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.
117
datasets available to search
ShareScore release 0.7.1
Dataset results
117 results for “research article”
Data underlying the manuscript: "Analysis of Research Data Sharing in Scientific Articles on Climate Change in the Covid-19 Year. The Spanish case 2020".
<p>This is the research data for the manuscript "Analysis of Research Data Sharing in Scientific Articles on Climate Change in the Covid-19 Year. The Spanish case 2020".<br>The following is the original abstract: Introduction: Sharing research data on climate change would facilitate the development of solutions to curb its impact, for this, data needs to be shared in an optimal way. General objective: To identify how many Spanish scientific articles on climate change published during 2020 share their research data in some way. Specific objectives: a) Identify the attributes of shared research data b) Describe the characteristics of the case studies found on how research data are shared. Methodology: Qualitative and descriptive study analyzing nine attributes: availability (1), accessibility (2), format (3), license (4), linkage (5), funding (6), editorial policy (7), content (8), statistics (9). Results: We analyzed 2212 articles were analyzed, 1867 (84%) articles had no associated research data. The remaining 16% have associated research data: 152 (7%) articles deposited their data in repositories, 42 (2%) submitted their data as supplementary material, 136 (6%) will share their data upon request to the author and 15 (1%) do not have publication permissions. Conclusions: Researchers are willing to share their research data, but under different conditions. Researchers who reused research data did not share the new data they generated. There is a lack of training among researchers on how to manage their research data. There is information on the web on this topic, but it is not just a matter of publishing manuals, but also of creating training spaces within universities, institutes and research centers to build a community of researchers committed to Open Science.</p>
Dataset of the research article "Choline Oxidase and Choline Ionic Liquids in Biocatalytic Heme Peroxidase Cascades"
<p>The dataset contains primary data related to the article entitled "Choline Oxidase and Choline Ionic Liquids in Biocatalytic Heme Peroxidase Cascades", published in ChemCatChem. The dataset contains spreadsheet data detailing kinetic measurements and calculations.</p>
Data collection of article research tittle "Online GIS and Remote Sensing-Based Mapping of Flood Vulnerability in Samarinda Seberang Subdistrict"
<p>This dataset contains the definition and name of the data used in the study. It also contains rows of data for all flood parameters applied to the creation of flood vulnerability maps, namely rainfall data, landsat-8 files, DEM, DSMW and drainage survey data.</p>
Data testing of article research tittle "Online GIS and Remote Sensing-Based Mapping of Flood Vulnerability in Samarinda Seberang Subdistrict"
<p>This dataset explains validation testing in a study of the Samarinda Seberang flood vulnerability map. There are two test methods, namely the Kappa accuracy test and the 3D simulation visualization test. The Kappa accuracy test tab displays a table of Kappa calculation results, and the second tab contains a 3D simulation scenario image.</p>
Data for the research article: "Detecting Seismo-ionospheric Anomalies Possibly Associated with the 2019 Ridgecrest (California) Earthquakes by GNSS, CSES and Swarm Observations"
<p>The zip archives contain 10 .mat files (MATLAB readable). Each .mat file can be loaded into the MATLAB workspace using the <em>load</em> command.</p>
Research data supporting article "Somatic mutation rates scale with lifespan across mammals"
<p>Data files supporting analyses described in the article "Somatic mutation rates scale with lifespan across mammals" (Cagan, Baez-Ortega et al., 2022).</p>
Master chart dor Research article
<p><strong>Title: </strong>Salivary Cortisol levels associated with Anxiety in Type II Diabetes Mellitus Patients before and after Complete Denture Rehabilitation. -In vivo analysis.</p> <p>All the observations for each patient are compiled in the data sheet</p>
Dataset for "Initial insight of three modes of data sharing: Prevalence of primary reuse, data integration and dataset release in research articles"
