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200 results for “Research integrity”
JasonAlongTrack: A reformatted version of the Integrated Multi-Mission Ocean Altimeter Data for Climate Research Version 5.1
<p>JasonAlongTrack contains geo-registered along-track sea surface height anomalies with respect to the DTU15 mean sea surface at 1-second intervals from Jason-class altimeters, reformatted for convenience into a 3D array with dimensions of along-track direction by geographically sorted track number by cycle.</p><p>This is a reformatted version of Beckley et al.'s <i>Integrated Multi-Mission Ocean Altimeter Data for Climate Research complete time series Version 5.1</i> dataset, available from <a href="https://podaac.jpl.nasa.gov/dataset/MERGED_TP_J1_OSTM_OST_ALL_V51">https://podaac.jpl.nasa.gov/dataset/MERGED_TP_J1_OSTM_OST_ALL_V51</a>. </p><p>The changes are as follows. Altimeter passes are sorted according to their initial longitude, then split into descending and ascending potions with all descending tracks preceding all ascending tracks. Descending tracks are then flipped so that latitude increases in the alongtrack direction for all tracks. This leads to a 3373 x 254 matrix of observational locations, with the first dimension being the along-track location and the second dimension being the track index. Sea surface height anomaly, time, and flag values are then placed into their correct locations within this matrix, such that these three variables are all of size 3373 x 254 x K where K is the number of cycles, currently 1087. A very good approximation to the time at each of the 3373 x 254 x K observation points is constructed with a length K array of cycles times together with a 3373 x 254 array of time offsets. A median-based editing criterion in introduced to identify a small number of suspect data points. These are set to a value of NaN in sla, but their positions and values are recorded in rejected_index and rejected_values, respectively. The DTU15 mean dynamic topography (mdt) is included, in addition to the mean sea surface field already provided, interpolated onto the track locations using bicubic interpolation. Finally, an estimate of the small-scale noise level, sigma, is produced using a wavelet transform filter.</p>
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>
Annex 1 – Actions and measures relevant to research integrity matched to the UK Concordat
<p>The present dataset is an Annex to the Discussion Document entitled “<a href="https://doi.org/10.5281/zenodo.6827947">Indicators of Research Integrity: An initial exploration of the landscape, opportunities and challenges</a>”. </p> <p>It consists in a longlist of actions and measures that organisations may put in place to support research integrity, building on a set of documents that we considered to represent the perspectives of the stakeholder groups mentioned in the UK Concordat to Support Research Integrity, including: </p> <ul> <li> <p>researchers; </p> </li> <li> <p>employers of researchers (i.e. bodies that conduct or host research; employ, support or host researchers; teach research students; or allow research to be carried out under their auspices); </p> </li> <li> <p>research funders; and </p> </li> <li> <p>other organisations (e.g. professional, statutory and regulatory bodies; academies and learned societies; professional and subject-specific representative bodies; journals and publishers; and organisations offering advice, guidance and support). </p> </li> </ul> <p>The table below provides an overview of the documents covered in the dataset. It should be noted that our selection of documents is not meant to imply that other efforts are of lesser importance: it is only a starting point for discussion and seeks to represent a breadth of stakeholder views. </p> <table> <tbody> <tr> <td> <p>Document </p> </td> <td> <p>Lead </p> </td> <td> <p>Main perspective(s) </p> </td> </tr> <tr> <td> <p><a href="https://ukrio.org/wp-content/uploads/UKRIO-Self-Assessment-Tool-for-The-Concordat-to-Support-Research-Integrity-V2.pdf">UKRIO Self-Assessment Tool for The Concordat to Support Research Integrity</a> </p> </td> <td> <p>UK Research Integrity Office (UKRIO) </p> </td> <td> <p>Employers of researchers </p> </td> </tr> <tr> <td> <p><a href="https://doi.org/10.1371/journal.pbio.3000737">The Hong Kong Principles for assessing researchers: Fostering research integrity</a> </p> </td> <td> <p>Moher et al. (academic article) </p> </td> <td> <p>Researchers, Employers of researchers, Research funders </p> </td> </tr> <tr> <td> <p><a href="https://www.vitae.ac.uk/vitae-publications/reports/research-integrity-a-landscape-study">Research integrity: a landscape study</a> </p> </td> <td> <p>UK Research and Innovation (UKRI), Vitae, UK Research Integrity Office (UKRIO), UK Reproducibility Network (UKRN) </p> </td> <td> <p>All stakeholders </p> </td> </tr> <tr> <td> <p><a href="https://wellcome.org/reports/what-researchers-think-about-research-culture">What Researchers Think About the Culture They Work In</a> </p> </td> <td> <p>Wellcome </p> </td> <td> <p>Researchers, Employers of researchers, Research funders </p> </td> </tr> <tr> <td> <p><a href="https://www.allea.org/wp-content/uploads/2017/05/ALLEA-European-Code-of-Conduct-for-Research-Integrity-2017.pdf">The European Code of Conduct for Research Integrity</a> </p> </td> <td> <p>All European Academies (ALLEA) </p> </td> <td> <p>All stakeholders </p> </td> </tr> <tr> <td> <p><a href="http://www.enrio.eu/wp-content/uploads/2019/03/INV-Handbook_ENRIO_web_final.pdf">Handbook on Research Integrity</a> </p> </td> <td> <p>European Network for Research Ethics and Integrity (ENERI) </p> </td> <td> <p>Researchers, Employers of researchers, Research funders </p> </td> </tr> <tr> <td> <p><a href="https://sops4ri.eu/wp-content/uploads/Guideline-for-Promoting-RI-in-RFOs_final.pdf">Guideline for Promoting Research Integrity in Research Funding Organisations</a> </p> </td> <td> <p>Standard Operating Procedures for Research Integrity (SOPs4RI) </p> </td> <td> <p>Research funders </p> </td> </tr> <tr> <td> <p><a href="https://ec.europa.eu/info/funding-tenders/opportunities/docs/2021-2027/horizon/guidance/guideline-for-promoting-research-integrity-in-research-performing-organisations_horizon_en.pdf">Guideline for Promoting Research Integrity in Research Performing Organisations</a> </p> </td> <td> <p>Standard Operating Procedures for Research Integrity (SOPs4RI) </p> </td> <td> <p>Employers of researchers </p> </td> </tr> <tr> <td> <p><a href="https://doi.org/10.24318/cope.2018.1.3">Cooperation between research institutions and journals on research integrity cases: guidance from the Committee on Publication Ethics</a> </p> </td> <td> <p>Committee on Publication Ethics (COPE) </p> </td> <td> <p>Publishers and Employers of researchers </p> </td> </tr> <tr> <td> <p><a href="https://doi.org/10.24318/cope.2019.1.4">COPE Retraction Guidelines</a> </p> </td> <td> <p>Committee on Publication Ethics (COPE) </p> </td> <td> <p>Publishers </p> </td> </tr> </tbody> </table> <p>Find more outputs of this project in the <a href="https://zenodo.org/communities/research-integrity-indicators/">dedicated Zenodo community</a>. </p>
Data Echoes: Tracking Data Availability and Integrity in Software Engineering Research
<p><strong>This is the dataset of the report: Data Echoes: Tracking Data Availability and Integrity in Software Engineering Research</strong></p> <p>It contains the following information of all the papers from ASE, FSE, and ICSE in 2023:</p> <ul> <li>Paper title</li> <li>Keyword</li> <li>Is the source data available and accessible in the paper?</li> <li>If the source data is not available, do the authors explain why?</li> <li>Hosting platforms</li> <li>Access mode</li> <li>License</li> <li>Is their experiment data reused from previous work, or newly generated specifically for this study, or combination of both? </li> <li>Do the authors change/modify their experiment data before experiment?</li> <li>What modifications do they perform?</li> <li>Does the link provide detailed instructions about how to replicate their paper?</li> <li>Does the link contains their complete experiment data, their source code or other materials that are necessary to replicate their experiments?</li> <li>What's the data format inside the link?</li> <li>What's the content of the link?</li> </ul> <p> </p> <p>This is a course project and I collect the data in a rush.</p> <p>If you want to use this dataset and find any error, please contact me ;-)</p> <p>My email: echo.xiangchen@gmail.com</p>
Contextual Factors Research in Continuous Integration (CI) Projects
<p>These files include process documentation for the research on project contextual factors in Continuous Integration (CI). They cover previous research studies and survey details. </p>
Research Integrity Promotion Work
