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79 results for “Research, Training”
Multi-stakeholder research data management training as a tool to improve the quality, integrity, reliability and reproducibility of research: Quantitative data of the post-course surveys
<p>Data contains doctoral students' and postdoc researchers' (n=168) self-ratings of their RDM competencies before and after the 3 ECTS credits "Basics of Research Data Management" (BRDM) trainings held 2019-2021 in the University of Turku and Åbo Akademi University, Finland. Moreover, data contains respondents' self-reported further learning needs.</p>
Pirate Illustrations for Research Data Management Training
<p>This collection of icons and comics was created to illustrate a workshop on Data Management Plans (<a href="https://doi.org/10.5281/zenodo.5575920">https://doi.org/10.5281/zenodo.5575920</a>). It is provided here to allow further reuse, for example to illustrate presentations.</p> <p>The theme of this collection is revolving around pirates, their accessories, and maritime items in general.</p> <p>Created by Jeanne Wilbrandt.</p>
Doctoral Studies as part of an Innovative Training Network (ITN): Early Stage Researcher (ESR) experiences - supplemental material & data
<p>Table and data repository for the manuscript "Doctoral Studies as part of an Innovative Training Network (ITN): Early Stage Researcher (ESR) experiences"</p> <p><strong>Supplemental Tables:</strong></p> <ul> <li>table1_ESIT Project Table</li> <li>table2_TIN-ACT Project Table</li> <li>table3_ITN_tinnitus</li> <li>table4_ITN_other</li> <li>table5_Individual PhDs</li> </ul> <p><strong>Individual-level and de-identified survey data (raw data):</strong></p> <ul> <li>raw_data_ITN_tinnitus (survey results from PhDs as part of an ITN with a focus on tinnitus)</li> <li>raw_data_ITN_other (survey results from PhDs associated to ITNs with another focus)</li> <li>raw_data_Individual_Phds (survey results from PhDs not part of an ITN)</li> </ul>
H2M survey data on commercialisation training needs of Health Researchers
<p>Health-2-Market was a 3-year long Coordination and Support Action, funded by the European Union’s Seventh Framework Programme for research, technological development and demonstration (Grant Agreement No 305532). H2M aimed at providing training and individual support to Health / Life Sciences researchers in the process of translating their research results into successful new business ideas.</p> <p>With a view to properly adapting the training offer of the project to the needs of Health / Life Sciences researchers in terms of entrepreneurship and business skill development a Training Needs Analysis (TNA) was conducted. In this context, H2M launched an online survey targeted at Health / Life Sciences researchers who have been involved in EU health projects. In particular, the objectives of the survey were:</p> <ul> <li>To formulate a descriptive understanding of various aspects of commercialisation and training needs of the main target group of the project;</li> <li>To divide this target group into homogeneous sub-groups (clusters) along a number of key characteristics such as demographics, commercialisation attitudes and needs;</li> <li>To understand preferences and importance of different aspects and needs through the analysis of: <ul> <li>Knowledge areas that can influence commercialisation behaviour;</li> <li>Training modalities that have an effect on the intention to participate and /or on the perception of the usefulness of a commercialisation training;</li> <li>Variations identified over different sub-groups.</li> </ul> </li> </ul> <p>The survey was dispatched to a database composed of 7,991 unique contacts of participants in previous health projects, accessed through the Directorate General for Health and Food Safety of the European Commission. The initial aim of at least 50 complete responses was overwhelmingly surpassed: 637 respondents completed the survey in full.</p> <p>The “H2M survey data on commercialisation training needs of Health Researchers” dataset contains the raw, anonymised data that were collected from these respondents, along with the questionnaire items that were utilised.</p>
