All posts by VPInstitute

Interdisciplinary knowledge combinations and emerging technological topics: Implications for reducing uncertainties in research evaluation (FULL-TEXT)

This article puts forth a new indicator of emerging technological topics as a tool for addressing challenges inherent in the evaluation of interdisciplinary research. We present this indicator and test its relationship with interdisciplinary and atypical research combinations. We perform this test by using metadata of scientific publications in three domains with different interdisciplinarity challenges: Nano-Enabled Drug Delivery, Synthetic Biology, and Autonomous Vehicles. Our analysis supports the connection between technological emergence and interdisciplinarity and atypicality in knowledge combinations. We further find that the contributions of interdisciplinary and atypical knowledge combinations to addressing emerging technological topics increase or stay constant over time. Implications for policymakers and contributions to the literature on interdisciplinarity and evaluation are provided.

doi.org/10.1093/reseval/rvaa029

Author(s): Seokbeom Kwon, Jan Youtie, and Alan L. Porter
Organization(s): The University of Tokyo, Georgia Institute of Technology
Source: Research Evaluation
Year: 2020

Scientific publications and COVID-19 “research pivots” during the pandemic: An initial bibliometric analysis (FULL-TEXT pre-print)

An examination is presented of scientific research publication trends during the global coronavirus (COVID-19) pandemic in 2020. After reviewing the timing of the emergence of the pandemic in 2020 and the growth of governmental responses, available secondary and sources are used to highlight impacts of COVID-19 on scientific research. A bibliometric analysis is then undertaken to analyze developments in COVID-19 related scientific publications through to October of 2020 by broad trends, fields, countries, and organizations. Two publication data sources are used: PubMed and the Web of Science.

While there has been a massive absolute increase in PubMed and Web of Science papers directly focused on COVID-19 topics, especially in medical, biological science, and public health fields, this is still a relatively small proportion of publication outputs across all fields of science. Using Web of Science publication data, the paper examines the extent to which researchers across all fields of science have pivoted their research outputs to focus on topics related to COVID-19. A COVID-19 research pivot is defined as the extent to which the proportion of output in a particular research field has shifted to a focus on COVID-19 topics in 2020 (to date) compared with 2019. Significant variations are found by specific fields (identified by Web of Science Subject Categories). In a top quintile of fields, not only in medical specialties, biomedical sciences, and public health but also in subjects in social sciences and arts and humanities, there are relatively high to medium research pivots. In lower quintiles, including other subjects in science, social science, and arts and humanities, low to zero COVID-19 research pivoting is identified.

For FULL-TEXT of this pre-print see tab at https://doi.org/10.1101/2020.12.06.413682

Author(s): Philip Shapira
Organization(s): The University of Manchester
Source: bioRxiv
Year: 2020

Tracking and Mining the COVID-19 Research Literature (FULL-TEXT)

The unprecedented, explosive growth of the COVID-19 domain presents challenges to researchers to keep up with research knowledge within the domain. This article profiles this research to help make that knowledge more accessible via overviews and novel categorizations. We provide websites offering means for researchers to probe more deeply to address specific questions. We further probe and reassemble COVID-19 topical content to address research issues concerning topical evolution and emphases on tactical vs. strategic approaches to mitigate this pandemic and reduce future viral threats. Data suggest that heightened attention to strategic, immunological factors is warranted. Connecting with and transferring in research knowledge from outside the COVID-19 domain demand a viable COVID-19 knowledge model. This study provides complementary topical categorizations to facilitate such modeling to inform future Literature-Based Discovery endeavors.

For FULL-TEXT  https://doi.org/10.3389/frma.2020.594060

Author(s): Alan L. Porter, Yi Zhang, Ying Huang, and Mengjia Wu
Organization(s): Search Technology, University of Technology Sydney
KU Leuven
Source: Frontiers in Research Metrics and Analytics
Year: 2020

Bibliometric Analysis of Research Hotspots Related to Marine Oil Spill Accidents in the Environmental Field Based on Web of Science

The objective of this paper is to conduct bibliometric analysis of the relevant literature in the environmental field published from 1982 to 2018 collected by the Web of Science citation database and further explore the frontier research dynamics and hotspots in the environmental field. The word “oil spill*” was used as the subject term for retrieval. A knowledge map of hotspots in oil spill research was built through software VOSviewer and the clustering relations between them were explored. The frequency and relevance of the keywords in the corresponding literature were obtained by the matrix of keywords built through the Thomson Data Analyzer (TDA)software. The four main research hotspots of marine oil spill pollution were oil spill numerical simulation and model prediction, oil spill exposure toxicity and risk assessment, oil spill component and source analysis and oil spill pollution characteristics and treatment. The study analyzes the main content of the four research hotspots and the current research progress and provides scientific basis for further understanding of the mechanism of marine oil spill occurrence, migration and transformation, implementation of oil spill treatment and repair as well as more accurate assessment of eco-environment damage.