<p>The aim of the research was to delve into the meaningfulness of such work as promotion of research integrity. The following research questions were formulated:</p> <p>1) What aspects of the role of research integrity promoter are meaningful? Why?</p> <p>2) To what changes does research integrity promotion as meaningful work lead?</p> <p>To answer these research questions, a qualitative research approach was employed using individual semi-structured interviews for data collection. The population of interest were national research integrity promoters: national ombudspersons for research integrity (coded as OMB), representatives for research integrity/misconduct from research funding organizations (RFO) and representatives from national research integrity networks (RIN) in European countries.</p> <p>Purposive sampling method was used to select informants. To identify potential informants, we used website of European Network of Research Integrity Offices (<a href="http://www.enrio.eu/">http://www.enrio.eu/</a>) and official websites of target organizations; in addition, snowball method was used to identify potential informants who corresponded to sampling criteria but were not part of the ENRIO membership. At the first stage, 32 potential informants were identified; due to missing contact information or irrelevance of activities as defined in sampling criteria, only 21 informants were invited to participate in the research. Overall, 10 national research integrity promoters (7 females and 3 males; all hold PhD degree and were or currently are part of academia) consented to take part in the research: 5 national ombudspersons for research integrity, 3 representatives for research integrity/misconduct from research funding organizations and 2 representatives from national research integrity networks.</p> <p>Semi-structured questionnaire (interview guide) consisting of five key topics (self-identity, goals, impediments to meaning, enablers to meaning, rewards for meaning-making) and the closing section was used. Interviews were conducted remotely. The interview language was English.</p> <p>Each interview was audio-recorded, transcribed, and anonymized. Average length of interview was 53 minutes; average non-anonymized interview transcript contained 6851 words.</p> <p>Each transcript was validated by two researchers for data accuracy and clarification of inaudible responses; anonymization of each transcript was validated by two researchers and a respective informant. Due to uniqueness of the national status of informants, two informants asked to change their initial consent to disclose anonymized transcript (i.e., they agreed on the use of their interview transcripts for data analysis but not on granting open access to them).</p> <p> </p> <p>The research is published as Tauginienė, L., Gaižauskaitė, I. (2022). Jumping with a Parachute – Is Promoting Research Integrity Meaningful? <em>Accountability in Research: Policies and Quality Assurance</em>. https://doi.org/10.1080/08989621.2022.2044318</p>
Research compendium for 'The contribution of integrated 3D model analysis to Protoaurignacian stone tool design'
<p><strong>Abstract:</strong> Protoaurignacian foragers relied heavily on the production and use of bladelets. Techno-typological studies of these implements have provided insights into important aspects of cultural variability. However, new technologies have seldom been used to quantify patterns of stone tool design. Taking advantage of a new scanning protocol and open-source software, we conduct the first 3D analysis of a Protoaurignacian assemblage, focusing on the selection and modification of blades and bladelets. We study a large sample of complete blanks and retouched tools from the early Protoaurignacian assemblage at Fumane Cave in northeastern Italy. Our main goal is to validate and refine previous techno-typological considerations employing a 3D geometric morphometrics approach complemented by 2D analysis of cross-section outlines and computations of retouch angle. The encouraging results show the merits of the proposed integrated approach and confirm that bladelets were the main focus of stone knapping at the site. Among modified bladelets, various retouching techniques were applied to achieve specific shape objectives. We suggest that the variability observed among retouched bladelets relates to the design of multi-part artifacts that need to be further explored via renewed experimental and functional studies.