<p>The dataset for "Initial insight of three modes of data sharing: Prevalence of primary reuse, data integration and dataset release in research articles" is coded as follows:</p> <p>01 DOI: DOI<br> 02 article number: the accession number in Web of Science<br> 03 article title: title of the articles<br> 04 exclude: if the article was excluded from the sample, assign 1.<br> 05 research_field: the categories of research fields are described in the Appendix (Table S1)<br> 06 target_of_study: the categories of the target of studies are described in the Appendix (Table S1)<br> 29 release_location_nameofpublicarchive: the names of the deposited public archives (comma separated)</p> <p>The following items, if they occur, are assigned a value of 1:<br> 07 No_datause: The article did not use data<br> 08 primary_reuse: primary reuse<br> 09 primary_data_specificresarchdata: primary reuse of specific research data<br> 10 primary_data_resource: primary reuse of resource<br> 11 primary_source_self: primary reuse from self-constructed data<br> 12 primary_source_citation: primary reuse from citation<br> 13 primary_source_archive: primary reuse from an archive<br> 14 primary_source_others: primary reuse from the other source<br> 15 primary_souce_na: primary reuse source is not available<br> 16 data_integration: data integration<br> 17 integration_type_empirical: data integration as empirical type<br> 18 integration_type_Introductionmaterialresearchmethod: data integration as introduction/material/research methods type<br> 19 integration_type_combinedanalysis: data integration as introduction/material/research methods type<br> 20 integration_source_self: data integration from self-constructed data<br> 21 integration_source_citation: data integration from citation<br> 22 integration_source_archive: data integration from an archive<br> 23 integration_source_others: data integration from the other source<br> 24 integration_source_na: data integration source is not available<br> 25 dataset_release: dataset release<br> 26 release_location_publicarchive: dataset deposit to a public archive <br> 27 release_location_supporting: dataset release in Supporting Information<br> 28 release_location_onrequest: dataset release through personal contacts </p> <p> </p> <p>The appendix includes following tables:<br> Table S1. Coding schema for analysis<br> Table S2. Primary reuse by research field and reused data<br> Table S3. Primary reuse by target of study and reused data<br> Table S4. Data integration by research field and reuse type<br> Table S5. Data integration by target of study and reuse type<br> Table S6. Dataset release by research field<br> Table S7. Dataset release by target of study and methods<br> Table S8. List of names of public data archives for dataset release</p>
Supplementary material for the ITP'23 article "Lessons for Interactive Theorem Proving Researchers from a Survey of Coq Users"
<p>This artifact contains the supplementary files for the ITP'23 article "Lessons for Interactive Theorem Proving Researchers from a Survey of Coq Users". More specifically, it contains:</p> <ul> <li>the Limesurvey structure exported file (<code>Limesurvey/survey-structure.lss</code>);</li> <li>the HTML print of the survey in English and Chinese (<code>Limesurvey/questionnaire_english.html</code> and <code>Limesurvey/questionnaire_chinese.html</code>);</li> <li>the Jupyter notebook (<code>Coq-survey-analysis.ipynb</code>) and the Stata code (<code>regressions/Regressions_and_Romano-Wolf.do</code>) that were used to produce the results;</li> <li>the plots for the answers to all the closed questions, as well as plots for some interactions between answers to multiple closed questions in <code>png</code> and <code>svg</code> formats (<code>assets/</code>);</li> <li>manual analysis of some open text questions (<code>coded_answers/</code>);</li> <li>answers to open text questions (<code>open_answers/</code>).</li> </ul> <p>This artifact does <em>not</em> contain the full raw data from the survey. These data have been deleted, following the GDPR compliance statement that was displayed at the beginning of the survey. The open text answers that are made available through this artifact have been sanitized to remove any personally identifiable element.</p> <p>File listing</p> <ul> <li>README.md: this README</li> <li>Limesurvey <ul> <li>questionnaire_english.html: survey HTML print in English</li> <li>questionnaire_chinese.html: survey HTML print in Chinese</li> <li>survey-structure.lss: Limesurvey structure export</li> </ul> </li> <li>Coq-survey-analysis.ipynb: Jupyter notebook used to produce plots</li> <li>regressions <ul> <li>Regressions_and_Romano-Wolf.do: Stata code used to do the regressions appearing in the article</li> </ul> </li> <li>assets <ul> <li>many <code>png</code> and <code>svg</code> files for plots showing quantitative results</li> </ul> </li> <li>coded_answers <ul> <li>renaming.md: manual analysis of the answers to the open text question "If you wish to elaborate on why Coq should / should not be renamed, feel free to do it here."