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.
2,084
datasets available to search
ShareScore release 0.7.1
Dataset results
2,084 results for “Courses”
Database of the assessment of two instructional design variables in verbal reasoning and mathematical reasoning courses from the perspective of a Peruvian pre-university center students
<p>These are the data obtained from 4 evaluations made to a sample of 630 students of a Peruvian pre-university center. First, two study variables were evaluated: teaching sequence compliance and the student's educational need according to the perspective of 315 students of the verbal reasoning course. Second, the same study variables were assessed in the remaining 315 students of the mathematical reasoning course. This information is being used in research to obtain an academic degree and later to make a publication of a scientific article.</p> <p>For the treatment of these data, inferential statistics was used through the software R version 3.4.4 (2018) The R Foundation for Statistical Computing.</p>
Samasgarh समस्गढ़ (Huzur tehsil, District Bhopal, Madhya Pradesh). Temple exterior in course of reconstruction.
<p>Samasgarh समस्गढ़ (Huzur tehsil, District Bhopal, Madhya Pradesh). Temple exterior in course of reconstruction, showing the Paramāra-period mouldings, early modern temple, and contemporary encasement in course of work in 11/2007.</p>
Fig. 7 in The changing course of the Amazon River in the Neogene: center stage for Neotropical diversification
Fig. 7. Growth of mega-wetlands in northern South America. Geological time scale at top. Eustatic sea-level estimates from Zachos et al. (2001). Area estimates of for Atlantic and Caribbean draining mega-wetlands from paleogeographic reconstructions in Wesselingh, Hoorn (2010) and Hoorn et al. (2017), and for the Orinoco basin by Jaramillo et al. (2017). Caribbeandraining Andean foreland basins in orange; Atlantic-draining basins contributing to transcontinental Amazon in yellow. Areas estimated using ImageJ (Abràmoff et al., 2004). Curves smoothed using a third-order Bezier Spline.
Data for "Incidence, clinical course and risk factor for recurrent PCR positivity in discharged COVID-19 patients in Guangzhou, China: a prospective cohort study"
<p>Data for "Incidence, clinical course and risk factor for recurrent PCR positivity in discharged COVID-19 patients in Guangzhou, China: a prospective cohort study"</p>
[RDF Triples] Courses given at the Vrije Universiteit Amsterdam 2020/2021
<p>This data set is published in Turtle format using triples. </p> <p>The dataset contains all the Courses and their information at the Vrije Universiteit Amsterdam for the university year 2020/2021. This information was gathered from the Vrije Universiteit Amsterdam online study guide </p> <p>A new vocabulary 'vu' was needed as some vocabularies did not allow full expression of the datas et.</p> <p>You can use SPARQL in order to fetch data from this dataset, the property variables one can user are:</p> <ul> <li>vu:offeredByFaculty <ul> <li>This property will return the faculty the course belongs to as a vu:<strong>FacultyName</strong>.</li> </ul> </li> <li>vu:taughtBy <ul> <li>This property will return the professors who teach that course as a vu:<strong>ProfessorName</strong>.</li> </ul> </li> <li>vu:courseContent <ul> <li>This property returns what a course is about as a string. </li> </ul> </li> <li>vu:courseLevel <ul> <li>This property returns the course level (between 100 and 600) as an integer.</li> </ul> </li> <li>vu:courseObjective <ul> <li>This property returns the objective of a course as a string.</li> </ul> </li> <li>vu:literature <ul> <li>This property returns the required literature of a course as a string.</li> </ul> </li> <li>vu:recommendedBackground <ul> <li>This poperty returns the recommended background of a course as a string.</li> </ul> </li> <li>vu:targetAudience <ul> <li>This property returns the target audience of a course as a string.</li> </ul> </li> <li>vu:teachingMethods <ul> <li>This property returns the teaching methods of a course as a string. </li> </ul> </li> </ul> <p>These are the by us created property variables. There are also some re-used variables which are:</p> <ul> <li>vuc:<strong>CourseID</strong> rdf:type teach:Course <ul> <li>This returns all courses when used in sparql.</li> </ul> </li> <li>dbo:language <ul> <li>This property returns the language in which a course is given as a dbr:<strong>LanguageName</strong></li> </ul> </li> <li>teach:academicTerm <ul> <li>This property is used in order to return the academic term in which a course is given as a string.</li> </ul> </li> <li>teach:courseTitle <ul> <li>This property returns the name of a course as a string.</li> </ul> </li> <li>teach:ects <ul> <li>This property returns the number of European credits one receives for a course as an integer.</li> </ul> </li> <li>teach:grading <ul> <li>This property returns the grading method of a course as a string. </li> </ul> </li> </ul> <p>This data set can be used in order to find specific information about courses without knowing the exact course name or code. For example, you can fetch all courses that have 3 credits and are in English, given at the faculty of Science. Therefore it becomes much easier for students that want to follow courses outside of their major/master, which also fit their requirements. In a normal situation, a student would need to search through all 2064 courses given at the VU to find a course that they like. </p>
