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213 results for “Research management”
Supplementary materials of the paper Identifying benchmark units for research management and evaluation
<p>Supplementary materials of the paper Identifying benchmark units for research management and evaluation</p> <p>Supplementary1 Rsearch topics of Hero-m and SciLifeLab</p> <p>Supplementary2 Topics of benchmarks</p> <p>Supplementary3 Measures of connectivity</p>
Quantitative assessment of research data management practice - 2021
<p>This survey aims to investigate research data management practices at EPFL and integrate their results into specific academic services. The previous two editions, in collaboration with TU Delft, Cambridge University and Illinois University, were carried out in 2017 and 2019.</p> <p>The objective of these surveys is to collect information on researchers' habits in terms of management of their research data, as well as to identify their needs for data curation services/support. For this edition of the survey, a particular focus has been given to the ways in which they disseminate data and code.</p> <p>You can find here a file corresponding to the report, in PDF, highlighting the findings of the survey, plus the file of the underlying data, in CSV, and a file with the graphical representation of such data, in PDF.<br> <br> For more information about this survey, a description on how the survey might be re-used by other institutions, and RDM services offered by the EPFL Library, please contact <a href="mailto:researchdata@epfl.ch?subject=Concerning%20the%20EPFL%20survey%20on%20RDM%20practices">researchdata@epfl.ch</a>.</p>
Data literacy and research data management survey
<p>Data from Czech version of Data literacy and research data management multinational study.</p>
Culture Collaboratory. Virtual Workspace for Interdisciplinary Collections Research and Management (Film)
<p>This short video presents the design concept of »Culture Collaboratory«, an interdisciplinary and interactive research platform and collections management system for museum professionals. »Culture Collaboratory« provides a virtual workspace that supports interdisciplinary collaboration and allows researchers to engage with collection objects, organize research processes, and share their knowledge.</p>
WebMicroscope's Deep Learning AI platform automates image analyses with an approach that is faster and able to understand tissue context, which reduces steps needed for accurate results. Researchers can gain access to digitized samples, such as this image of breast-cancer tissue (left), and analyze results through the cloud platform anywhere, anytime. This is a whole slide image of a tissue section of an adrenal gland (right). Fimmic's WebMicroscope cloud platform allows researchers to manage, share, and view digital gigapixel images with any modern browser. Researchers can rapidly pan, zoom, and analyze a digital sample. Photographs: Courtesy of Fimmic Oy. in Deep learning brings speed, accuracy to the life sciences.
WebMicroscope's Deep Learning AI platform automates image analyses with an approach that is faster and able to understand tissue context, which reduces steps needed for accurate results. Researchers can gain access to digitized samples, such as this image of breast-cancer tissue (left), and analyze results through the cloud platform anywhere, anytime. This is a whole slide image of a tissue section of an adrenal gland (right). Fimmic's WebMicroscope cloud platform allows researchers to manage, share, and view digital gigapixel images with any modern browser. Researchers can rapidly pan, zoom, and analyze a digital sample. Photographs: Courtesy of Fimmic Oy.
Supplementary material 7 from: Borghi J, Abrams S, Lowenberg D, Simms S, Chodacki J (2018) Support Your Data: A Research Data Management Guide for Researchers. Research Ideas and Outcomes 4: e26439. https://doi.org/10.3897/rio.4.e26439
A draft guide that corresponds with the "Sharing and publishing your data" row of the RDM rubric. Suggested points of customization are highlighted in yellow (discipline-specific) and red (institution-specific).
Supplementary material 6 from: Borghi J, Abrams S, Lowenberg D, Simms S, Chodacki J (2018) Support Your Data: A Research Data Management Guide for Researchers. Research Ideas and Outcomes 4: e26439. https://doi.org/10.3897/rio.4.e26439
A draft guide that corresponds with the "Analyzing your data and handling the outputs" row of the RDM rubric. Suggested points of customization are highlighted in yellow (discipline-specific) and red (institution-specific).
Supplementary material 4 from: Borghi J, Abrams S, Lowenberg D, Simms S, Chodacki J (2018) Support Your Data: A Research Data Management Guide for Researchers. Research Ideas and Outcomes 4: e26439. https://doi.org/10.3897/rio.4.e26439
A draft guide that corresponds with the "Saving and backing up your data" row of the RDM rubric. Suggested points of customization are highlighted in yellow (discipline-specific) and red (institution-specific).
