All posts by VPInstitute

How to Identify Cooperation Partners based on multisource data

CTI, Research Examples, Research Type, Strategic planning, Uncategorized

This study aims at identifying potential industry-University-research institution collaborations partners (IURC) efficaciously and analyzes the conditions and dynamics in the IURC process, based on knowledge potential and the knowledge spillover theory. Furthermore, a new identification method is constructed that takes into account the law of scientific research cooperation and economic factors. The method utilizes multisource data, combining bibliometric and econometrics analyses to achieve the network core of the existing collaboration network, and institution competitiveness in the innovation chain. Empirical analysis of the genetic engineering vaccine field shows that throughout the distribution characteristics of creative technologies from different institutions, the analysis based on the innovation chain can identify more complementarities between institutions. Compared to previous studies, this study emulates the real conditions of IURC. The rule of technological innovation can be better revealed, potential partners of IURC can be more easily identified, and the conclusion has a higher value in consultation. In particular, diverse informative indices can assist researchers in deriving appropriate partners for research and development cooperation.

https://doi.org/10.1145/3110025.3110142

Author(s): Haiyun Xu, Kun Dong, Ling Wei, Chao Wang, Shu Fang
Organization(s): Chengdu Documentation and Information Center, CAS; University of Chinese Academy of Sciences
Source: Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
Year: 2017

Air bearing: academic insights and trend analysis

Research Examples, Research profiling

The development of air bearing demands further research and certain guidance. The previous technical reviews focused on specific aspects, while bibliometric analysis employed in this paper gave a general overview on air bearing field and provided clearer research interest and development trend. The publications in the field of air bearing from 1990 to 2017 based on the Science Citation Index Expanded (SCIE) database were analyzed from the aspects of countries, institutions, research areas, journals, authors, keywords, reviews, and high cited papers, implemented by some representative and convincing indicators. The result showed that the USA held the dominant position in this field, followed by Japan and China. The University of California System held the top position in terms of total papers and h-indexes. It had shown a multi-disciplinary development trend of air bearings from the aspect of research area. Tribology related journal took high ranking of the list, in which “Journal of Tribology-Transactions of the ASME” ranked first. Bogy, D. B., made most contributions to the air bearing field, with the highest total citations and h-index. Thermal effects, foil bearing, dynamic analysis, and active compensation were hotspots. Reynolds equation, stability, optimization, load-carrying capacity, foil bearings, and aerostatic bearings were potential directions that might have greater opportunities for improvement. The improvement of air bearing requires common progress in multiple aspects.

https://doi.org/10.1007/s00170-019-04663-5

Author(s): Guoda Chen, Bingfeng Ju, Hui Fang, Yijie Chen, Nan Yu, Yuehua Wan

Organization(s): Zhejiang University of Technology

Source: The International Journal of Advanced Manufacturing Technology

Year: 2019

Academic Review and Perspectives on Robotic Exoskeletons (FULL-TEXT)

Research Examples, Research profiling

Since the first robotic exoskeleton was developed in 1960, this research field has attracted much interest from both the academic and industrial communities resulting in scientific publications, prototype developments and commercialized products. In this article, to document the progress in and current status of this field, we performed a bibliometric analysis. This analysis evaluated the publications in the field of robotic exoskeletons from 1990 to July 2019 that were retrieved from the Science Citation Index Expanded database. The bibliometric analyses were presented in terms of author keywords, year, country, institution, journal, author, and the citation. Results show that currently the United States has taken the leading position in this field and has built the largest collaborative network
with other countries. The Massachusetts Institute of Technology (MIT) made the greatest contribution to the field of robotic exoskeleton investigations in terms of the number of publications, average citations per publication and the h-index. In addition, the Journal of Neuro Engineering and Rehabilitation ranks first among the top 20 academic journals in terms of the number of publications related to robotic exoskeletons during the period investigated. Author keyword analysis indicates that most research has focused on rehabilitation robotics. Biomedical engineering, rehabilitation and the neurosciences are the most common disciplines conducting research in this area according to the Web of Science (WoS). Our study comprehensively assesses the current research status and collaboration network of robotic exoskeletons, thus helping researchers steer their projects or locate potential collaborators.

