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35 results for “Research Fund”
Research funding for male reproductive health and infertility in the UK and USA [2016 – 2019]
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Data from: Using risk of bias domains to identify opportunities for improvement in food- and nutrition-related research: an evaluation of research type and design, year of publication, and source of funding
Purpose: This retrospective cross-sectional study aimed to identify opportunities for improvement in food and nutrition research by examining risk of bias (ROB) domains. Methods: Rating were extracted from critical appraisal records for 5675 studies used in systematic reviews conducted by three organizations. Variables were as follows: ROB domains defined by the Cochrane Collaboration (Selection, Performance, Detection, Attrition, and Reporting), publication year, research type (intervention or observation) and specific design, funder, and overall quality rating (positive, neutral, or negative). Appraisal instrument questions were mapped to ROB domains. The kappa statistic was used to determine consistency when multiple ROB ratings were available. Binary logistic regression and multinomial logistic regression were used to predict overall quality and ROB domains. Findings: Studies represented a wide variety of research topics (clinical nutrition, food safety, dietary patterns, and dietary supplements) among 15 different research designs with a balance of intervention (49%) and observation (51%) types, published between 1930 and 2015 (64% between 2000-2009). Duplicate ratings (10%) were consistent (k=0.86-0.94). Selection and Performance domain criteria were least likely to be met (57.9% to 60.1%). Selection, Detection, and Performance ROB ratings predicted neutral or negative quality compared to positive quality (p<0.001). Funder, year, and research design were significant predictors of ROB. Some sources of funding predicted increased ROB (p<0.001) for Selection (Interventional: industry only and none/not reported; Observational: other only and none/not reported) and Reporting (Observational: university only and other only). Reduced ROB was predicted by combined and other-only funding for intervention research (p<0.005). Performance ROB domain ratings started significantly improving in 2000; others improved after 1990 (p<0.001). Research designs with higher ROB were nonrandomized intervention and time series designs compared to RCT and prospective cohort designs respectively (p<0.001). Conclusions: Opportunities for improvement in food and nutrition research are in the Selection, Performance, and Detection ROB domains.
Research software funding policies and programs: Results from an international survey (Dataset)
<p>Research software is increasingly recognized as critical infrastructure in contemporary science. Research software spans a broad spectrum, including source code files, algorithms, scripts, computational workflows, and executables, all created for or during research. Research funders have developed programs, initiatives and policies to bolster research software’s role. However, there has been no empirical study of how research funders prioritize support for research software. This information is needed to clarify where current funder support is concentrated and where strategic gaps may exist. Here, we present data from a survey of research software funders (n=36) from around the world. The survey explored these funders’ priorities, finding a strong emphasis on developing skills, software sustainability, embedding open science, building community and collaboration, advancing research software funding, increasing software visibility and use, innovation and security. </p> <h1>Methods</h1> <p>This research was carried out using a survey combining qualitative and quantitative items. The survey was designed to investigate how research software funders support research software’s sustainability and impact.</p> <p>The study was reviewed and given an exempt determination by the University of Illinois Urbana-Champaign Institutional Review Board (no. 24374).</p> <h2>Survey design</h2> <p>The survey designed for this study began by collecting profile information, including institutional affiliation and job title. The survey gathered information about respondents’ organization’s initiatives, policies, or programs to support research software. The range of questions yielded too much data for one article. In this article, we focus exclusively on the results generated via an open-ended question asking about the top priorities for the respondents’ organizations’ support for research software: “What are your organization's top priorities related to research software?”. Four open-response text boxes were provided for respondents to indicate and list these priorities.</p> <h2>Sampling</h2> <p>This survey was aimed at international research funders, including governmental and non-governmental (e.g., philanthropic) funders. A list of contacts to invite to participate in this survey was created based on participation in the Research Software Association (ReSA) and responsibility for research software funding known to the authors. This initial list of people was refined, with removals based on individuals having moved to unrelated professional roles or being unavailable long-term, for example, due to personal issues.