DOI: 10.12116/j.issn.1004-5619.2020.04.005

Author(s): J Wu, M Wang, C M Ye, Z H Xu, C Y Sha, J Y Zhang, S F Huang
Organization(s): Shanghai Academy of Environmental Sciences, East China Normal University
Source: Journal of Forensic Medicine
Year: 2020

The effect of competitive public funding on scientific output: A comparison between China and the EU

Public funding is believed to play an important role in the development of science and technology. However, whether public funding and, in particular, competitive funding from public agencies actually helps to increase scientific output (i.e. publications) remains a matter of debate. By analysing a dataset of co-publications between China and the EU and a dataset of joint project collaborations in European Framework Programs for Research and Innovation [FP7 and Horizon 2020 (H2020)], we investigate whether different public funding agencies’ competitive assets have different impact on the volume of publication output. Our results support the hypotheses that competitively funded research output varies by funding sources, so that a high level of funding does not necessarily lead to high scientific output. Our results show that FP7/H2020 funded projects do not have a positive contribution to the output of joint publications between China and the EU. Interestingly, cooperation in the form of jointly writing proposals to these EU programmes, especially when they are not granted by the European Commission, can contribute significantly to joint scientific publications in a later stage. This applies in particular to cases where funding from China is involved. Our findings highlight the key role that funding agencies play in influencing research behaviour. Our results indicate that Chinese funding triggers a high number of publications, whereas research funded by the EU does so to a much lower extent, arguably due to the EU’s strong focus on social impact and its funding schemes as tools to promote European integration.

https://doi.org/10.1093/reseval/rvaa023

Author(s): Lili Wang, Xianwen Wang, Fredrik Niclas Piro, Niels J Philipsen
Organization(s): Maastricht University, Dalian University of Technology, Nordic Institute for Studies in Innovation, Erasmus University Rotterdam
Source: Research Evaluation
Year: 2020

Mining Technological Innovation Talents Based on Patent Index using t-SNE Algorithms*: Take the Field of Intelligent Robot as an Example

The purpose of this paper is to effectively evaluate the innovation ability and classification of technical talents in the intelligent robot field, and to be able to carry out adaptive learning and mining technical innovation talents according to the real-time change data corresponding to different indicators. Taking inventor’s patent information retrieved and cleaned from DI database as research object, it constructs the evaluation index system of technological innovation talents. It reduces the dimension of the index and cluster automatically, shows the visual effect, and mines the similar technical innovation talents through t-SNE algorithm. For a large number of patent information data, machine learning algorithm improves the traditional recognition method. According to inventor similarity, automatic classification is realized. Combined with DWPI manual code mining, the corresponding innovators and members of the technical team in the intelligent robot technology field were found. According to the results of visual dimensional reduction, the specific inventors can be traced. Machine learning algorithm t-SNE can reduce dimension and analysis clustering. It breaks the limitations of artificial statistics, deals with the larger order of magnitude data, and analyzes data timely, accurate and intuitive.

10.1109/ICAICA50127.2020.9182541

Author(s): Ning Zhao, Guohui Yang, Yang Cao
Organization(s): Harbin Institute of Technology
Source: 2020 IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA)
Year: 2020

Neglected tropical diseases in Brazil: lack of correlation between disease burden, research funding and output

Objectives
To assess the correlation between the burden of seven priority neglected tropical diseases (NTDs) included in the Brazilian National Agenda of Priorities in Health Research – tuberculosis, Chagas disease, leprosy, malaria, leishmaniasis, dengue and schistosomiasis – and their respective research funding and output.

Methods
This retrospective review obtained data on disease burden from the Global Burden of Disease Study and funding data from open access sources. Publications were retrieved from Scopus and SciELO, and characterised according to the type of research conducted. Correlation between funding, research output and burden was assessed by comparing the ‘expected’ and ‘observed’ values for funding and publications relative to the proportional burden for each disease.

Results
There was an emphasis in basic biomedical research (average 30% of publications) and a shortage of health policy and systems (average 7%) and social sciences research (average 3%). Research output and funding were poorly correlated with disease burden. Tuberculosis, Chagas disease and schistosomiasis accounted for more than 75% of total NTD‐related DALYs, but accounted for only 34% of publications. Leprosy, leishmaniasis and malaria, together, received 49% of NTD‐related funding despite being responsible for only 9% of DALYs.