</p> <p><strong>Overview of contents:</strong></p> <p>01. AGMT3-D project of the first dataset used in the study;</p> <p>02. AGMT3-D project of the second dataset used in the study;</p> <p>03. Raw outline data of the middle cross-section. Each specimens has a dedicate .txt file;</p> <p>04. Raw outline data of the upper cross-section. Each specimens has a dedicate .txt file;</p> <p>05. Angles3-D project with all files generated by the software (.mat and .xlsx formats) to quantify the mean retouch angle of retouched bladelets;</p> <p>06. R project and scripts for the 1) 2D shape analysis of the middle and upper cross-sections of retouched bladelets and the 2) design of all bivariate plots and boxplots with jittered points used in the paper. All related datasets, principal components, and generated figures are included in the folder;</p> <p>07. Folder with all figures published in the paper and in its supplementary materials;</p> <p>08. Dataset of the first study in .csv with all attributes used to run the statistical analysis presented in the paper;</p> <p>09. Dataset of the second study in .csv with all attributes used to run the statistical analysis presented in the paper;</p> <p>10. Dataset for the study of the upper cross-sections in .csv with all attributes used to run the statistical analysis presented in the paper;</p> <p>11. Dataset for the study of the middle cross-sections in .csv with all attributes used to run the statistical analysis presented in the paper;</p> <p>12. Dataset in .csv used to study the mean retouch angles;</p> <p>13. Supplementary information file in .pdf with all supplementary figures and tables.</p> <p><strong>Extra</strong>: All 3D meshes of blades and bladelets are available on Zenodo following this link: https://doi.org/10.5281/zenodo.6362150.</p>
Dataset for 'A Resource Hub For Interoperability And Data Integration In Heritage Research: The H-Setis Database'
<p> Data and scripts for charts and maps published in "A Resource Hub For Interoperability And Data Integration In Heritage Research: The H-Setis Database".</p>
Combat-TB-NeoDB: fostering Tuberculosis research through integrative analysis using graph database technologies.
<p>NeoDB is a free and open source integrated M.tuberculosis ‘omics’ knowledge-base. NeoDB is based on Neo4j and enables researchers to execute complex federated queries by linking well-known, curated and widely used biological data resources, and supplementary TB variants data from published literature.</p> <p>Documentation can be found at https://combat-tb-db.readthedocs.io</p>
Data Echoes: Tracking Data Availability and Integrity in Software Engineering Research
<p><strong>This is the dataset of the report: Data Echoes: Tracking Data Availability and Integrity in Software Engineering Research</strong></p> <p>It contains the following information of all the papers from ASE, FSE, and ICSE in 2023:</p> <ul> <li>Paper title</li> <li>Keyword</li> <li>Is the source data available and accessible in the paper?</li> <li>If the source data is not available, do the authors explain why?</li> <li>Hosting platforms</li> <li>Access mode</li> <li>License</li> <li>Is their experiment data reused from previous work, or newly generated specifically for this study, or combination of both? </li> <li>Do the authors change/modify their experiment data before experiment?</li> <li>What modifications do they perform?</li> <li>Does the link provide detailed instructions about how to replicate their paper?</li> <li>Does the link contains their complete experiment data, their source code or other materials that are necessary to replicate their experiments?</li> <li>What's the data format inside the link?</li> <li>What's the content of the link?</li> </ul> <p> </p> <p>We collect the data in a rush.</p> <p>If you want to use this dataset and find any errors, please contact us ;-)</p> <p> </p> <p>Our emails:</p> <ul> <li>echo.xiangchen@gmail.com</li> <li>zhifengyao731@gmail.com</li> </ul>
Research integrity practices and environmental impact of research: Questionnaire of the survey conducted at two French institutions
<p>This dataset is a questionnaire designed to evaluate researchers' understanding, application, and perception of responsible research principles, and to identify strengths and weaknesses in their implementation.<br>It contains about thirty questions and covers various and sometimes complex topics: responsible and inclusive research practices, public trust in science, climate crisis, reduction of GHG emissions caused by research activities, research integrity, researchers' engagement in the public sphere.</p> <p>It is divided into 6 sections:<br>- Relations between science and society <br>- Conducting research in a changing world <br>- Ethics and research integrity <br>- Engaged research <br>- Science communication </p> <p>To enable comparative analysis, it incorporates questions from other surveys which are cited as references.</p>