Data from Finnish Research Data Management Training Survey 2020-2021
<p>This is the survey data used in The Finnish Research Data Management Training Survey 2020-2021. The survey was sent to 74 Finnish research organizations of which 36 responded. The aim of the report was to gain a deeper understanding of what kind of research data management (RDM) training activities are provided by different Finnish organizations.</p> <p> </p>
Gregory-MS: list of research papers relevant/not relevant for Multiple Sclerosis research (for machine learning training)
<p>This dataset represents the list of research papers' data that was used to train and test different machine learning algorithms in the Gregory-MS project. The list includes the title and abstract (when available) of the research papers and an annotated field (relevant) that specifies if the given research paper is relevant or not for multiple sclerosis research.</p>
Training dataset from the Da Vinci Research Kit
<p>The use of data sets are getting more relevance in surgical robotics since they can be used to recognise and automate tasks in the lab. Also, it allows to use a common data set to compare different algorithms and methods. The objective of this work is to provide a complete data set of several training tasks that surgeons perform to improve their skills. For this purpose, the Da Vinci research kit has been used to perform a different training tasks. The obtained data set includes all the information provided by the da Vinci robot together with the corresponding video from the camera. Kinematic data has been collected at 50 frames per seconds, and images at 15 frames per seconds. All the information has been carefully timestamped and provided in a readable csv format. The application used to retrieve the information from the da Vinci research kit, as well as tools to access the information are also provided. </p>
Data from: Postdoctoral T32 training is correlated with obtaining an academic primarily research faculty position
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Proceeding of The International Research Education & Training Center
<p>AGRICULTURAL, ENVIRONMENTAL & NATURAL SCIENCES</p> <p>SOCIAL, PEDAGOGY SCIENCES & HUMANITIES</p> <p>MEDICINE AND BIOLOGY SCIENCES</p> <p>REGIONAL DEVELOPMENT AND INFRASTRUCTURE</p> <p>ECONOMIC, MANAGEMENT & MARKETING SCIENCES</p> <p>LEGAL, LEGISLATION AND POLITICAL SCIENCES</p>
Proceeding of The International Research Education & Training Center
<p>AGRICULTURAL, ENVIRONMENTAL & NATURAL SCIENCES</p> <p>SOCIAL, PEDAGOGY SCIENCES & HUMANITIES</p> <p>MEDICINE AND BIOLOGY SCIENCES</p> <p>REGIONAL DEVELOPMENT AND INFRASTRUCTURE</p> <p>ECONOMIC, MANAGEMENT & MARKETING SCIENCES</p> <p>LEGAL, LEGISLATION AND POLITICAL SCIENCES</p>
Research data on pass-by sound emission measurements from train units for D7.4-Susteren pilot
<p>This dataset compiles sample measurement results for the N-RSD rail pilot from D7.4-Susteren pilot project report available once approved by the EC at https://cordis.europa.eu/project/id/860441/results. The data includes train unit subtypes, pass-by sound levels, speed, weight, wheel flat indication, brake type information and a sound emission rating. </p>
Terms4FAIRskills - an overview for the Research Data Alliance 'Birds of a Feather' session, Skills and training curriculums to support FAIR for Research Software
<p>Short talk (7m) on the terms4FAIRskills initiative for the Research Data Alliance 'Birds of a Feather' session, Skills and training curriculums to support FAIR for Research Software, at RDA plenary 18 on 3 Nov 2021.</p> <p>Please see https://www.rd-alliance.org/skills-and-training-curriculums-support-fair-research-software for more information on the BoF session. Please see https://terms4fairskills.github.io/ for more information on the terms4FAIRskills initiative.</p>
PROCEEDING OF THE INTERNATIONAL RESEARCH EDUCATION & TRAINING CENTRE (PIRETC)
<p>AGRICULTURAL, ENVIRONMENTAL & NATURAL SCIENCES</p> <p>SOCIAL, PEDAGOGY SCIENCES & HUMANITIES</p> <p>MEDICAL SCIENCE</p> <p>ECONOMIC, MANAGEMENT & MARKETING SCIENCES</p> <p>LEGAL, LEGISLATION AND POLITICAL SCIENCES</p>
Proceeding of The International Research Education & Training Centre.
