Category Archives: Data Type

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

Do national funding organizations properly address the diseases with the highest burden? – Observations from China and the UK (Full-Text)

Recent years have witnessed an incipient shift in science policy from a focus mainly on academic excellence to a focus that also takes into account “societal impact”. This shift raises the question as to whether medical research has given proper attention to the diseases imposing the greatest burden on society. Therefore, with the aim of identifying correlations between research funding priorities and public demand in health, we examine grants issued by the major medical research funding bodies of China and the UK during the decade 2006-2017 and compare the focus of their funded projects with the diseases that carry the highest burden of death, risk, or loss of health. The results indicate that the funding decisions of both nations do correspond to the illnesses with the highest health impact on their citizens. For both regions, the greatest health concerns surround non-communicable diseases, and neoplasms and cardiovascular disease in particular. In China, national health priorities have remained focused on these illnesses for the benefit of its own population, whereas the UK has funded a wider variety of research, extending to projects with impacts outside its borders to some developing countries. Additionally, despite an increased incidence of mental illness and HIV/AIDs in China, there is evidence that less priority has been given to these conditions. Both of these health areas seem to require more attention from China’s national funding agencies and the society in general. Methodologically, this study can serve as an example of how to conduct analyses related to public health issues by combining informetric methods and data with data and tools from other fields, thereby inspiring other scientometrics studies.

For FULL-TEXT download at DOI: 10.31219/osf.io/ckpf8

Author(s): Lin Zhang, Wenjing ZHAO, Jianhua Liu, Gunnar Sivertsen, Ying HUANG
Organization(s): Wuhan University, KU Leuven, Beijing Wanfang Data Ltd., Nordic Institute for Studies in Innovation Research and Education (NIFU)
Source: SocArXiv
Year: 2020

Robotic Bureaucracy and Administrative Burden: What Are the Effects of Universities’ Computer Automated Research Grants Management Systems?

Our paper seeks to understand effects of computerized approaches to university research grants and contracts management, especially impacts on administrative burden. Ours is a multi-method paper, including interviews with academic researchers but focuses chiefly on participant-observer research, using hundreds of our own emails from two projects located at two different universities. We find that robotic emails have complex effects and that their utility pertains to researchers’ familiarity with the systems and compliance requirements, the clarity of administrative requests, the extent and location of staff support, and the interaction of personal work habits with system requirements. We provide suggestions for improving automated research administration.

https://doi.org/10.1016/j.respol.2020.103980

Author(s): Barry Bozeman, Jan Youtie, Jiwon Jung
Organization(s): Arizona State University, Georgia Institute of Technology
Source: Research Policy
Year: 2020

Study on Worldwide Development and Trends of Quantum Technologies Based on Patent Data (FULL-TEXT)

Quantum technologies attracted much attention for their disruptive potential in last two decades. The article analyzes the worldwide patent landscape for quantum technologies based on data extracted from Derwent Innovation and Web of Science. The quantum technologies were grouped
into three distinct technology areas of quantum computing, quantum communication and quantum sensing, to demonstrate detailed development and trends respectively. It shows that quantum technology is a highly competitive research field, and United States, China and Japan are the most prominent countries, in particular China made a great progress in recent years. United States has a significant advantage in the field of quantum computing, which is the most promising field, meanwhile China has a significant advantage in the field of quantum communication and succeeds in launching a quantum satellite.

FULL-TEXT http://www.ijiet.org/vol10/1370-CP2-026.pdf

Author(s): Juan Zhang, Qianfei Tian, Chuan Tang, Lina Wang, Jing Xu, and Junmin Fang
Organization(s): Chengdu Library and Information Center
Source: International Journal of Information and Education Technology
Year: 2020

Technological domain in the automotive sector: analysis of the relational structure of patents for electric vehicles (FULL-TEXT)

This work aims to analyse a relational structure of patents in automotive sector, especially for electric vehicles. The automotive industry is equivalent to 22% of Brazil’s industrial gross domestic product (GDP), 4% of Brazil’s total GDP, and worldwide it should reach a mark of 100 million vehicles sold by 2020. In recent decades, innovation processes have become a matter of survival for companies. Resource Based View admits that companies are looking for strategic resources that are a source of competitive advantage. This work comprises the automotive market as an organizational field in which the actors struggle to reach more favourable positions from the available resources. The network approach was used together with patent analysis to highlight the existing relationships within this industry in the construction of innovation, through the analysis of patents of high commercial value in the automotive sector, collected through the Derwent database.

