Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
112
datasets available to search
ShareScore release 0.9.0
Dataset results
112 results for “careers”
Evaluation of the impact of interdisciplinarity on the careers of researchers
<p>This questionnaire, developed by CNRS’ Mission for Transversal and Interdisciplinary Initiatives, aims to assess the impact of involvement in the development of an interdisciplinary research project on the careers of researchers. It has been sent to a list of pre-identified CNRS staff. Answers, together with facts and figures from CNRS HR department have been analysed and discussed in a publication, which is under review. THe original questionnaire was in French. In order to give access to a wide audience, we have translated into English. Please feel free to contact us, if you are interested in the French version.</p>
Career Advancement Scheme (CAS) for College Teachers
<p><strong>State level Online Workshop</strong> on <strong>‘Career Advancement Scheme (CAS) for College Teachers’</strong> Organized by Internal Quality Assurance Cell (IQAC) of J. S. M. College, Alibag, Sponsored by University of Mumbai on Saturday <strong>31st July, 2021.</strong></p>
Career Enhancement Training Study (USAF)
ClinicalTrials.gov study NCT04067401. IPD Sharing: Not stated. Countries: 1. Publications: 6.
Long-term perceptions of freshwater anglers about abandoned, lost or discarded fishing gear during their fishing careers
Open the record for dataset details and reuse information.
Leaving academia: Insights from evolutionary biologists on their career transitions and job satisfaction
Open the record for dataset details and reuse information.
Data from: TRANSCENDS: a career development program for underrepresented in medicine scholars in academic neurology
Open the record for dataset details and reuse information.
Open Science and Career Pathways
<p><strong>Episode Summary:</strong></p> <p>In this episode we are discussing researcher career options and how open science can have career benefits. Our interview guest will be <a href="https://www.vitae.ac.uk/events/event-presenters/dr-janet-metcalfe">Dr Janet Metcalfe</a> who is the Head of Vitae, an organisation supporting researcher professional development. We will cover the challenges researchers face in modern academia, the surprising truth about changing career paths, and how Open Science can benefit research career progression. </p> <p><strong>Resources and Links:</strong></p> <ul> <li><a href="https://www.vitae.ac.uk/%20">Vitae</a></li> <li><a href="https://qz.com/547641/theres-an-awful-cost-to-getting-a-phd-that-no-one-talks-about/">Cost of Getting a PhD (Article)</a></li> </ul> <p><strong>Episode Quotes:</strong></p> <p>“People, when they are doing their PhD, they tend to measure their PhD in terms of the research results at the end of it, but actually the most important product of a PhD is the person.”</p>
Datasets on contributorship and bibliometric variables for the study 'Task specialization across research careers'
<p>Datasets used in the study 'Task specialization and its effects on research careers'.</p> <p><strong>Dataset 1 (plos_contribution_data_set.csv).</strong> Seed dataset containing contribution and bibliometric data on a set of publications assigned to the Medical and Life Sciences from PLOS journals.</p> <p><strong>Dataset 2 (pub_history.csv).</strong> Dataset of author-publication combinations for the complete publication history of 222,295 disambiguated authors and 6,236,239 distinct publications.</p> <p> </p> <p><strong>Summary of the paper</strong></p> <p>Research evaluation remains largely focused on individuals’ leadership and excellence, disregarding the collaborative nature of their work. We model a set of 70,694 publications and 347,136 distinct authors using Bayesian networks to predict scientists’ specific contributions on each of their publications. We predict the contributions of 222,925 authors in 6,236,239 publications, and apply an archetypal analysis to profile scientists by career stage. We divide scientific careers into four stages: junior, early-career, mid-career and late-career. Three scientific archetypes are found throughout the four career stages: 1) leader, 2) specialized, and 3) supporting. All three archetypes are encountered for the early- and mid-career stages, whereas for junior and late-career stages only two archetypes are found: specialized and supporting for junior scholars, and leader and supporting for late-career scholars. Scientists assigned to the leader and specialized archetypes tend to have longer careers than researchers who belong to the supporting archetype. There is consistent gender bias at all stages: the majority of male scientists belong to the leader archetype, while the larger proportion of women belong to the specialized archetype, especially for early and mid-career researchers. </p>
Data on universities offering undergraduate degrees that train students for soil science careers at universities in the USA and its territories
