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15 results for “Digital repository”
A2.2a Digital repositories data citation practices. Supplementary material
<p>Data to complement the quantitative analysis of data citation practices in digital repositories based on metadata records from the re3data.org repositories registry.</p> <p>Data was retrieved using re3data.org API on 23-02-2023 and 06-03-2023 and processed using the OpenRefine software.</p> <p>Part of "A FAIR-enabling citation model for Cultural Heritage Objects" project activities.</p>
Questionnaire for the self-assessment of digital preservation activities in institutional research repositories
<p>This dataset includes a questionnaire designed to enable institutional repository managers to conduct a self-assessment of their digital preservation strategies and activities. It consists of 46 evaluation criteria extracted and modified from the NDSA Levels of Digital Preservation and ISO 16363:2017 standards. The questionnaire is provided in queXML format, facilitating its import into various survey applications</p> <p> </p>
Digital Repository of Ireland Member Digitisation Workflows for 2D Image Files: Survey Questions and Dataset
<p>The Digital Repository of Ireland (DRI) issued a survey to its membership, <strong>DRI Member Digitisation Workflows for 2D Images</strong>, which ran from December 7, 2023–January 31, 2024. The survey was conducted to improve the DRI’s understanding of the technical processes and metadata workflows that our members use to digitise and share images in the Repository, in order to better tailor our support for this work and deliver the most complete information about digital images files available to our users. </p> <p>The survey informed the actions taken in WorldFAIR Project WP13 deliverable <a href="https://doi.org/10.5281/zenodo.10850009" target="_blank" rel="noopener">13.3 Implementing and Testing the Cultural Heritage Image Sharing Recommendations: DRI Case Study Report</a>. The data will inform ongoing work at DRI aimed at improving the transparency of technical information associated with digital assets accessed through the Repository.</p> <p>Read more about the Cultural Heritage Image Sharing Case Study DRI on our website: <a href="https://dri.ie/the-worldfair-project/">https://dri.ie/the-worldfair-project/</a>. </p> <p>Summary: DRI is Ireland's national repository for the arts, humanities, and social sciences data, and operates on a membership scheme. There were 20 respondents to the survey, giving us a response rate of about 35% of DRI's membership. Representation from professional fields of work across the cultural heritage sector was captured in the results (note that some institutions gave multiple responses): 17 Archives, 12 Libraries, 5 Museums and 11 Higher Education Institutions. </p>
"Canvas BM" Digital Business Model Template Repository
<p>The Digital Business Model Template Repository consists of 265 unique one-page, diverse business model compositions, constructed as variants or adaptations based on the reference Business Model Canvas (BMC) created by A. Osterwalder. Business Model Canvases are templates composed of key blocks (elements) of the business model, which are interconnected and ready to be filled with content. The process of acquiring templates through quantitative, and then qualitative research, was conducted from November 2020 to October 2022. Each identified template was verified for compliance with licensing rights. The thematic repository should be treated as a business guide, aiding in the selection of suitable tools for designing business models for specific organizations, as well as in the process of creating, analyzing, and modifying business model templates. The Digital Business Model Template Repository can be useful in both a scientific, research, didactic, and individual context, and can also be beneficial in business practice.</p>
The Collection Management System Collection - Crowd-sourcing a list of digital repository options
<p><strong>The Collection Management System Collection - Crowd-sourcing a list of digital repository options</strong></p> <p>This dataset contains a list of digital repository options for collection management systems. It has been started and complited by Ashley Blewer.<br> The data set contains:</p> <ul> <li>a PDF capture of the blog describing motivation and background, columns of the spreadsheet and further resources; originally published at https://bits.ashleyblewer.com/blog/2017/08/09/collection-management-system-collection/</li> <li>The dataset / spreadsheet of The Collection Management System Collection, originally published at https://docs.google.com/spreadsheets/d/1cXOug3qM0pNNeD_wssiVEv9c0W1Y5I1VDTnSPTk7fb4/<br> The data was exported from the google spreadsheet on November 14th 2020 into the following formats: <ul> <li>PDF</li> <li>XLSX</li> <li>CSV</li> <li>TSV</li> </ul> </li> </ul> <p>The list contains basic information, administration considerations, interface considerations, technical considerations and social considerations for 70 different repository systems.</p>
Digital repository for: Large-scale forest disturbance and associated management shape bird communities in Central European spruce forests
