Scientific collaboration, research funding, and novelty in scientific knowledge.
Ontology highlight
ABSTRACT:
SUBMITTER: Shin H
PROVIDER: S-EPMC9312390 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Background Limited knowledge and unclear underlying biology of many rare diseases pose significant challenges to patients, clinicians, and scientists. To address these challenges, there is an urgent need to inspire and encourage scientists to propose and pursue innovative research studies that aim to uncover the genetic and molecular causes of more rare diseases and ultimately to identify effective therapeutic solutions. A clear understanding of current research efforts, knowledge/research gaps, and funding patterns as scientific evidence is crucial to systematically accelerate the pace of research discovery in rare diseases, which is an overarching goal of this study. Methods To semantically represent NIH funding data for rare diseases and advance its use of effectively promoting rare disease research, we identified NIH funded projects for rare diseases by mapping GARD diseases to the project based on project titles; subsequently we presented and managed those identified projects in a knowledge graph using Neo4j software, hosted at NCATS, based on a pre-defined data model that captures semantics among the data. With this developed knowledge graph, we were able to perform several case studies to demonstrate scientific evidence generation for supporting rare disease research discovery. Results Of 5001 rare diseases belonging to 32 distinct disease categories, we identified 1294 diseases that are mapped to 45,647 distinct, NIH-funded projects obtained from the NIH ExPORTER by implementing semantic annotation of project titles. To capture semantic relationships presenting amongst mapped research funding data, we defined a data model comprised of seven primary classes and corresponding object and data properties. A Neo4j knowledge graph based on this predefined data model has been developed, and we performed multiple case studies over this knowledge graph to demonstrate its use in directing and promoting rare disease research. Conclusion We developed an integrative knowledge graph with rare disease funding data and demonstrated its use as a source from where we can effectively identify and generate scientific evidence to support rare disease research. With the success of this preliminary study, we plan to implement advanced computational approaches for analyzing more funding related data, e.g., project abstracts and PubMed article abstracts, and linking to other types of biomedical data to perform more sophisticated research gap analysis and identify opportunities for future research in rare diseases. Supplementary Information The online version contains supplementary material available at 10.1186/s13023-021-02120-9.
| S-EPMC8600882 | biostudies-literature
Project description:PurposeResearch collaborations can help to increase scientific productivity. The purpose of the present study was to draw up the knowledge flow network of the Endocrinology and Metabolism Research Institute (EMRI) affiliated to Tehran University of Medical Sciences.MethodsThe present study is a descriptive cross-sectional study on the publications of the EMRI. Web of Science Core collection databases were searched for the EMRI publications between 2002 to November 2019. Besides, publications were classified and visualized based on authorships (institutes and country of affiliation), and keywords (co-occurrence and trend). Scientometric methods including VOSviewer and HistCite were used for descriptive statistics and data analysis.ResultsTotal citations to the records were 47,528 and papers were published in 916 journals. The annual growth rate of publications and the citation was 14.2% and 18.9%, respectively. A total of 9466 authors from 136 countries collaborated in the publications. The co-authorship patterns showed that the average co-authorship and collaboration coefficient was 3.3 and 0.19.ConclusionKnowledge flow between EMRI researchers with international collaborations, engagement with leading countries, and interdisciplinary collaborations have an increasing trend. To develop a full picture of co-authorship, using social network analysis indicators are suggested for future studies.
| S-EPMC8212232 | biostudies-literature
Project description:In this paper, we estimate the impact of receiving an NIH grant on subsequent publications and citations. Our sample consists of all applications (unsuccessful as well as successful) to the NIH from 1980 to 2000 for standard research grants (R01s). Both OLS and IV estimates show that receipt of an NIH research grant (worth roughly $1.7 million) leads to only one additional publication over the next five years, which corresponds to a 7 percent increase. The limited impact of NIH grants is consistent with a model in which the market for research funding is competitive, so that the loss of an NIH grant simply causes researchers to shift to another source of funding.
| S-EPMC3156466 | biostudies-literature
Project description:Crowdfunding has gained traction as a mechanism to raise resources for entrepreneurial and artistic projects, yet there is little systematic evidence on the potential of crowdfunding for scientific research. We first briefly review prior research on crowdfunding and give an overview of dedicated platforms for crowdfunding research. We then analyze data from over 700 campaigns on the largest dedicated platform, Experiment.com. Our descriptive analysis provides insights regarding the creators seeking funding, the projects they are seeking funding for, and the campaigns themselves. We then examine how these characteristics relate to fundraising success. The findings highlight important differences between crowdfunding and traditional funding mechanisms for research, including high use by students and other junior investigators but also relatively small project size. Students and junior investigators are more likely to succeed than senior scientists, and women have higher success rates than men. Conventional signals of quality-including scientists' prior publications-have little relationship with funding success, suggesting that the crowd may apply different decision criteria than traditional funding agencies. Our results highlight significant opportunities for crowdfunding in the context of science while also pointing towards unique challenges. We relate our findings to research on the economics of science and on crowdfunding, and we discuss connections with other emerging mechanisms to involve the public in scientific research.
| S-EPMC6319731 | biostudies-literature
Project description:Tie strength has been examined as an antecedent of creativity. Although it has been discovered that international collaboration affects scientific performance, the effect of tie strength in the international collaboration network has been largely neglected. Based on international publications of 72 countries/regions published from 1993 to 2013, we combine descriptive and panel regression methods to examine how the bonding of strong collaboration ties contributes to countries’ international scientific performance. Strong ties occur at an average rate of 1 in 4 collaborators, whereas countries/regions share on average 84% of articles with their strong-tie collaborators. Our quantitative results provide an explanation for this phenomenon in international collaboration: the establishment of a strong tie relationship contributes to above-average productivity and citation frequency for countries/regions. To further explore which types of strong ties tend to have stronger citation impact, we analyse the relationship between persistent and stable collaboration and publication citation impact. Experimental results show that international collaborations with greater persistence and moderate stability tend to produce high impact publications. It is noteworthy that when the collaboration period is divided into different time intervals, similar findings can be found after the same analysis procedure is carried out. This indicates that our conclusions are robust. Overall, this study provides quantitative insights into the added value of long-term commitment and social trust associated with strong collaborative partnerships in international collaboration.