<p>Several soil science education studies over the last 15 years have focused on the number of students enrolled in soil science programs. However, no studies have quantitatively addressed the number of undergraduate soil science preparatory programs that exist in the United States, which means we do not have solid data concerning whether overall program numbers are declining, rising, or holding steady. This also means we do not have complete data on the same trends for total undergraduate soil science students in the United States. This study used the US Office of Personnel Management (OPM) Soil Science Series 0470 standards to determine if a bachelor's degree met soil science preparatory criteria. Lists of the approximately 3,500 regionally accredited colleges and universities were obtained from the regional accrediting agencies and the website of each of the colleges and universities was visited to determine if they had a degree program that met the OPM 0470 criteria. A total of 92 soil science preparatory degree programs were identified at 86 colleges and universities. These programs were primarily linked to 1) agriculture, 2) environmental science, and 3) soil and water science based on number of degree occurrences. This study creates a baseline for future studies that can investigate trends in soil science programs. It also provides insight into the institutions and degree programs that should be included in soil science education studies.</p>
Las asignaturas de los planes de estudio D y E de la carrera de Estomatología relacionadas con la Odontología Restauradora [The subjects of study plans D and E of the Dentistry career related to Restorative Dentistry]
<p>En la presente base de datos, exploraremos las asignaturas de los planes de estudio D y E de la carrera de Estomatología que están directamente relacionadas con la Odontología Restauradora y que tienen actividades que se desarrollan en la educación en el trabajo. Analizaremos en detalle los contenidos programáticos, las metodologías de enseñanza y los recursos utilizados en cada una de estas asignaturas, con el fin de comprender cómo contribuyen a la formación integral de los estudiantes y su preparación para enfrentar los desafíos de la práctica profesional.</p>
Research database - Regulations, Manuals and Technical Standards Professional Career Pharmaceutical Sciences and Biochemistry
<p><span>This database contains information on Regulations, Manuals and Technical Standards of the Professional Career of Pharmaceutical Sciences and Biochemistry. Inca Garcilaso de la Vega University. Lima Peru</span></p> <p><span> </span></p>
Engineering Careers of Graduates from a Unique Summer Bridge Program (G5)
<p>This is the data for first time freshman in Engineering departments at Jackson State University (de-identified), including the retention and graduation information, and whether they have attended the summer program (SEEP).</p>
Replication Package for "Early Career Developers' Perceptions of Code Understandability. A Study of Complexity Metrics"
<div> <div> <div> <div> <div> <h2>Authors</h2> <ul> <li>Matteo Esposito, University of Oulu, Finland</li> <li>Andrea Janes, <span>Free University of Bozen-Bolzano</span>, Italy</li> <li>Terhi Kilamo, University of Tampere, Finland</li> <li>Valentina Lenarduzzi, University of Oulu, Finland</li> </ul> <h2>Content Overview</h2> <p>This replication package contains the following materials:</p> <ul> <li><strong>Tables:</strong> Excel files that include all hypothesis testing data, including normality tests.</li> <li><strong>Data:</strong> RAW Questionarie datasett.</li> </ul> <h2>Contact Information</h2> <p>For any issues, questions, or further assistance, please do not hesitate to contact the authors of the paper. We are here to help!</p> </div> </div> </div> </div> </div>
HAND IN HAND: Empowering Teachers Across Europe to Deal with Social, Emotional and Diversity Related Career Challenges - International Dataset
<p><span>HAND IN HAND: Empowering teachers across Europe to deal with social, emotional and diversity related career challenges (HAND:ET) is a European (Erasmus K3) policy experimentation project that brings together 11 partners and 13 associated partners from seven countries (Austria, Croatia, Denmark, Germany, Portugal, Slovenia, and Sweden).</span></p> <p><span>The project focuses on teachers by supporting their development of social and emotional competencies as well as their diversity awareness (SEDA) to empower them for the complexity of everyday working life with increasingly diverse classrooms and enable them to deal flexibly with new challenges. It also puts the teachers' well-being at the centre by highlighting how developing SEDA competencies simultaneously fosters self-care for teachers, giving a central role to the voices of teachers.</span></p> <p><span>Information on the project can be accessed at: <a href="https://www.handinhand.si/en/" target="_blank" rel="noopener">https://www.handinhand.si/en/</a></span></p> <p><span>Further information on the project and the evaluation results can be found in the following publication: Kozina, A. (2024). Empowering Teachers Across Europe to Deal with Social, Emotional and Diversity Related Challenges, Volume 1: Experimentation Perspectives. Waxman.</span></p> <p><span>Information on the instruments used in the evaluation is provided in the attached document "HAND_ET_Scale_Documentation.pdf".</span></p> <p><span>Design: All countries implementing the experiment (Austria, Croatia, Portugal, Slovenia and Sweden) invited schools to participate. The schools participating in the experiment were randomly allocated to either the experimental or the control group. Central to the experiment’s design, schools had to agree to their participation in either condition (experimental or control). The intention was to test the effectiveness of the HAND:ET system in promoting SEDA competencies: to compare the changes in the same competencies from before implementing the HAND:ET system (pre-test) to after implementing the system (post-test) in a group of teachers (and other school staff) who took part in the experiment (experimental group) with a group of teachers (and other school staff) who did not participate (the control group). </span></p> <p><span> </span><span>Data collection period: T1 (pre-test) data was collected August to September 2022, T2 (post-test) data was collected Mai to July 2023.