For FULL-TEXT see http://leblog.gerpisa.org/node/4456

Author: Filippo Filippo Savoi de Assis
Organization: Universidade Federal de São Carlos – UFSCar
Source: Gerpisa Colloquium
Year: 2018

Patent Portfolio Model for Measuring Strategic Technological Strength

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

TECHNOLOGICAL INNOVATIONS OF THE 3D PRINTER APPLIED TO HEALTH (INOVAÇÕES TECNOLÓGICAS DA IMPRESSORA 3D APLICADA À SAÚDE) FULL-TEXT

3D printing technology has already been created by the manufacturing industry for decades. In the health area has grown rapidly, allowing the application to various areas of medicine. This work carried out a quantitative study in patent databases with the aim of sticking to the innovations that emerged with the 3D printer applied to health through technological indicators inherent in patents. It is possible to check the countries, companies and applications for the innovations that emerged after the patent for Fusion and Deposition Modeling (FDM) technology came into the public domain. China, listed as one of the countries in the Global Innovation Index, holds the development of new technologies as well as the patent protection of 3D Health Printer prototypes.

A tecnologia da impressão 3D tem sido utilizada pela indústria de manufatura há décadas. Na área da saúde tem crescido rapidamente, possibilitando a aplicação em diversas áreas da medicina. Este trabalho realizou um estudo quantitativo nas bases de dados de patentes com o objetivo de apontar as inovações surgidas com a impressora 3D aplicada à saúde por meio de indicadores tecnológicos inerentes nas patentes. É possível verificar os países, as empresas e as aplicações referentes às inovações que surgiram após a patente da tecnologia de Modelagem por Fusão e Deposição (FDM) entrar em domínio público. A China, listada como um dos países no Índice Global de Inovação, detém o desenvolvimento de novas tecnologias, bem como a proteção por patente de protótipos da Impressora 3D aplicado à saúde.

D.O.I.: 10.7198/geintec.v9i4.1413 Full-Text at link below

Technological Innovations of the 3D printer applied to health

Author(s): Lana Grasiela Alves Marques,  Rosângela Cordeiro de Souza Assef Neto,  Rosane Abdala Lins,  Maria Cristina Soares Guimarães

Organization(s): Fundação Oswaldo Cruz – FIOCRUZ

Source: GEINTEC

Year: 2019

Fine-grained Construction of Semantic Technology Network for Technology Evolution Analysis

As a basic tool for technology evolution analysis, technology network can visualize the relationship among technologies in different patents. However, the current constructions of technology network only represent common technical information, and cannot reflect different types of technical information. We propose a new approach to construct a fine-grained technology network and display technical information from multiple perspectives. Based on the Subject-Action-Object (SAO) structures extracted from patent documents, we first classify the technical information, and then investigate the semantic relationship among different types of technical information. Based on that, single-type and multi-type technology networks are constructed, which can demonstrate different types of technical information and make the technology evolution analysis easier and more reliable. Finally, taking the Nano-fertilizer patents as a data source, we construct a fine-grained construction of technology network, which might help identify fundamental and emerging technologies in the Nano-fertilizer field.

doi>10.1145/3331453.3361638

Author(s): Xiaoman Li, Hongyan Song, Xuefu Zhang, Qian Xu

Organization: Agricultural Information Institute, Chinese Academy of Agricultural Sciences

Source: Proceedings of the 3rd International Conference on Computer Science and Application Engineering

Year: 2019