Conclusions
The analysis evidenced a lack of correlation between disease burden, research output and government funding for priority NTDs in Brazil. Our findings highlight the importance of monitoring health needs, research investments and outputs to inform policy and optimise the uptake of evidence for action, particularly in developing countries, where resources are scarce and the research capacity is limited. The results contribute to health policy by highlighting the need for improving coordination of scientific activities and public health needs for effective impact.

https://doi.org/10.1111/tmi.13478

Author(s): Bruna de Paula Fonseca, Priscila Costa Albuquerque, Fabio Zicker
Organization(s): Oswaldo Cruz Foundation (Fiocruz)
Source: Tropical Medicine & International Health
Year: 2020

Framework of Computational Intelligence-Enhanced Knowledge Base Construction: Methodology and A Case of Gene-Related Cardiovascular Disease (FULL-TEXT)

Knowledge base construction (KBC) aims to populate knowledge bases with high-quality information from unstructured data but how to effectively conduct KBC from scientific documents with limited preknowledge is still elusive. This paper proposes a KBC framework by applying computational intelligent techniques through the integration of intelligent bibliometrics—e.g., co-occurrence analysis is used for profiling research topics/domains and identifying key players, and recommending potential collaborators based on the incorporation of a link prediction approach; an approach of scientific evolutionary pathways is exploited to trace the evolution of research topics; and a search engine incorporating with fuzzy logics, word embedding, and genetic algorithm is developed for knowledge searching and ranking. Aiming to examine and demonstrate the reliability of the proposed framework, a case of gene-related cardiovascular diseases is selected, and a knowledge base is constructed, with the validation of domain experts.

For FULL-TEXT https://doi.org/10.2991/ijcis.d.200728.001

Author(s): Yi Zhang, Mengjia Wu, Hua Lin, Steven Tipper, Mark Grosser, Guangquan Zhang, Jie Lu
Organization(s): University of Technology Sydney, 23 Strands
Source: International Journal of Computational Intelligence Systems
Year: 2020

Probing Expert Opinions on the Future of Kidney Replacement Therapies

Patients with kidney failure can only survive with some form of kidney replacement (transplant or dialysis). Unfortunately, innovations in kidney replacement therapy lag behind many other medical fields. This study compiles expert opinions on candidate technologies for future kidney replacement therapies. A worldwide web‐based survey was conducted with 1,566 responding experts, identified via a text-mining process of scientific publications on kidney (renal) replacement therapy, indexed in the Web of Science Core Collection (period 2014‐2019). Candidate innovative approaches were categorized in line with the Kidney Health Initiative roadmap for innovative kidney replacement therapies. Most respondents expected a revolution in kidney replacement therapies: 68.59% before 2040 and 24.85% after 2040, while 6.56% expected none. Approaches anticipated as most likely were implantable artificial kidneys (38.6%) and wearable artificial kidneys (32.4%). A majority of experts expect that kidney replacement therapies can be significantly improved by innovative technologies.

https://doi.org/10.1111/aor.13784

Author(s): Bernardo Pereira Cabral, Joseph V. Bonventre , Fokko Wieringa , Fabio Batista Mota
Organization(s): Oswaldo Cruz Foundation, Harvard Medical School, Maastricht University
Source: Artificial Organs                                                                                              Year: 2020

Twenty-five years’ contribution of “Benchmarking: an International Journal” to manufacturing strategy: a scientometric review

This study aims at reviewing the articles on the themes of manufacturing strategy (MS) published in “Benchmarking: An International Journal (BIJ)” and investigating the trends of publication for future research. Five-stage methodology to conduct a literature review is adopted comprising: (1) article collection, (2) inclusion/exclusion criteria, (3) reviewing the articles, (4) analyzing the articles and (5) future research directions. A total of 57 articles specific to MS domain published in BIJ are reviewed. Further, a bibliometric analysis comprising keywords co-occurrence, citation and co-citation using a VOSviewer software followed by content analysis using VantagePoint software to analyze the type of research, type of industry and type of tool/method used is carried out. The study helps to find the scope of the journal and research gaps in the MS domain to provide future research directions. Most of the work found is survey-based or case-based in nature. However, there is a need for empirical research to be done in the field of MS.The study facilitates researchers willing to publish in BIJ to understand different themes of accepted papers concerning MS domain. The identified research gaps and future research direction can motivate researchers and practitioners to coin new approaches in the MS domain. A comprehensive review and analysis of the MS literature published in BIJ has been provided. To the best of authors’ knowledge, the current study is the only review study in MS domain focusing on one specific journal.

https://doi.org/10.1108/BIJ-06-2020-0316

Author(s): Vishwas Dohale, Angappa Gunasekaran, Milind M. Akarte, Priyanka Verma
Organization(s): National Institute of Industrial Engineering/India, California State University Bakersfield
Source: Benchmarking: An International Journal
Year: 2020