</li> <li>renaming_choices.md: manual analysis of the answers to the open text question "If you wish to share any specific arguments in favor or against some specific name choices, please do so here."</li> <li>contributing_experience.csv: answers to the open text question "Feel free to elaborate on the contributing experience, what we can do better, or why you do not contribute." with manual analysis</li> <li>doc_improvements-grouped.docx manual analysis of the answers to the open text question "Feel free to elaborate on any of the items listed above, their importance, etc. Are there other improvements that you think would be important?" (in the context of a question on "How important are improvements to the following aspects of the Coq documentation?")</li> </ul> </li> <li>open_answers: Each table has been reordered and has a different indexing, so relating answers from different tables is not possible. Furthermore, answers have been checked and sanitized to remove any personally identifiable elements. <ul> <li>ci_feedback.csv: answers to the question "If you have general feedback on CI in the Coq ecosystem, feel free to share it here." Also shared at: <a href="https://github.com/coq-community/manifesto/issues/141">https://github.com/coq-community/manifesto/issues/141</a></li> <li>contributing_experience.csv: answers to the question "Feel free to elaborate on the contributing experience, what we can do better, or why you do not contribute."</li> <li>coqide_improvements.csv: answers to the question "What improvements, bug fixes and new features would you most like to see in CoqIDE?" Also shared at: <a href="https://github.com/coq/coq/issues/16580">https://github.com/coq/coq/issues/16580</a></li> <li>coq_improvements.csv: answers to the question "Feel free to elaborate on any of the items listed above, their importance, etc. Are there other improvements that you think would be important? Also, feel free to tell us how Coq does compared to other proof assistants you have experience with." (in the context of a question on "In order to make you more productive in Coq and to encourage others to learn and use Coq, how important are improvements in the following areas?")</li> <li>coqtail_improvements.csv: answers to the question "What improvements, bug fixes and new features would you most like to see in Coqtail?" Also shared at: <a href="https://github.com/whonore/Coqtail/issues/277">https://github.com/whonore/Coqtail/issues/277</a></li> <li>distracting_company_coq_features.csv</li> <li>doc_improvements.csv: answers to the question "Feel free to elaborate on any of the items listed above, their importance, etc. Are there other improvements that you think would be important?" (in the context of a question on "How important are improvements to the following aspects of the Coq documentation?")</li> <li>extraction_targets.csv: answers to the question "If you're interested in new extraction targets, which languages do you want?" Also analyzed quantitatively in: assets/extraction-targets-barplot.png</li> <li>jscoq_improvements.csv: answers to the question "What improvements, bug fixes and new features would you most like to see in jsCoq?" Also shared at: <a href="https://github.com/jscoq/jscoq/issues/261">https://github.com/jscoq/jscoq/issues/261</a></li> <li>jupyter_improvements.csv: answers to the question "What improvements, bug fixes and new features would you most like to see in coq_jupyter?" Also shared at: <a href="https://github.com/EugeneLoy/coq_jupyter/issues/46">https://github.com/EugeneLoy/coq_jupyter/issues/46</a></li> <li>jupyter_support.csv: answers to the question "Have you had any issues or lack of support for coq_kernel for any service? If so, feel free to share here." Also shared at: <a href="https://github.com/EugeneLoy/coq_jupyter/issues/46">https://github.com/EugeneLoy/coq_jupyter/issues/46</a></li> <li>languages.csv: answers to the question "What languages would be the most useful to support?" Also analyzed quantitatively in: assets/languages-barplot.png</li> <li>learning_experience.csv: answers to the question "How was your experience while learning Coq? For example, what were the easiest and/or most difficult parts of the process? Do you have suggestions to improve the experience?"