</p> <p>The final, refined contact list comprised 71 people. After removing individuals when a member of their organization already provided a complete answer or when the person turned out to no longer be working on a relevant topic or to be otherwise unavailable (total of n=30), 41 people remained. Five of these individuals did not complete the survey, while 36 people (representing 30 research funding organizations) did, yielding a response rate of 87.8%. Fully completed survey responses were not required for individuals to be retained in the sample, resulting in varied sample bases across survey questions.</p> <p>The sample includes research funders in North and South America, Europe, Oceania and Asia, but over-represents North America and European funder representatives. Some participating funders cover a broad spectrum of disciplines, while others focus on a particular domain such as social science, health, environment, physical sciences or humanities.</p> <table> <tbody> <tr> <td> <p><strong>Continent</strong></p> </td> <td> <p><strong>Count</strong></p> </td> </tr> <tr> <td> <p>North America</p> </td> <td> <p>15</p> </td> </tr> <tr> <td> <p>South America</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>Europe</p> </td> <td> <p>12</p> </td> </tr> <tr> <td> <p>Oceania</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>Asia</p> </td> <td> <p>1</p> </td> </tr> </tbody> </table> <p>The respondents represented research funders supported by governmental (n=26), philanthropic (n=6) and corporate (n=1) resources.</p> <p>Respondents’ job titles span the following categories: <em>Senior Leadership and Executive</em>, such as a Vice President of Strategy; <em>Program and Project Management</em>, such as Senior Program Manager; <em>Planning and Business Development</em>; <em>Scientific, Technical and IT</em>, such as Scientific Information Lead.</p> <p>Most respondents 72.7% (n=24) answered ‘Yes’ to the question, “Has your organization established any policies, initiatives or programs aimed at supporting research software?”, while 18.2% (n=6) said ‘No’ and 9.1% (n=3) ‘Unsure’.</p> <h2>Data collection, management and analysis</h2> <p>Data collection took place from December 2023 to May 2024. The mean completion time for the detailed survey was 28 minutes and 13 seconds.</p> <p>The data were cleaned and prepared for analysis by removing any identifiable respondent details. The data analysis process followed a standard thematic qualitative analysis approach (e.g., Jensen & Laurie, 2016). This involved first identifying themes and organizing the data accordingly. Dimensions of each theme were identified where relevant. Then data extracts were selected from the survey responses associated with each theme and theme dimension. </p> <h1>Additional data: Evolving funding strategies for research software: Insights from an international survey of research funders</h1> <p>Data were uploaded in December 2024 to support another paper drawing on the same overall survey data. This one is entitled: 'Evolving funding strategies for research software: Insights from an international survey of research funders'. The survey data for this upload were generated using the following survey items.</p> <table> <tbody><tr> <td> <p><strong><span>Variable</span></strong></p> </td> <td> <p><strong><span>Survey Item</span></strong></p> </td> <td> <p><strong><span>Response Options</span></strong></p> </td> </tr> </tbody><tbody> <tr> <td> <p><span>Policies, initiatives, or programs aimed at supporting research software</span></p> </td> <td> <p><span>“Has your organization established any policies, initiatives or programs aimed at supporting research software?”<br>(This could include grants, fellowships, funding policies, conference funding, or other kinds of support aimed at bolstering the sustainability or impact of research software)</span></p> </td> <td> <p><span>Yes, No, Unsure</span></p> <p><span>(If ‘Yes’, then the next question was asked)</span></p> </td> </tr> <tr> <td> <p><span>Number of policies or programs to be reported</span></p> </td> <td> <p><span>“How many of your organization’s policies, initiatives or programs to support research software are you familiar with?”</span></p> </td> <td> <p><span>1, 2, 3, 4, 5+</span></p> </td> </tr> <tr> <td> <p><em><span>The following questions were asked for each policy, initiative, or program</span></em></p> </td> </tr> <tr> <td> <p><span>Name of policy or program</span></p> </td> <td> <p><span>“Please name the policy, initiative or program (starting with the one you are most familiar with):”</span></p> </td> <td> <p><span>[Text line]</span></p> </td> </tr> <tr> <td> <p><span>Status of policy or program</span></p> </td> <td> <p><span>“What is the status of this policy, initiative or program?”</span></p> </td> <td> <p><span>Completed/closed, In progress/open, Other (please specify)</span></p> </td> </tr> <tr> <td> <p><span>Link(s)/description</span></p> </td> <td> <p><span>“Please provide link(s) to the policy, initiative or program, upload or email to [the researcher’s contact details].”