</span></p> <p><span> </span><span>Sample: The HAND_ET datafile includes primary and/or secondary teachers from Austria, Croatia, Portugal, Slovenia, and Sweden, who responded to the questionnaire either at first time point or second time point or both. In Austria, teachers teaching students in grades 1 to 4, in Croatia those teaching students in grades 1 to 8, in Portugal those teaching students in grades 1 to 12, in Slovenia those teaching students in grades 1 to 9, while in Sweden teachers teaching students in grades 4 to 9 participated.</span></p> <p><span> </span><span>The HAND_ET datafile is structured as follows: </span></p> <p><span>·</span><span> </span><span>Variables from 'IDS' to 'Gender' include general information about the participant (e.g group, participation in pre- or post-test, gender)</span></p> <p><span>·</span><span> </span><span>Variables from 'TC06exp' to 'TCN22_TCN2204' capture responses from questionnaire items administered during the pre-test.</span></p> <p><span>·</span><span> </span><span>Variables from 'TC02_2' to 'TCN30_TCN30Q04_TCN30G03_2' contain responses to questionnaire items used in the post-test data collection.</span></p> <p><span>·</span><span> </span><span>Variables from 'observe' to 'coopteach' include scale scores for the scales administered in pre-test.</span></p> <p><span>·</span><span> </span><span>Variables from 'observe_2' to 'coopteach_2' include scale scores for the scales administered in post-test.</span></p> <p><span>·</span><span> </span><span>Variables from 'observe_D' to 'CloseC_D' include scale scores calculated as differences between measurements at Time 1 (T1) and Time 2 (T2) for all questionnaire scales.</span></p> <p><span>·</span><span> </span><span>Variables from 'observe_D.1' to 'CloseS_D.5' contain scale score differences (T1-T2) with missing values imputed. As we did 5 imputations, there are five variables for each scale (as indicated at the end of the variable name).</span></p> <p><span> </span><span>The scale score for each participant at each point in time was computed as the arithmetic mean of responses to the items of a scale measuring a SEDA construct. A scale value was only computed if responses for at least half of the items of a scale were available. No overall scale score was computed for multidimensional constructs. Subscales were treated as separate scales in the analysis. The difference score was computed as the T2 minus T1 scale score. A positive value corresponds to an increase of the scale score and a negative value indicates a decrease in the scale score of T2 compared to T1.</span></p> <p><span> </span><span>The dataset includes variables with imputed scale scores. We only imputed the difference score for each of the outcome variables five times. The imputation was carried out separately for each of the scales based on the three variables: group, T1, and T2 scale score. We used predictive mean matching with the R package mice (Buuren & Groothuis-Oudshoorn, 2011) for imputation. The teachers that have a missing in the group variable have no imputed values.</span></p>
Figure 1 in In Memoriam From Cotton Farming to the Congressional Gold Medal: The Career and Legacy of Ernest James Harris (1928-2018)
Figure 1: A–B: Ernie Harris ca. 1929 and in the early 1950s. C: Ernie and Betty Jo Harris and children Mark and Tanya arriving at the Honolulu Airport in February 1962. D: Early prototype of the Jackson trap, scanned from Ernie's private slide collection, photo dated June 1968. E: Last meeting between Ernie and the authors in March 2017.
Ciência Vitae controlled vocabulary - Career path
Open the record for dataset details and reuse information.
Database: Exploring the perception of barriers to a dual career by student-athletes with/out disabilities
<p>Database of the paper "Exploring the perception of barriers to a dual career by student-athletes with/out disabilities"</p>
Supplementary File: followed by Predicting Religious Undergraduates' Career Development: The Salient Roles of Religious Calling, Life Satisfaction, and Quest Religiosity
<p>Supplementary File: followed by Predicting Religious Undergraduates’ Career Development: The Salient Roles of Religious Calling, Life Satisfaction, and Quest Religiosity</p>
"Reading" people to learn about new science careers: the Human Library method
<p>The "human library" method is frequently used to establish open conversations with people one would not meet in their daily routine, and this is what makes it so interesting in the context of science education. The MULTIPLIERS project is exploring the method to promote meaningful interactions between students and stakeholders involved in socio-scientific issues, while also eliciting interest in future career paths in science.</p> <p>Take a look at the expert interviews recorded by our students during the MULTIPLIERS awareness-raising campaign on Antimicrobial Resistance in Nicosia, Cyprus!</p> <p>More about the project: https://multipliers-project.org/</p>
Dataset for the Paper "Indigenous populations in STEM careers: A systematic Review of programs and studies"
<p><strong>Resouces for the Systematic Literature Review (SLR) carries out as part of PhD thesis about </strong><strong>Indigenous populations in STEM careers.</strong></p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
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.