</li> <li>proof_general_customizations.csv: answers to the question "Do you use specific customizations or fixups of Proof General or Company-Coq (in your ~/.emacs)? If yes, briefly speaking, what are these customizations and would you like to have some of them applied by default?" Also shared at: <a href="https://github.com/ProofGeneral/PG/issues/671">https://github.com/ProofGeneral/PG/issues/671</a></li> <li>proof_general_improvements.csv: answers to the question "What improvements, bug fixes and new features would you most like to see in Proof General?" Also shared at: <a href="https://github.com/ProofGeneral/PG/issues/671">https://github.com/ProofGeneral/PG/issues/671</a></li> <li>renaming.csv: answers to the question "If you wish to elaborate on why Coq should / should not be renamed, feel free to do it here."</li> <li>renaming_choices.csv: answers to the question "If you wish to share any specific arguments in favor or against some specific name choices, please do so here."</li> <li>survey_issues.csv: answers to the question "Did you encounter any issues with the survey that you'd like to report or do you have other feedback that we should hear about?"</li> <li>vim_compatibility.csv: answers to the question "What Vim / NeoVim features or plugins would you like to have better integrated with Coqtail? " Also shared at: <a href="https://github.com/whonore/Coqtail/issues/277">https://github.com/whonore/Coqtail/issues/277</a></li> <li>vscoq_improvements.csv: answers to the question "What improvements, bug fixes and new features would you most like to see in VsCoq?" Also shared at: <a href="https://github.com/coq-community/vscoq/issues/308">https://github.com/coq-community/vscoq/issues/308</a></li> </ul> </li> </ul>
Dataset of the Article Evaluating a Framework of Conceptual Modelling Research through a Family of Experiments
<p>Data set of the article "Evaluating a Framework of Conceptual Modelling Research through a Family of Experiments". Contains the results of:</p> <p>-Demographic questionnaire</p> <p>- Agreement and correctness of Paper A</p> <p>- Agreement and correctness of Paper B</p> <p>- Agreement and correctness of Paper C</p> <p>-Satisfaction questionnaire</p> <p>-Procedure and Pros and Cons of the framework</p>
Dataset for: Do you Cite What you Tweet? Investigating the relationship between tweeting and citing research articles
<p>This dataset was used for the work "Do you cite what you tweet? Investigating the relationship between tweeting and citing research articles", submitted to the Quantitative Science Studies Journal. The accompanying R script was used for the logistic regression model in the paper.</p> <p> </p> <p> </p>
Data-set for "Reliability and operation cost of underdamped memories during cyclic erasures" (Research Article, No. apxr.202300074) to Advanced Physics Research.
<p><strong>Dataset for the article: "Reliability and operation cost of underdamped memories during cyclic erasures" (Research Article, No. apxr.202300074) to Advanced Physics Research. </strong></p> <ul> <li><strong>FigX.fig: </strong>Matlab format figure source used to draw all of the plots of the article, embedding the all data.</li> <li><strong>evolution_K.m:</strong> Matlab code file that implement the Repeated Erasure model and compute the success rate of the erasure from the temperature evolution computed from the model.</li> <li><strong>Model_Landauer_enchaine.m:</strong> Matlab code file. Function which uses the SE Model to calculate the evolution of all the energy quantities (average) during step 1 and step 2 starting at an initial temperature CI, and also renders the final temperature conditions to be used iteratively in the RE Model.</li> <li><strong>Toy_Model.m: </strong>Theoretical toy model for explaning the Landauer repeted erasures temperature evolution.</li> <li><strong>Analysis_repeated_erasure.m:</strong> Matlab code file to treat raw data .mat files of 45 repeated erasures to compute the energy, work and heat evolution. The average is done on the full raw data samples corresponding to thousands of 45 repeated erasures.</li> <li><strong>XmsRawData.zip:</strong> Raw data of 45 repeated erasures of duration X ms each. Those Matlab data files are meant to be analysed with the Analysis_repeated_erasure code. Among the usefull variables contained in those files we identifiy :</li> </ul> <ol> <li>V: applied protocol, position of center of the wells in nm</li> <li>x: position signal in nm</li> <li>sigma_m: calibration of the standard deviation used by the feedback</li> <li>x0: threshold of the virtual potential</li> <li>tau1: duration of step1</li> <li>tau2: duration of step 2</li> <li>tau4: half resting time between step1 and step2</li> <li>X1: initial half distance between the wells</li> <li>dt: acquisition sampling time</li> </ol> <p><br> </p> <p> </p>
research data for the article Elenius et al, 'Where can rewetting of forested peatland reduce extreme flows?'