<br>“Link(s)/Description:”<br>(If there is no documentation available, please describe it here:)</span></p> </td> <td> <p><span>[Textarea], [File upload]</span></p> </td> </tr> <tr> <td> <p><span>Type of policy or program</span></p> </td> <td> <p><span>“Which of the following best describes the policy, initiative or program you named above?”</span></p> </td> <td> <p><a name="_Hlk180534652"></a><span>Funding program, Policy that affects funding decision-making or outcomes (funder side), Policy that affects funding applicants or recipients (applicant/awardee side), Other (please specify)</span></p> </td> </tr> <tr> <td> <p><em><span>If ‘Funding program’ was selected in the previous question, then the next question was asked</span></em></p> </td> </tr> <tr> <td> <p><span>Type of funding</span></p> </td> <td> <p><span>“Which of the following best describes the available funding?”</span></p> </td> <td> <p><span>Funding that <strong>includes</strong> research software, Dedicated funding <strong>only</strong> for research software, Other (please specify)</span></p> </td> </tr> <tr> <td> <p><em><span>For all categories of policy, initiative or program, the following questions were asked.</span></em></p> </td> </tr> <tr> <td> <p><span>Problem(s) addressed</span></p> </td> <td> <p><span>“Please summarize the problem(s) this policy, initiative or program is aiming to address from your organization’s perspective:”</span></p> </td> <td> <p><span>[Text Area]</span></p> </td> </tr> <tr> <td> <p><span>Perceived level of program success</span></p> </td> <td> <p><span>“What factors have contributed to its success or lack of success?”</span></p> </td> <td> <p><span>Very successful, Successful, Neutral, Unsuccessful, Very unsuccessful, Not applicable / No opinion</span></p> </td> </tr> </tbody> </table>
Project factors and conservation outcome data for SeaDoc Society-funded research projects
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Data from: Using risk of bias domains to identify opportunities for improvement in food- and nutrition-related research: an evaluation of research type and design, year of publication, and source of funding
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Supplementary material 1 from: Lymer G, Leliaert F, Mergen P, Pijls S (2023) Pre-Commercial Procurement framework and European funding sources for European Research Infrastructure Consortiums: Insights from the DiSSCo ERIC development. Research Ideas and Outcomes 9: e113294. https://doi.org/10.3897/rio.9.e113294
Glossary
Supplementary material 2 from: Lymer G, Leliaert F, Mergen P, Pijls S (2023) Pre-Commercial Procurement framework and European funding sources for European Research Infrastructure Consortiums: Insights from the DiSSCo ERIC development. Research Ideas and Outcomes 9: e113294. https://doi.org/10.3897/rio.9.e113294
ANNEXE 1: Additional and non-EU funding sources
Data from: Early Firm Engagement, Government Research Funding, and the Privatization of Public Knowledge
<p>This is a demo and partial dataset of a full dataset of paper- patent pair from chinese chemical scholars. The full dataset covers the published English papers and the paired patents by some of the scholars of the chemical and pharmaceutical field who received the Distinguished Young Scholars of the National Science Foundation of China (NSFC) during 2009–2018. Data related to the papers are obtained from the China National Knowledge Infrastructure (CNKI) and WoS; data related to the scholars are obtained from the NSFC website, the Ministry of Science and Technology of China (MSTC) website, and the scholars' home pages; and data related to the patents are obtained from the CNIPA website. The dataset also covers the data on the average number of patent infringement cases at the prefecture level from China Judgements Online (CJO) using crawlers and text mining techniques to reflect the degree of local intellectual property protection (IPR). Besides the paper information, the dataset also contains the corresponding scholars' funding information and the paired patents<a href="#_ftn1">[1]</a> information gathered through “patent–paper pairs.”</p> <p>This demo datasets covers about 1/15 samples of the full datast. The detail variable explanation will be found in the "label" and "Notes" column after every variable name in the DTA data file. As a series of related papers are published, we will gradually publish the full data set.</p> <p> </p> <p><a href="#_ftnref1">[1]</a> A small number of papers may be paired with multiple patents. We deal with the situation of multiple paired patents when constructing variables. See “Variable” section of original paper for detailed illustrations. </p>
Figure 1 from: Versieux LM, Dávila N, Delgado GC, de Sousa VF, de Moura EO, Filgueiras T, Alves MV, Carvalho E, Piotto D, Forzza RC, Calvente A, Jardim JG (2017) Integrative research identifies 71 new plant species records in the state of Rio Grande do Norte (Brazil) and enhances a small herbarium collection during a funding shortage. PhytoKeys 86: 43-74. https://doi.org/10.3897/phytokeys.86.13775
Figure 1 - Map of Rio Grande do Norte state and municipalities, phytogeographical domains (Atlantic Rainforest and Caatinga), conglomerates points and new botanical records.
