measuring and visualizing research collaboration and productivity (full-text)

This paper presents findings of a quasi-experimental assessment to gauge the research productivity and degree of interdisciplinarity of research center outputs. Of special interest, we share an enriched visualization of research co-authoring patterns.

We compile publications by 45 researchers in each of 1) the iUTAH project, which we consider here to be analogous to a “research center,” 2) CG1— a comparison group of participants in two other Utah environmental research centers, and 3) CG2—a comparison group of Utah university environmental researchers not associated with a research center. We draw bibliometric data from Web of Science and from Google Scholar. We gather publications for a period before iUTAH had been established (2010–2012) and a period after (2014–2016). We compare these research outputs in terms of publications and citations thereto. We also measure interdisciplinarity using Integration scoring and generate science overlay maps to locate the research publications across disciplines.

We find that participation in the iUTAH project appears to increase research outputs (publications in the After period) and increase research citation rates relative to the comparison group researchers (although CG1 research remains most cited, as it was in the Before period). Most notably, participation in iUTAH markedly increases co-authoring among researchers—in general; and for junior, as well as senior, faculty; for men and women: across organizations; and across disciplines.

The quasi-experimental design necessarily generates suggestive, not definitively causal, findings because of the imperfect controls.

This study demonstrates a viable approach for research assessment of a center or program for which random assignment of control groups is not possible. It illustrates use of bibliometric indicators to inform R&D program management. New visualizations of researcher collaboration provide compelling comparisons of the extent and nature of social networking among target cohort.ings of a

For full-text DOI: https://doi.org/10.2478/jdis-2018-0004

Author(s): Jon Garner, Alan L. Porter, Andreas Leidolf, Michelle Baker
Organization(s): Georgia Institute of Technology, Utah State Universit
Source: Journal of Data and Information Science (JDIS)
Year: 2018

Visualization of Disciplinary Profiles: Enhanced Science Overlay Maps

Purpose
The purpose of this study is to modernize previous work on science overlay maps by updating the underlying citation matrix, generating new clusters of scientific disciplines, enhancing visualizations, and providing more accessible means for analysts to generate their own maps.

Design/methodology/approach
We use the combined set of 2015 Journal Citation Reports for the Science Citation Index (n of journals = 8,778) and the Social Sciences Citation Index (n = 3,212) for a total of 11,365 journals. The set of Web of Science Categories in the Science Citation Index and the Social Sciences Citation Index increased from 224 in 2010 to 227 in 2015. Using dedicated software, a matrix of 227 × 227 cells is generated on the basis of whole-number citation counting. We normalize this matrix using the cosine function. We first develop the citing-side, cosine-normalized map using 2015 data and VOSviewer visualization with default parameter values. A routine for making overlays on the basis of the map (“wc15.exe”) is available at http://www.leydesdorff.net/wc15/index.htm.

Findings
Findings appear in the form of visuals throughout the manuscript. In Figures 1–9 we provide basemaps of science and science overlay maps for a number of companies, universities, and technologies.

Research limitations
As Web of Science Categories change and/or are updated so is the need to update the routine we provide. Also, to apply the routine we provide users need access to the Web of Science.

Practical implications
Visualization of science overlay maps is now more accurate and true to the 2015 Journal Citation Reports than was the case with the previous version of the routine advanced in our paper.

Originality/value
The routine we advance allows users to visualize science overlay maps in VOSviewer using data from more recent Journal Citation Reports.

https://www.degruyter.com/view/j/jdis.2017.2.issue-3/jdis-2017-0015/jdis-2017-0015.xml

Author(s): Stephen Carley, Alan L. Porter, Ismael Rafols, Loet Leydesdorff
Organization(s): Georgia Institute of Technology , Universitat Politècnica de València, University of Amsterdam
Source: Journal of Data and Information Science
Year: 2017

Tracking the emergence of synthetic biology (full-text)

Synthetic biology is an emerging domain that combines biological and engineering concepts and which has seen rapid growth in research, innovation, and policy interest in recent years. This paper contributes to efforts to delineate this emerging domain by presenting a newly constructed bibliometric definition of synthetic biology. Our approach is dimensioned from a core set of papers in synthetic biology, using procedures to obtain benchmark synthetic biology publication records, extract keywords from these benchmark records, and refine the keywords, supplemented with articles published in dedicated synthetic biology journals. We compare our search strategy with other recent bibliometric approaches to define synthetic biology, using a common source of publication data for the period from 2000 to 2015. The paper details the rapid growth and international spread of research in synthetic biology in recent years, demonstrates that diverse research disciplines are contributing to the multidisciplinary development of synthetic biology research, and visualizes this by profiling synthetic biology research on the map of science. We further show the roles of a relatively concentrated set of research sponsors in funding the growth and trajectories of synthetic biology. In addition to discussing these analyses, the paper notes limitations and suggests lines for further work.