<p>This dataset includes data of changes in hydrology when rewetting of drained forested peatland is performed. Details are explained in the companion article, Elenius et al, 'Where can rewetting of forested peatland reduce extreme flows?'</p> <p>Data worksheets and columns are described on the readme worksheet in the file.</p>
Research data supporting article "Recurrent horizontal transfer identifies mitochondrial positive selection in a transmissible cancer"
<p>Gene expression data supporting analyses described in the article "Recurrent horizontal transfer identifies mitochondrial positive selection in a transmissible cancer" (Strakova et al., 2020).</p>
Raw data for the research article "The relevance of pyrogenic carbon for carbon budgets from fires: insights from the FIREX experiment"
<p>These are the raw data for the paper entitled "The relevance of pyrogenic carbon for carbon budgets from fires: insights from the FIREX experiment" that is currently under revision in Global Biochemical Cycles. </p>
The clinical impact of high-profile animal-based research reported in the UK national press: a detailed discussion of articles from 1995, and full search results from the Nexis database
<p><span><span><span><span><span><span><span><span><span><span><span><b>Objectives</b>: We evaluated animal-based biomedical 'breakthroughs' reported in the UK national press in 1995 (25 years prior to the conclusion of this study). Based on evidence of over-speculative reporting of biomedical research in other areas (e.g. press releases and scientific papers), we specifically examined animal research in the media, asking, "In a given year, what proportion of animal research 'breakthroughs' published in the UK national press had translated, more than 20 years later, to approved interventions?"</span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span><b>Methods</b>: We searched the Nexis media database (LexisNexis.com) for animal-based biomedical reports in the UK national press. The only restrictions were that the intervention should be specific, such as a named drug, gene, biomedical pathway, to facilitate follow-up, and that there should be claims of some clinical promise. </span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span><b>Main Outcome Measures</b>: Were any interventions approved for human use? If so, when and by which agency? If not, why, and how far did development proceed? Were any other, directly related interventions approved? Did any of the reports over-state human relevance?</span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span><b>Results</b>: Over-speculation and exaggeration of human relevance was evident in all the articles examined. Of 27 unique published 'breakthroughs', only one had clearly resulted in human benefit. Twenty were classified as failures, three were inconclusive, and three were partially successful.</span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span><b>Conclusions</b>: The results of animal-based pre-clinical research studies are commonly over-stated in media reports, to prematurely imply often-imminent 'breakthroughs' relevant to human medicine.</span></span></span></span></span></span></span></span></span></span></span></p>
Dataset for the research article entitled " New insights on the Empty Quarter desert environment derived from the WInd-blown Sand Experiment (WISE)"
Open the record for dataset details and reuse information.
INDEX OF ARTICLES PUBLISHED IN THE JOURNAL "NATURE CONSERVATION RESEARCH"
<p>This data file includes the list of articles previously published in the journal “Nature Conservation Research” (https://ncr-journal.bear-land.org/).</p> <p>All articles are grouped by the research thematic.</p> <p>As an explanation of each article, a brief (one sentence) description is provided by highlighting its contents. The Archive of the journal is available here: https://ncr-journal.bear-land.org/journal</p>
Research data supporting "article test"
<p>Research data supporting "article test"</p>
Digital research materials of spectral data for the article: [3+2]-Cycloaddition of azomethine ylides to 5-methylidene-3-aryl-2-сhalcogen-imidazolones: Access to dispiro indolinone-pyrrolidine-imidazolones
<p>Digital research materials of NMR spectral data for the article "[3+2]-Cycloaddition of azomethine ylides to 5-methylidene-3-aryl-2-сhalcogen-imidazolones: access to dispiro indolinone-pyrrolidine-imidazolones" submitted to the <em>Royal Society Open Science. </em>NMR spectra were recorded on Bruker Avance 400 and Agilent MR-400 spectrometers in DMSO-d<sub>6</sub> and C<sub>6</sub>D<sub>6</sub>. Chemical shifts were measured relative to residual solvent signals and referenced in parts per million to TMS. Original fid files are presented, which can be opened, for example, using the ASD Labs software package.</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.