| S-EPMC9844855 | biostudies-literature
Project description:This article examines the relationship between Research & Development (R&D) funding and the production of knowledge by academic chemists. Using articles published, either raw counts or adjusted for quality, we find a strong, positive causal effect of funding on knowledge production. This effect is similar across subsets of universities, suggesting a relatively efficient allocation of R&D funds. Finally, we document a rapid acceleration in the rate at which chemical knowledge was produced in the late 1990s and early 2000s relative to the financial and human resources devoted to its production.
| S-EPMC4570780 | biostudies-literature
Project description:BackgroundEstablishment of the Canadian Institutes of Health Research (CIHR) in 2000 resulted in increased funding for health research in Canada. Since 2001, the number of proposals submitted to CIHR that, following peer review, are judged to be of scientific merit to warrant funding, has grown by 77%. But many of these proposals do not receive funding because of budget constraints. Given the role of Members of Parliament in setting government funding priorities, we surveyed Members of Parliament about their knowledge of and attitudes toward health research, health research funding and CIHR.MethodsAll Members of Parliament were invited to participate, or to designate a senior aide to participate, in a 15-minute survey of knowledge of and attitudes toward health research, health research funding and CIHR. Interviews were conducted between July 15, 2006, and Dec. 20, 2006. Responses were analyzed by party affiliation, region and years of service as a Member of Parliament.ResultsA total of 101 of 308 Members of Parliament or their designated senior aides participated in the survey. Almost one-third of respondents were senior aides. Most of the respondents (84%) were aware of CIHR, but 32% knew nothing about its role. Participants believed that health research is a critical component of a strong health care system and that it is underfunded. Overall, 78% felt that the percentage of total government spending directed to health research funding was too low; 85% felt the same way about the percentage of government health care spending directed to health research. Fifty-four percent believed that the federal government should provide both funding and guidelines for health research, and 66% believed that the business sector should be the primary source of health research funding. Participants (57%) most frequently defined health research as study into cures or treatments of disease, and 22% of participants were aware that CIHR is the main federal government funding organization for health research. Participants perceived health research to be a low priority for Canadian voters (mean ranking 3.8/10, with 1 being unimportant and 10 being extremely important [SD 1.85]).InterpretationOur results highlight significant knowledge gaps among Members of Parliament regarding health research. Many of these knowledge gaps will need to be addressed if health research is to become a priority.
| S-EPMC2025626 | biostudies-literature
Project description:BACKGROUND:Text mining (TM) methods have been used extensively to extract relations and events from the literature. In addition, TM techniques have been used to extract various types or dimensions of interpretative information, known as Meta-Knowledge (MK), from the context of relations and events, e.g. negation, speculation, certainty and knowledge type. However, most existing methods have focussed on the extraction of individual dimensions of MK, without investigating how they can be combined to obtain even richer contextual information. In this paper, we describe a novel, supervised method to extract new MK dimensions that encode Research Hypotheses (an author's intended knowledge gain) and New Knowledge (an author's findings). The method incorporates various features, including a combination of simple MK dimensions. METHODS:We identify previously explored dimensions and then use a random forest to combine these with linguistic features into a classification model. To facilitate evaluation of the model, we have enriched two existing corpora annotated with relations and events, i.e., a subset of the GENIA-MK corpus and the EU-ADR corpus, by adding attributes to encode whether each relation or event corresponds to Research Hypothesis or New Knowledge. In the GENIA-MK corpus, these new attributes complement simpler MK dimensions that had previously been annotated. RESULTS:We show that our approach is able to assign different types of MK dimensions to relations and events with a high degree of accuracy. Firstly, our method is able to improve upon the previously reported state of the art performance for an existing dimension, i.e., Knowledge Type. Secondly, we also demonstrate high F1-score in predicting the new dimensions of Research Hypothesis (GENIA: 0.914, EU-ADR 0.802) and New Knowledge (GENIA: 0.829, EU-ADR 0.836). CONCLUSION:We have presented a novel approach for predicting New Knowledge and Research Hypothesis, which combines simple MK dimensions to achieve high F1-scores. The extraction of such information is valuable for a number of practical TM applications.
| S-EPMC6019216 | biostudies-literature
Project description:ObjectiveTo quantify randomness and cost when choosing health and medical research projects for funding.DesignRetrospective analysis.SettingGrant review panels of the National Health and Medical Research Council of Australia.ParticipantsPanel members' scores for grant proposals submitted in 2009.Main outcome measuresThe proportion of grant proposals that were always, sometimes, and never funded after accounting for random variability arising from differences in panel members' scores, and the cost effectiveness of different size assessment panels.Results59% of 620 funded grants were sometimes not funded when random variability was taken into account. Only 9% (n = 255) of grant proposals were always funded, 61% (n = 1662) never funded, and 29% (n=788) sometimes funded. The extra cost per grant effectively funded from the most effective system was $A18,541 (£11,848; €13,482; $19,343).ConclusionsAllocating funding for scientific research in health and medicine is costly and somewhat random. There are many useful research questions to be addressed that could improve current processes.
| S-EPMC3181233 | biostudies-literature
Project description: Not available
| S-EPMC5822732 | biostudies-literature