Data and material for the manuscript "Mutation testing and self/peer assessment: analyzing their effect on students in a software testing course"
<p><strong>This repository is composed of two different parts: </strong></p> <ul> <li><a href="https://zenodo.org/record/4464300/files/Assessment%20data%20and%20Mutation%20Scores.xlsx?download=1">Assessment data and Mutation Scores</a> file contains the student-generated data used in the experience.</li> <li><a href="https://zenodo.org/record/4464300/files/experience-material.zip?download=1">Experience-material</a> file contains the files to be able to reproduce the experience.</li> </ul> <p> </p> <p><strong>The </strong><strong> <a href="https://zenodo.org/record/4464300/files/experience-material.zip?download=1">Experience-material</a> file for the lab is used in two sessions:</strong></p> <p>Session 1: Development and assessment of test suites</p> <p>In this session, the student has to develop a test suite for a program under test. At the end of the session, the test suite will be evaluated against a set of assessment criteria regarding the quality of the developed test suite.</p> <p>Files for this session:</p> <ul> <li>VVS-Lab6-S1 pdf file , with the description of this session.</li> <li>Material-S1 zip file, with the files required to complete this session.</li> </ul> <p>Session 2: Evaluation applying mutation testing with MuCPP</p> <p>In this session, the test cases designed in the first part of this lab will be evaluated based on the mutation adequacy criterion. This will be done by using the <a href="https://ucase.uca.es/mucpp/">MuCPP mutation tool</a>.</p> <p>Files for this session:</p> <ul> <li>VVS-Lab6-S2 pdf file, with the description of this session.</li> <li>Material-S2 zip file, with the files required to complete this session.</li> </ul> <p><em>The source code files family.[cpp|hpp] have been adapted from a listing in [1]. Note that, while considered to be fault free in this lab, these source files are used in other sessions where students are expected to detect some defects in them.</em></p> <p>[1] S. Wiener and L. J. Pinson, The C++ Workbook. USA: Addison-Wesley Longman Publishing Co., Inc., 1990.</p>
Data files for INS data analysis course at github.com/pace-neutrons/edatc
<p>Large data files for use in the inelastic neutron training course hosted at https://github.com/pace-neutrons/edatc</p> <p>Included are:</p> <ul> <li>UPd3 measured on MERLIN (M. D. Le et al., 2008)</li> <li>bcc-Iron measured on MAPS (T. G. Perring et al., 2010)</li> <li>CuGeO3 measured on MERLIN (H. C. Walker et al., 2014)</li> </ul>
Epidemiology, risk factors and clinical course of SARS-CoV-2 infected patients in a Swiss university hospital: an observational retrospective study
<p>This is the dataset of the study called "Epidemiology, risk factors and clinical course of SARS-CoV-2 infected patients in a Swiss university hospital: an observational retrospective study". <br> <br> <strong>Abstract: </strong></p> <p>Background<br> Coronavirus disease 2019 (COVID-19) is now a global pandemic with Europe and the USA at its epicenter. Little is known about risk factors for progression to severe disease in Europe. This study aims to describe the epidemiology of COVID-19 patients in a Swiss university hospital.</p> <p>Methods<br> This retrospective observational study included all adult patients hospitalized with a laboratory confirmed SARS-CoV-2 infection from March 1 to March 25, 2020. We extracted data from electronic health records. The primary outcome was the need to mechanical ventilation at day 14. We used multivariate logistic regression to identify risk factors for mechanical ventilation. Follow-up was of at least 14 days. <br> <br> Results<br> 200 patients were included, of whom 37 (18·5%) needed mechanical ventilation at 14 days. The median time from symptoms onset to mechanical ventilation was 9·5 days (IQR 7.00, 12.75). Multivariable regression showed increased odds of mechanical ventilation in males (3.26, 1.21-9.8; p=0.025), in patients who presented with a qSOFA score ≥2 (6.02, 2.09-18.82; p=0.001), with bilateral infiltrate (5.75, 1.91-21.06; p=0.004) or with a CRP of 40 mg/l or greater (4.73, 1.51-18.58; p=0.013). <br> <br> Conclusions<br> This study gives some insight in the epidemiology and clinical course of patients admitted in a European tertiary hospital with SARS-CoV-2 infection. Male sex, high qSOFA score, CRP of 40 mg/l or greater and a bilateral radiological infiltrate could help clinicians identify patients at high risk for mechanical ventilation.</p>
Dataset for "Communication with family and friends across the life course"