Supplementary material 3 from: Borghi J, Abrams S, Lowenberg D, Simms S, Chodacki J (2018) Support Your Data: A Research Data Management Guide for Researchers. Research Ideas and Outcomes 4: e26439. https://doi.org/10.3897/rio.4.e26439
A draft guide that corresponds with the "Organizing your data" row of the RDM rubric. Suggested points of customization are highlighted in yellow (discipline-specific) and red (institution-specific).
Supplementary material 5 from: Borghi J, Abrams S, Lowenberg D, Simms S, Chodacki J (2018) Support Your Data: A Research Data Management Guide for Researchers. Research Ideas and Outcomes 4: e26439. https://doi.org/10.3897/rio.4.e26439
A draft guide that corresponds with the "Getting your data ready for analysis" row of the RDM rubric. Suggested points of customization are highlighted in yellow (discipline-specific) and red (institution-specific).
Supplementary material 2 from: Borghi J, Abrams S, Lowenberg D, Simms S, Chodacki J (2018) Support Your Data: A Research Data Management Guide for Researchers. Research Ideas and Outcomes 4: e26439. https://doi.org/10.3897/rio.4.e26439
A draft guide that corresponds with the "Planning your project" row of the RDM rubric. Suggested points of customization are highlighted in yellow (discipline-specific) and red (institution-specific).
Supplementary material 1 from: Van Tuyl S, Whitmire A (2018) Investigation of Non-Academic Data Management Practices to Inform Academic Research Data Management. Research Ideas and Outcomes 4: e30829. https://doi.org/10.3897/rio.4.e30829
Interview protocol used for the project, "Investigation of Non-Academic Data Management Practices to Inform Academic Research Data Management"
Why research data management: four videos
<p>See https://rdmpromotion.rbind.io, and doi: <a href="https://doi.org/10.5281/zenodo.1293375">10.5281/zenodo.1293375</a> </p> <p>The four videos are presented in their own folder, we have one version without sound, and the music and the voice over sound in three different files. Finally, the version with all 4 elements is also there. The videos were also pushed to figshare and got their own doi there (they are also on youtube at the moment).</p> <p>01_opendata, doi: https://doi.org/10.6084/m9.figshare.7379942<br> 02_retrievedata, doi: https://doi.org/10.6084/m9.figshare.7163396<br> 03_analysedata, doi: https://doi.org/10.6084/m9.figshare.7673543<br> 04_data_champions, doi: https://doi.org/10.6084/m9.figshare.7053797</p> <p>subtitles (including translations) can be found here and at https://github.com/open-science-promoters/RDM-promotion/tree/master/subtitlesvideo. You may want to check youtube for later translations. </p> <p>Note that timing of the voice over of the 3d movie had to be modified, and a second file with the modification is included.</p> <p><br> Source of videos:</p> <p>01_opendata:</p> <p>Superman, Secret Agent<br> Superman, Billion dollar limited<br> Superman, Superman (the mad scientist)<br> Superman, Japoteurs<br> Superman, the magnetic telescope (music only)</p> <p>source: toonamiarsenal.com (deprecated, see archive.org to get it)</p> <p>02_retrievedata:<br> Popeye, Parlez Vous Woo<br> Popeye, A date to skate<br> Popeye, A Haul in One</p> <p>source: archive.org</p> <p>03_analysedata:<br> The haunted house<br> One week</p> <p>source: archive.org</p> <p>04_data_champions:<br> classic TV commercial from the 50s,<br> ClassicT1948_7<br> ClassicT1948_8<br> Televisi1960</p> <p>source: prellinger collection, archive.org</p>
FAIRness of Repositories & Their Data: A Report from LIBER's Research Data Management Working Group
<p>Data repositories play a crucial role in the evolution of Open Science. The FAIR Data Principles establish how to make data Findable, Accessible, Interoperable and Reusable (Wilkinson et al., 2016). The FAIR principles are as follows: </p> <p><strong>To Be Findable</strong></p> <ul> <li>F1. (meta)data are assigned a globally unique and eternally persistent identifier.</li> <li>F2. data are described with rich metadata.</li> <li>F3. (meta)data are registered or indexed in a searchable resource.</li> <li>F4. metadata specify the data identifier.</li> </ul> <p><strong>To Be Accessible:</strong></p> <ul> <li>A1 (meta)data are retrievable by their identifier using a standardized communications protocol.</li> <li>A1.1 the protocol is open, free, and universally implementable.</li> <li>A1.2 the protocol allows for an authentication and authorization procedure, where necessary.</li> <li>A2 metadata are accessible, even when the data are no longer available.</li> </ul> <p><strong>To Be Interoperable</strong></p> <ul> <li>I1. (meta)data use a formal, accessible, shared, and broadly applicable language for knowledge representation.