<p>AGRICULTURAL, ENVIRONMENTAL & NATURAL SCIENCES</p> <p>SOCIAL, PEDAGOGY SCIENCES & HUMANITIES</p> <p>MEDICINE, VETERINARY MEDICINE, PHARMACY AND BIOLOGY SCIENCES</p> <p>TECHNICAL AND APPLIED SCIENCES</p> <p>REGIONAL DEVELOPMENT AND INFRASTRUCTURE</p> <p>ECONOMIC, MANAGEMENT & MARKETING SCIENCES</p> <p>LEGAL, LEGISLATION AND POLITICAL SCIENCES</p>
Proceeding of The International Research Education & Training Centre
<p>AGRICULTURAL, ENVIRONMENTAL & NATURAL SCIENCES</p> <p>SOCIAL, PEDAGOGY SCIENCES & HUMANITIES</p> <p>MEDICINE AND BIOLOGY SCIENCES</p> <p>REGIONAL DEVELOPMENT AND INFRASTRUCTURE</p> <p>ECONOMIC, MANAGEMENT & MARKETING SCIENCES</p> <p>LEGAL, LEGISLATION AND POLITICAL SCIENCES</p>
Proceeding of The International Research Education & Training Centre.
<p>AGRICULTURAL, ENVIRONMENTAL & NATURAL SCIENCES</p> <p>SOCIAL, PEDAGOGY SCIENCES & HUMANITIES</p> <p>MEDICINE, VETERINARY MEDICINE, PHARMACY AND BIOLOGY SCIENCES</p> <p>TECHNICAL AND APPLIED SCIENCES</p> <p>REGIONAL DEVELOPMENT AND INFRASTRUCTURE</p> <p>ECONOMIC, MANAGEMENT & MARKETING SCIENCES</p> <p>LEGAL, LEGISLATION AND POLITICAL SCIENCES</p>
l-sized Training and Evaluation Data for Publication "Using Supervised Learning to Classify Metadata of Research Data by Field of Study"
<p>Automated classification of metadata of research data by their discipline(s) of research can be used in scientometric research, by repository service providers, and in the context of research data aggregation services. Openly available metadata of the DataCite index for research data were used to compile a large training and evaluation set comprised of 609,524 records. This is the cleaned and vectorized version with a feature selection of large size.</p>
s-sized Training and Evaluation Data for Publication "Using Supervised Learning to Classify Metadata of Research Data by Field of Study"
<p>Automated classification of metadata of research data by their discipline(s) of research can be used in scientometric research, by repository service providers, and in the context of research data aggregation services. Openly available metadata of the DataCite index for research data were used to compile a large training and evaluation set comprised of 609,524 records. This is the cleaned and vectorized version with a feature selection of small size.</p>
Pediatric standardized residency training faculty's perceptions of medical education research
<p><strong>Background:</strong> Rigorous medical education research (MER) conducted by faculty in pediatric standardized residency training (SRT) can contribute to the promotion of child health care. </p> <p><strong>Aim:</strong> This study aimed to assess the perceptions of pediatric SRT faculty regarding MER in Guangdong Province, China. </p> <p><strong>Methods:</strong> A questionnaire survey was conducted involving 40 pediatric SRT clinical teachers from 10 hospitals in Guangdong Province.</p> <p><strong>Results:</strong> Among the 40 teachers, 16 (40.00%) stated that they did not participate any MER activities. The main challenges they encountered in conducting MER were the lack of training (72.50%), limited time (80.00%), and lack of grants funding (60.00%). Only 10 (25.00%)teachers were reported to have received grants for MER projects. </p> <p><strong>Conclusion: </strong>The findings highlight the importance of providing support and training to pediatric SRT faculty in Guangdong Province, China, to enhance their engagement in MER. Addressing these challenges can lead to significant improvements in child heal care promotion through evidence-based educational practices. </p>
Pediatric standardized residency training faculty’s perceptions of medical education research
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.