<p>This is the dataset for "Communication with family and friends across the life course", to be published in PLOS One.</p> <p>The file contains data corresponding to egocentric networks of 3340868 individuals, derived from anonymized call detail records for a 7 months period in the year 2007 from a mobile phone service provider in a European country. Each line in the file corresponds to a different ego-alter pair and provides aggregated voice calling information for the concerned month.</p> <p>Details in README file.</p> <p> </p>
facebook-activity in a Mooc Course
<p>agentxknowledge: Dataset which gathers the information about the interaction performed by learners to certain topics published in facebook as social activity of a Mooc course. It consists on three columns: learner, topic and times that learner participated.</p> <p>agentxagent: Dataset which gathers the information about the interaction performed among learners who participated in a Mooc course. It consists on three columns: learner, learner and times that the first learner answered to the second learner.</p>
Presence and proportion of plants in biodiversity inventories conducted by undergraduate students enrolled in animal-related courses
<p>Dataset on biodiversity inventories conducted by 110 undergraduate students enrolled in animal-related courses using the iNaturalist platform.</p>
Getting the Most Out of Every Training Day – A Diary Study on the Influence of Instructors on Self-Regulated Learning During Firefighter Leadership Courses
<p>This is the online supplement for a diary study on self-regulated learning in firefighter leadership courses and how it is susceptible to instructor behavior.</p> <p><em>Abstract: </em>Leadership courses in the fire services are highly challenging, up to the point that they can seriously exhaust the trainees and hamper their self-regulated learning efforts (e.g., setting goals, focusing attention, seeking feedback). We theorize that experiences of failure or overload can curtail trainees’ available energy resources on subsequent training days, which in turn should affect trainees’ learning efforts. Given the central role of instructors in leadership courses, we hypothesize that supportive and humble instructor behaviors decrease experiences of failure and overload, and thus increase self-regulated learning. Moreover, we argue that supportive instructor behavior fosters the learning-promoting effect of high levels of energy resources among trainees, while humble instructor behavior mitigates hampering effects of low levels of resources. We conducted a preregistered diary study with 118 firefighters who participated in two-week leadership courses at a German fire academy. The participants completed short questionnaires before and after classes each day. Multilevel analyses confirmed that perceived daily supportive and humble instructor behavior predict trainees’ reports of daily self-regulated learning activity. Notably, this effect was independent of positive effects of trainees’ reported resources in the morning. However, supportive and humble behavior did not moderate the effect of energy resources. Our results suggest that instructors can elicit effective learning despite challenging training conditions. Furthermore, this study offers implications for leaders in the fire services who themselves often conduct trainings with their subordinates.</p> <p>The study was approved by the ethics committee of the Faculty of Psychology & Sports Science of [institution anonymized for review] and pre-registered with Aspredicted.org (see https://aspredicted.org/DM2_78R).</p> <p><br>This online supplement includes</p> <ul> <li>a codebook describing all instructions and items</li> <li>raw data (anonymised) and analysis script (Note: The raw data contains only the information of persons who were included in the analysis and have agreed to it.)</li> <li>supplemental analyzes</li> </ul>
SARS-Cov-2 illumina sequencing training course
<p>Dataset with two samples of SARS-Cov-2 sequenced with Illumina using Artic v3 amplicon enrichment protocol.</p>
Data for Diniz et al. (2022) Changing the main course: strong bat visitation to the ornithophilous mistletoe Psittacanthus robustus (Loranthaceae) in a Neotropical savanna (Biotropica)
<p>The Neotropical genus <i>Psittacanthus</i> comprises mostly specialized ornithophilous mistletoes, with rare exceptions. <i>Psittacanthus robustus </i>is a common ornithophilous species from the South American savannas whose bright-yellow flowers secrete copious diluted nectar. Due to a three-day-long anthesis and a short, non-restrictive floral tube, we suggest that the species also serves as a resource for flower-visiting bats. In a Cerrado area in central Brazil, we investigated the usage of the species by bats through systematic bat captures for pollen sampling, its nocturnal nectar secretion dynamics, mating system, and the relative dependence on diurnal and nocturnal pollinators for reproduction. Nine phyllostomid bat species visited <i>P. robustus</i>. Up to 50% of pollen samples from bats contained the species<i> </i>during peak flowering, equating or surpassing the prevalence