10.1109/TNSRE.2019.2944655

FULL-TEXT 

Author(s): Guanjun Bao, Lufeng Pan , Hui Fang, Xinyu Wu , Haoyong Yu ,
Shibo Cai, Bingqing Yu, and Yuehua Wan

Organization(s): Zhejiang University of Technology; Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences

Source: IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING

Year: 2019

Patent Portfolio Model for Measuring Strategic Technological Strength

Patents, Research Examples, Tech mining

As technological innovation plays important role in today’s knowledge economy, intellectual property as the most important output of technological development is valued highly for generating monopoly position in providing payoffs to innovation. Intellectual Property Management (IPM) helps organizations to identify, enhance and evaluate their technological strength. Patent portfolio Model (PPM) is built for assessing the advantages and disadvantages of organization, identifying the opportunities of development potentials and optimal distribution, to support the decision-making for optimizing resource allocation and developing layout for technical field. The case study of research institute in china show that this method is feasible and fulfilled the needs of different institutions, so as to provide suggestions for R&D technology management.

10.23919/PICMET.2019.8893967

Author(s): Li Shuyin, Zhang Xian,  Xu Haiyun,  Fang Shu

Organization(s): Chengdu Library and Information Center, Chinese Academy of Sciences

Source:  IEEE Xplore: 2019 Portland International Conference on Management of Engineering and Technology (PICMET)

Year: 2019

Early childhood caries Scientometric indicators 2000-2017 (Caries de la infancia temprana Indicadores cienciométricos 2000 a 2017) FULL-TEXT

Research Examples, Research profiling

The authors present in this document the results of the bibliometric and scientometric analyses related to research articles about dental caries and early childhood, published in journals indexed in Scopus from 2000 to 2017. The following indicators were extracted from the analyzed datasets: general, and specific for Latin America and Colombia, output and collaboration indicators (publication output by year, affiliation countries, affiliations, authors and journals). On the other hand, the scientometric analysis was performed by grouping the keywords into four conceptual categories: prevalent microorganisms, diet, mother-child pair, and hygiene. The resulting indicators were obtained by applying the aggregation levels mentioned above. Finally, the world-wide patent application activity was analyzed in order to complete the research and development trends related to the topics of this study.

FULL-TEXT https://doi.org/10.15332/978-958-8477-70-1

Author(s): Lofthy Piedad Mejía-Lora, César Augusto Acevedo-Argüello

Organization(s): Universidad Santo Tomás

Source: Colección: Estudios de Bibliometría y Vigilancia Tecnológica

Year: 2019

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

Research Examples, Research Type, Science mapping

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

Evaluating technological emergence using text analytics: two case technologies and three approaches (FULL-TEXT)

Research Examples, ST&I indicators

Scientometric methods have long been used to identify technological trajectories, but we have seldom seen reproducible methods that allow for the identification of a technological emergence in a set of documents. This study evaluates the use of three different reproducible approaches for identifying the emergence of technological novelties in scientific publications. The selected approaches are term counting technique, the emergence score (EScore) and Latent Dirichlet Allocation (LDA). We found that the methods provide somewhat distinct perspectives on technological. The term count based method identifies detailed emergence patterns. EScore is a complex bibliometric indicator that provides a holistic view of emergence by considering several parameters, namely term frequency, size, and origin of the research community. LDA traces emergence at the thematic level and provides insights on the linkages between emerging research topics. The results suggest that term counting produces results practical for operational purposes, while LDA offers insight at a strategic level.

For FULL-TEXT https://doi.org/10.1007/s11192-019-03275-w

Author(s): Samira Ranaei, Arho Suominen, Alan Porter, Stephen Carley

Organization(s): VTT Technical Research Centre of Finland, Lappeenranta University of Technology, Search Technology

Source: Scientometrics

Year: 2019

Calculate Emergence with “check for a term to grow”

VP Macros

This version incorporates the new check for a term to grow at 1.5 times the overall dataset growth in place of the 2:1 Analysis:Base Year record count ratio requirement.