Full-text via Open Access at
https://link.springer.com/article/10.1007/s11192-017-2452-5

Author(s): Philip Shapira, Seokbeom Kwon, Jan Youtie
Organization(s): University of Manchester, Georgia Institute of Technology
Source: Scientometrics
Year: 2017

Mapping the dengue scientific landscape worldwide: a bibliometric and network analysis (full-text)

Despite the current global trend of reduction in the morbidity and mortality of neglected diseases, dengue’s incidence has increased and occurrence areas have expanded. Dengue also persists as a scientific and technological challenge since there is no effective treatment, vaccine, vector control or public health intervention. Combining bibliometrics and social network analysis methods can support the mapping of dengue research and development (R&D) activities worldwide.

We use scientific publication data from Web of Science Core Collection – articles indexed in Science Citation Index Expanded (SCI-EXPANDED) – and combine bibliometrics and social network analysis techniques to identify the most relevant journals, scientific references, research areas, countries and research organisations in the dengue scientific landscape.

Our results show a significant increase of dengue publications over time; tropical medicine and virology as the most frequent research areas and biochemistry and molecular biology as the most central area in the network; USA and Brazil as the most productive countries; and Mahidol University and Fundação Oswaldo Cruz as the main research organisations and the Centres for Disease Control and Prevention as the most central organisation in the collaboration network.

For full-text, http://www.scielo.br/scielo.php?pid=S0074-02762017005005103&script=sci_arttext&tlng=en

Author(s): Fabio Batista Mota, Bruna de Paula Fonseca e Fonseca, Andréia Cristina Galina, Roseli Monteiro da Silva
Organization(s): Fundação Oswaldo Cruz-Fiocruz
Source: Memórias do Instituto Oswaldo Cruz
Year: 2017

Aesthetics in the age of digital humanities

One of the most difficult but yet unavoidable tasks for every academic field is to define its own nature and demarcate its area. This article addresses the question of how current computational text-mining approaches can be used as tools for clarifying what aesthetics is when such approaches are combined with philosophical analyses of the field. We suggest that conjoining the two points of view leads to a fuller picture than excluding one or the other, and that such a picture is useful for the self-understanding of the discipline. Our analysis suggests that text-mining tools can find sources, relations, and trends in a new way, but it also reveals that the databases that such tools use are presently seriously limited. However, computational approaches that are still in their infancy in aesthetics will most likely gradually affect our understanding about the ontological status of the discipline and its instantiations.

Open Access article…. for full-text, click http://www.aestheticsandculture.net/index.php/jac/article/view/30072

Author(s): Ossi Naukkarinen and Johanna Bragge
Organization: Aalto University School of Arts, Design and Architecture; Aalto University School of Economics
Source: Journal of Aesthetics and Culture
Year: 2016

Map of science with topic modeling: Comparison of unsupervised learning and human-assigned subject classification

The delineation of coordinates is fundamental for the cartography of science, and accurate and credible classification of scientific knowledge presents a persistent challenge in this regard. We present a map of Finnish science based on unsupervised-learning classification, and discuss the advantages and disadvantages of this approach vis-à-vis those generated by human reasoning. We conclude that from theoretical and practical perspectives there exist several challenges for human reasoning-based classification frameworks of scientific knowledge, as they typically try to fit new-to-the-world knowledge into historical models of scientific knowledge, and cannot easily be deployed for new large-scale data sets. Automated classification schemes, in contrast, generate classification models only from the available text corpus, thereby identifying credibly novel bodies of knowledge. They also lend themselves to versatile large-scale data analysis, and enable a range of Big Data possibilities. However, we also argue that it is neither possible nor fruitful to declare one or another method a superior approach in terms of realism to classify scientific knowledge, and we believe that the merits of each approach are dependent on the practical objectives of analysis.

Full-text available at http://onlinelibrary.wiley.com/doi/10.1002/asi.23596/full

Author(s): Arho Suominen and Hannes Toivanen
Organization(s): VTT Technical Research Centre of Finland Ltd
Source: Journal of the Association for Information Science and Technology
Year: 2015

Patent overlay maps: Spain and the Basque Country

This study uses the new global patent map developed by Kay et al. (2014) to reflect the patenting activity of Spain together with the activity of the Basque Country, a highly industrialised region in Spain, for the time interval 2000-2006. The global patent map reflects the technology categories where a patent could be categorised according to the international patent classification (IPC) system, in addition to the degree of similarity among different IPCs, determined by using the citing-to-cited relationships as bonds between categories. An overlay method has been developed to compare, on the one hand, the patenting activity in Spain and the Basque Country and a display of the most important technology sectors and; on the other, the selection of a technology sector and an analysis of technology transfer in both regions through different IPCs to compare them and determine the possible technological sources remaining for development.

http://www.inderscienceonline.com/doi/abs/10.1504/IJTM.2015.072976

Author(s): Javier Gavilanes-Trapote, Rosa María Río-Belver, Ernesto Cilleruelo, Gaizka Garechana, Jaso Larruscain
Organization(s): University of the Basque Country
Source: International Journal of Technology Management
Year: 2015