Role of the RIO (Research Integrity Officer) at the University of Florida
<p><strong>Role of the RIO</strong><br> Learn more about the importance of research integrity at UF and the role of the Research Integrity Officer (RIO) in helping you navigate potential instances of research misconduct. Contact <a href="mailto:RIO@research.ufl.edu">RIO@research.ufl.edu</a> for assistance.</p>
Data sharing: an integral part of research practice? Codebook
<p>List of thematic codes for qualitative review of studies focusing on data sharing motives and barriers.</p>
Open dataset for the research of "Assessing accuracy improvement of integrating digital footprints into gridded population mapping: spatiotemporal variations and data bias"
<p>Result datasets for "Assessing accuracy improvement of integrating digital footprints into gridded populationmapping:spatiotemporal variations and data bias":</p> <ol> <li> S1 is the results for gridded population mapping using different methods.</li> <li> S2 is the aggregate results of population mapping at county level.</li> <li> S3 is the results for intraday variation of population disaggregation accuracy,</li> <li> S4 is the data bias of different digital footprints.</li> </ol>
The Role of the Research Integrity Officer (RIO) External Editable File
<p><strong>Role of the RIO</strong><br> Learn more about the importance of research integrity at UF and the role of the Research Integrity Officer (RIO) in helping you navigate potential instances of research misconduct. This video is for external audiences to modify/adapt for their own institution.</p>
Literature compilation for: The rise of animal biotelemetry and genetics research data integration
<p><span>The advancement and availability of innovative animal biotelemetry and genomic technologies are improving our understanding of how the movements of individuals influence gene flow within and between populations and ultimately drive evolutionary and ecological processes. There is a growing body of work that is integrating what were once disparate fields of biology, and here we reviewed the published literature up until January 2023 (139 papers) to better understand the drivers of this research and how it is improving our knowledge of animal biology. The review showed that the predominant drivers for this research were: i) understanding how individual-based movements affect animal populations, ii) analyzing the relationship between genetic relatedness and social structuring, and iii) studying how the landscape affects the flow of genes, and how this is impacted by environmental change. However, there was a divergence between taxa as to the most prevalent research aim, and the methodologies applied. We also found that after 2010 there was an increase in studies that integrated the two data types using innovative statistical techniques instead of analyzing the data independently using traditional statistics from the respective fields. This new approach greatly improved our understanding of the link between </span><span>the individual, the population, and the environment and is being used to better conserve and manage species. We discuss the challenges and limitations, as well as the potential for growth and diversification of this research approach. The paper provides a guide for researchers who wish to consider applying these disparate disciplines and advancing the field.</span></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>
Review of annual statements on research integrity - Annex B - Full dataset
<p>This dataset has been shared as a supplementary material to the report "Review of annual statements on research integrity", also available via Zenodo at https://doi.org/10.5281/zenodo.8014377 </p> <p><br> Please note that, although all information in annual research integrity statements is publicly available, the names of institutions have been pseudonymised to minimise the risk of inappropriate comparisons or benchmarking.</p>
Literature compilation for: The rise of animal biotelemetry and genetics research data integration
Open the record for dataset details and reuse information.
Supplemental data for: Type genomics: a framework for integrating genomic data into biodiversity and taxonomic research
Open the record for dataset details and reuse information.
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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)
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.