French research projects funded on climate studies and forest research between 1997 and 2017
<p>Exhaustive list of 163 projects used to analyse how French research agencies funded climate studies in forest research. Each project is referenced by its acronym, full title, beginning/end year, disciplinary approaches, use of social or economic approaches, research main focuses, integration of mitigation issues, and website. One project may have two main focuses of the same class, although sometimes only one main focus could be determined, as the projects mentioned only one objective (e.g., “MACCLIF”) or explored a main focus that was too broad to be further refined into a subcategory (e.g., “INFORMED”)</p>
Funding and Research Output Data
<p>The following dataset includes the anonymized and aggregated data underlying the following publication:</p> <p>Heyard, R., Hottenrott, H. The value of research funding for knowledge creation and dissemination: A study of SNSF Research Grants. <em>Humanit Soc Sci Commun</em> <strong>8</strong>, 217 (2021). <a href="https://doi.org/10.1057/s41599-021-00891-x">https://doi.org/10.1057/s41599-021-00891-x</a> </p> <p>The dataset includes researcher-year observations, so each row of the CSV represents one research, identified by an anonymised identifier, <strong>for a given year</strong>. Included researchers applied for funding by the Swiss National Science Foundation (SNSF). The variables are described in the data dictionnairy (see file data_dic.csv). </p> <p><span>Inclusion criteria:</span></p> <ul> <li>All researchers who applied to SNSF funding instrument project funding or Sinergia as<br>main applicant (e.g. PI) or co-applicant11 (e.g. co-PI) are included.</li> <li>Our observation period started in the year 2005 and ends in 2019.</li> <li>Dynamic, Researcher-specific Observation Period: it starts with the year in which the SNSF observes the researcher for the first time as (co-)PI to PF or as a career funding grantholder (after the postdoctoral level); the year the independent research career starts. However, this study period has its lower bound in 2005. The period ends in 2019 for everyone, and some researchers are observed for a longer period than others.</li> </ul> <p><span>Data anonymisation considerations:</span></p> <p>To ensure pseudo-anonymization of the data we only provide applicants’ age as categorical variable.</p> <p><span>Provenance of the data:</span></p> <p>The dataset was build by combining data owned by the Swiss National Science Foundation (SNSF) on researcher who submitted a proposal and were either funded or not, with data from Dimensions (<a href="https://www.dimensions.ai/">dimensions.ai</a>), a commercial database on scientific publications, which was access via an API (for which service the SNSF paid). All request regarding the process of data retrieval have to be addressed to the SNSF (datateam@snf.ch); same goes for the analysis code. </p>
Strategic Research Program 17 (VUB Funding)
ClinicalTrials.gov study NCT03498872. IPD Sharing: NO. Countries: 1. Publications: 0.
Long COVID Cutaneous Signatures: An ARPA Funded Research Project
ClinicalTrials.gov study NCT07005947. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Dataset: The impact of UKRI funded research on policy
<p>Publications Dataset used in the study "The Impact of UKRI Research Councils Funded Research on Policy: An Explorative Analysis". The data were collected during the first week of March 2024. This file contains Web of Science proprietary data and access can only be granted upon explicit request and only for reproducibility purposes.</p> <p>See version 2 for openly available data obtained from Overton.</p>
Data Set of the Study "Fostering transdisciplinary research for sustainability in the global south: Pathways to impact for funding programmes "
<p>Supplementary survey data to the project "LIRA 2030 – Fostering Transdisciplinarity in Africa". The data set contains a survey that was conducted in three cohorts to find out about the transdisciplinarity competence and learning within projects funded by the Leading Integrated Research for Agenda 2030 in Africa (LIRA2030) programme of the International Science Council. The survey encompassed 13 rating questions and 9 open questions.</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
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OpenNeuro
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