of chiropterophilous species and representing roughly a third of the floral resources consumed by specialized nectarivores <i>Glossophaga soricina </i>and <i>Anoura caudifer</i>. Flowers actively produced nectar at night with volume and concentration values in the ideal ranges for bat consumption. Nectar is continuously secreted after sunset and accumulates in the absence of visitors. <i>Psittacanthus robustus </i>is self-compatible but seeds are set mostly by diurnal visitors. Nocturnal animals had a low and secondary contribution to plant fitness. This is the second report of bat pollination for the genus <i>Psittacanthus</i>, and the largest assemblage of bat visitors for the family Loranthaceae. Although ornithophilous, <i>P. robustus </i>is an important resource for bats in the Brazilian savanna, potentially representing a mixed or early transitional state towards bat pollination.</p>
Course 27255 - Subsampled Sequencing Results
<p>This dataset contains a subset of the raw fastq data of the microbial isolates collected during the course <strong>27255 - Advanced Experimental Prokaryotic Molecular Biology and Ecology (Spring 2022) </strong>at DTU.</p>
Course 27255 - Sequencing Results
<p>This dataset contains the raw fastq data of the microbial isolates collected during the course <strong>27255 - Advanced Experimental Prokaryotic Molecular Biology and Ecology (Spring 2022) </strong>at DTU.</p>
Tutorial videos of MEFisTo software and other UVic ECE 340 course content
<p>An assemblage of tutorial videos and content that document the usage of MEFisTo software and detail example questions from the <em>Fundamentals of Applied Electromagnetism</em> textbook by Ulaby <strong>2014</strong>. These materials were used for the ECE 340 course at the University of Victoria in Winter 2021.</p>
Microspines in tropical climbing plants: a small-scale fix for life in an obstacle course
<p>This dataset is associated to the original research article "Microspines in tropical climbing plants: a small-scale fix for life in an obstacle course" published in the Journal of Experimental Botany. </p> <table> <tbody> <tr> <td>Variable</td> <td>Description</td> <td>Type of variable</td> <td>Units</td> </tr> <tr> <td>sample</td> <td>Sample identifiier</td> <td>Nominal Variable</td> <td> </td> </tr> <tr> <td>sp_code</td> <td>Species identifier</td> <td>Nominal Variable</td> <td> </td> </tr> <tr> <td>sp</td> <td>Species latin name</td> <td>Nominal Variable</td> <td> </td> </tr> <tr> <td>direction</td> <td>Friction test direction</td> <td>Categorical variable</td> <td> </td> </tr> <tr> <td>static_force</td> <td>Force needed to induce motion of the stem segment</td> <td>Continuous variable</td> <td>mN</td> </tr> <tr> <td>sliding_force</td> <td>Force needed to maintain the stem segment in motion</td> <td>Continuous variable</td> <td>mN</td> </tr> <tr> <td>sliding_dist</td> <td>Distance spanned by the stem segment during test</td> <td>Continuous variable</td> <td>mm</td> </tr> <tr> <td>nPeaks</td> <td>Number of force peaks detected during test</td> <td>Discrete variable</td> <td>mN</td> </tr> <tr> <td>peak_frequ</td> <td>Peak frequency during sliding (NPeaks/sliding_dist)</td> <td>Continuous variable</td> <td>peaks.mm<sup>-1</sup></td> </tr> <tr> <td>diam</td> <td>Diameter of the tested segment</td> <td>Continuous variable</td> <td>mm</td> </tr> </tbody> </table> <p> </p>
Systematic analysis of alternative splicing in time course data using Spycone
<p>Spycone is available as a python package that provides systematic analysis of time course transcriptomics data. Figure 1 shows the workflow of Spycone. It uses gene or isoform expression and a biological network as an input. It employs the sum of changes of all isoforms relative abundance (total isoform usage) across time points to detect IS events. It further provides downstream analysis such as clustering by total isoform usage, gene set enrichment analysis, network enrichment, and splicing factors analysis.</p> <p>The SARS-Cov-2 infection and cancer dataset are used as an application demonstration for our Spycone tool and a simulation dataset is used for benchmark analysis. </p> <p>The rhinovirus dataset and SARS-Cov-2 infection (3 time points) for the tutorial in the documentation are included here. </p> <p>The simulated dataset from the 2 models described in the manuscript are uploaded as zen_simdata_{model}_{noise}.csv.</p> <p>A gtf file used in the splicing factor analysis, both in the manuscript and tutorial. Derived from ensembl GRCh38.99.</p>
Data from evaluation of the WHO ICFP2022 Scientific Writing, Mentoring and Coaching Course
<p>Data from the evaluation of the WHO ICFP 2022 scientific writing, mentoring and coaching course.</p> <ol> <li>Dataset includes responses from 49 participants and 12 coaches who responded to a questionnaire about their experience and engagement with the post conference coaching course</li> <li>Dataset includes responses from participants and mentors who attended the ICFP2022 in-conference workshop and mentoring program</li> </ol>
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.