There is no change to the scoring calculation used in this VPInstitute version and the Calculate Emergence Indicators version executed from the toolbar of VP Student Edition or VantagePoint. The change in this VPInstitute version of the script applies to how the terms are filtered to remove “common” terms in relation to the dataset. This version checks that each term is growing faster in use than the growth of the overall dataset.

Calculate Emergence Indicators zip file

A few caveats to use it:

  1. Once downloaded, unzip and drop into the VantagePoint\Macros installation directory. Note that it’s possible some files will be either blocked by Windows – thus will need to right click the file->Properties->Click Unblock.
  2. It’s also possible that some of the files will be given an “unsafe” file extension. Literally something like “Emergence.html.unsafe”. If that is the case you will need to rename the file and remove the “.unsafe” bit at the end. Windows will warn you about doing this but go ahead anyway. If you hit any errors trying to run the script or something isn’t loading right then 1 or 2 is likely the cause.
  3. If you are comparing results of this version with the commercial version of the script, and you’ve selected the same Term and Year field, then the score for a given term should be the same between the two versions. It just might not appear in both lists due to the change in filtering. Which version is “right” is subjective in this case.

Long term prevention and vector control of arboviral diseases: What does the future hold? (FULL-TEXT)

Research Examples, Research profiling

Arboviral diseases are a global growing problem due to climate change, urbanization, population density, and global transportation. However, new technologies currently being developed in research labs are expected to play a relevant role in combatting arboviral diseases in the future, reducing the health and economic burden imposed by these diseases. This paper aims to anticipate the technologies that might be relevant for prevention and vector control of arboviral diseases in the future. A web-based survey was conducted of over 2,000 experts from all over the world. Both the technologies and the respondents were identified from recent scientific publications on arboviral diseases indexed in the Web of Science Core Collection. Our results show that within 20 years the enveloped virus-like particles-based vaccine and the gene-edited mosquitoes through CRISPR/Cas9 will likely be the most promising technologies for, respectively, prevention and vector control of arboviral diseases. If these expectations are confirmed, these new technologies, when fully developed, may support global public health efforts aimed at reducing transmission, mortality and morbidity of arboviral diseases.

For FULL-TEXT https://www.ijidonline.com/article/S1201-9712(19)30394-7/fulltext

Author(s): Bernardo Pereira Cabral, Maria da Graça Derengowski Fonseca, Fabio Batista Mota

Organization(s): Fundação Oswaldo Cruz, a, Universidade Federal da Bahia, Universidade Federal do Rio de Janeiro

Source: International Journal of Infectious Diseases

Year: 2019

Collaborative networks in gene editing

Research Examples, Research profiling

Over 15,000 articles and reviews published since 2000 were collected, with genome editing-related queries in the Web of Science (Table 1 and Supplemental Table S1). We use tech mining to investigate the underlying patterns that drive the adoption of genome editing, proposing an integrated research framework with bibliometrics, text analyses, and network analysis to analyze publication trends, authorship patterns, and key research topics and technologies of the genome editing field and provide quantitative and qualitative insights into the drivers of the CRISPR craze. Of the literature on gene-editing modalities, CRISPR-Cas continues to grow, whereas publications describing meganucleases, zinc-finger nucleases, and transcription activator-like effector nuclease (TALENs) have been decreasing since 2016. The top 5 nations contributing gene-editing research are the United States, China, Germany, the United Kingdom, and Japan, with papers from China growing fastest.  A diverse set of collaborative authors provides both leadership in the field and globalized contributions to the literature across space, time, and disciplines. The collaborative nature of this field is underscored by each of the 15 leading authors in the field (Table 2), all working with at least one fellow leading author, with 10 of the 15 co-authoring manuscripts with at least 2 other leading authors, and 4 highly collaborative authors contributing manuscripts with three or more prolific colleagues.

http://dx.doi.org/10.1038/s41587-019-0275-z

Author(s): Ying Huang, Alan Porter, Yi Zhang & Rodolphe Barrangou

Organization(s): Wuhan University, Georgia Institute of Technology, University of Technology Sydney, North Carolina State University

Source: Nature Biotechnology (Data Page)

Year: 2019