</li> <li>I2. (meta)data use vocabularies that follow FAIR principles.</li> <li>I3. (meta)data include qualified references to other (meta)data.</li> </ul> <p><strong>To Be Reusable</strong></p> <ul> <li>R1. meta(data) have a plurality of accurate and relevant attributes.</li> <li>R1.1. (meta)data are released with a clear and accessible data usage license.</li> <li>R1.2. (meta)data are associated with their provenance.</li> <li>R1.3. (meta)data meet domain-relevant community standards. </li> </ul> <p><strong>Methodology</strong></p> <p>Based on the FAIR Data Principles, two questionnaires were created. The first (hereafter #Q1 - see Appendix #1) targeted repository managers and/or librarians and consisted of 40 questions. The second (hereafter #Q2 - see Appendix #2) targeted technical staff responsible for repository development and maintenance and consisted of 25 questions. </p> <p>Members of LIBER’s <a href="https://libereurope.eu/strategy/research-infrastructures/rdm/">Research Data Management (RDM) Working Group</a> circulated the questionnaires between December 2018 and February 2019. Responses were collected from managers and/or librarians of 29 repositories for the first (#Q1) questionnaire. </p> <p>In addition, technical staff responsible for the development and maintenance of 14 repositories (Table 1) responded to the second (#Q2) questionnaire. In 11 cases, repositories filled out both #Q1 and #Q2. </p> <p>In this report, the responses for both questionnaires have been merged and analyzed to gain a comprehensive picture about FAIRness at the level of repositories and their data.<br> </p>
Supplementary material 3 from: Groom Q, Desmet P, Reyserhove L, Adriaens T, Oldoni D, Vanderhoeven S, Baskauf SJ, Chapman A, McGeoch M, Walls R, Wieczorek J, Wilson JR.U, Zermoglio PFF, Simpson A (2019) Improving Darwin Core for research and management of alien species. Biodiversity Information Science and Standards 3: e38084. https://doi.org/10.3897/biss.3.38084
The Convention on Biological Diversity pathway vocabulary adapted from Harrower et al. 2017. Including proposed simple labels for these terms.
Supplementary material 1 from: Groom Q, Desmet P, Reyserhove L, Adriaens T, Oldoni D, Vanderhoeven S, Baskauf SJ, Chapman A, McGeoch M, Walls R, Wieczorek J, Wilson JR.U, Zermoglio PFF, Simpson A (2019) Improving Darwin Core for research and management of alien species. Biodiversity Information Science and Standards 3: e38084. https://doi.org/10.3897/biss.3.38084
Distinct values for dwc:establishmentMeans and their frequency from observations on the Global Biodiversity Information Facility on 27 February 2017. Taken from GitHub repository of the Darwin Core Questions & Answers Site (https://github.com/tdwg/dwc-qa/tree/master/data/GBIFDistinctValues).
Supplementary material 2 from: Groom Q, Desmet P, Reyserhove L, Adriaens T, Oldoni D, Vanderhoeven S, Baskauf SJ, Chapman A, McGeoch M, Walls R, Wieczorek J, Wilson JR.U, Zermoglio PFF, Simpson A (2019) Improving Darwin Core for research and management of alien species. Biodiversity Information Science and Standards 3: e38084. https://doi.org/10.3897/biss.3.38084
A tab-delimited file mapping values (synonyms; orthographic and language variations) found in Darwin Core dwc:establishmentMeans to a controlled vocabulary.
Demystifying Open Science and Research Data Management: A practical workshop for researchers
<p>Have you ever wondered why is everyone discussing about Open Science and Research Data Management (RDM) these days? Good Research Data Management (RDM) is crucial for reproducible and robust scientific research. Consequently, more and more funding bodies, governments, research institutions and other agencies have emphasised the value and importance of good data management and introduced policies on data management and sharing. However, it is easier said than done.<br> Like most researchers you might have more questions than answers about the topic. You are not alone! Come join us on the 24th at an interactive workshop where you can understand the why and how of open science and research data management in practical terms.</p> <p> </p> <p>This zenodo entry is a recording of the workshop described above. </p>
Committee For Research Management, Madan Bhandari Memorial College
<p>RMC Declaration for 2023 </p>
Childhood Asthma Research and Education (CARE) Network Trial - Acute Intervention Management Strategies (AIMS)
ClinicalTrials.gov study NCT00319488. IPD Sharing: Not stated. Countries: 1. Publications: 2.
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.