<p>Repository containing R-script and data to reproduce analysis and main figures on the effect of large-scale forest disturbance and associated pre- and post-disturbance management on bird communities in the Harz Mountains, Germany.</p> <p>R-script includes:</p> <ul> <li>indicator species analysis (R package indicspecies; Cáceres & Legendre, 2009)</li> <li>non-metric multidimensional scaling (R package vegan; Oksanen et al., 2016)</li> <li>rarefaction- and extrapolation of Hill numbers (R package iNEXT; Hsieh et al., 2019)</li> <li>multi-species community distance sampling (R package sp Abundance; Doser et al., 2023)</li> </ul> <p>Attached files:</p> <ul> <li><strong>bird_data_Graser_et_al.csv </strong>(row data of bird species point counts per distance category)</li> <li><strong>bird_data_abundance_100_Graser_et_al.csv </strong>(abundance of species per sampling site, summed up over all four sampling repeats only considering detected individuals up to 100 m around the sampling point)</li> <li><strong>siteCovs_Graser_et_al.csv</strong> (environmental variables for each sampling point)</li> <li><strong>A_species_matrix_100_new_Graser_et_al.csv</strong> (species-site matrix of <strong>bark-beetle disturbance, unlogged </strong>sites for rarefaction and extrapolation, species number summed up over all four sampling repeats only considering detected individuals up to 100 m around the sampling point)</li> <li><strong>B_species_matrix_100_new_Graser_et_al.csv </strong>(species-site matrix of <strong>windthrow disturbance, unlogged </strong>sites for rarefaction and extrapolation, species number summed up over all four sampling repeats only considering detected individuals up to 100 m around the sampling point)</li> <li><strong>C_species_matrix_100_new_Graser_et_al.csv </strong>(species-site matrix of <strong>bark-beetle/windthrow disturbance, underplanted, unlogged </strong>sites for rarefaction and extrapolation, species number summed up over all four sampling repeats only considering detected individuals up to 100 m around the sampling point)</li> <li><strong>D_species_matrix_100_new_Graser_et_al.csv </strong>(species-site matrix of <strong>bark-beetle /windthrow disturbance, salvage-unlogged </strong>sites for rarefaction and extrapolation, species number summed up over all four sampling repeats only considering detected individuals up to 100 m around the sampling point)</li> <li><strong>E_species_matrix_100_new_Graser_et_al.csv </strong>(species-site matrix of <strong>bark-beetle /windthrow disturbance, underplanted, salvage-unlogged </strong>sites for rarefaction and extrapolation, summed up over all four sampling repeats only considering detected individuals up to 100 m around the sampling point)</li> <li><strong> F_species_matrix_100_new_Graser_et_al.cs</strong>v (species-site matrix of <strong>mature spruce plantation </strong>sites for rarefaction and extrapolation, species number summed up over all four sampling repeats only considering detected individuals up to 100 m around the sampling point)</li> <li><strong>msHDS_bird_data_management_model_Graser_et_al.rds</strong> (R-data set for multi-species community distance sampling of the effect of different pre- and post-disturbance management groups)</li> <li><strong>msHDS_bird_data_stand_age_model_Graser_et_al.rds </strong>(R-data set for multi-species community distance sampling of the effect of post-disturbance forest succession)</li> </ul> <p>A more detailed description of the data can be found in the README.txt document.</p> <p><span>References:</span></p> <p><span>Cáceres, M. D., & Legendre, P. (2009). </span><span>Associations between species and groups of sites: Indices and statistical inference. <em>Ecology</em>, <em>90</em>(12), 3566–3574. https://doi.org/10.1890/08-1823.1</span></p> <p><span>Doser, J. W., Finley, A. O., Kéry, M., & Zipkin, E. F. (2023). spAbundance: An R package for single‐species and multi‐species spatially explicit abundance models. <em>Methods in Ecology and Evolution</em>, <em>15</em>(6), 1024–1033. https://doi.org/10.1111/2041-210X.14332</span></p> <p><span>Hsieh, T. C., Ma, K. H., & Chao, A. (2019). <em>iNEXT-package: Interpolation and extrapolation for species diversity</em>. https://cran.r-project.org/web/packages/iNEXT/vignettes/Introduction.html</span></p> <p><span>Oksanen, J., Blanchet, F. G., Kindt, R., Legendre, P., O’hara, R. B., Simpson, G. L., Solymos, P., Stevens, M. H. H., Wagner, H., Minchin, P. R., Gavin, L., & Henry, H. (2016). Vegan: Community ecology package. R package version 1.17-4. <em>Http://CRAN. R-Project. </em></span><em><span>Org/Package=vegan</span></em><span>.</span></p> <p></p> <p></p>
Future-ready Nordic homes: Responding to the Changing Climate with Free-running Buildings; Digital Repository of Obtained Results
<p>The figures provided here show complete results of the parametric building performance simulation for each studied location, which was a part of the Master thesis in Energy-efficient and Environmental Building Design (Faculty of Engineering, Lund University, Sweden) by Marko Ljubas.</p> <p>The simulations were performed using software IDA ICE 4.8 by EQUA.</p> <p>The weather files were generated using software Meteonorm 8.2 by Meteotest.</p>
Prototyping 3D Virtual Learning Environments with X3D-based Content and Visualization Tools-Figure 11. Online accessible repository of digital data on cultural heritage with X3D models (STARC Web Repository, 2017, © Copyright 2017, STARC, Cyprus Institute. Used with permission)
<p>Prototyping can also include the development of toolkits for automatic content generation simulator, but in the case of an architectural environment, the components are too complex to be automatically generated. Furniture elements or the learning artifacts (i.e. content created by learners) can be converted to be viewed in X3D compatible browsers or included in online galleries (Figure 11). After functional and 3D content prototyping, certain components of the virtual campus can be easily modified and adapted as needed.</p>
Digital Radiology Case Repository
<p>Radiology case images( DICOM to picture formats eg JPEF,PNG,TIFF etc) with no patient related data or information.</p> <p>These pictures serve as the source for the digital online radiology case repository </p>
Repository for "Standardized classification of cerebral vasospasm after subarachnoid hemorrhage by digital subtraction angiography"
<p>Repositories for "Standardized classification of cerebral vasospasm after subarachnoid hemorrhage by digital subtraction angiography"</p> <p>Repository 1: Digital subtraction angiographies of CVS patients for grading with pM1 values</p> <p>Repository 2: Vessel values</p> <p>Repository 3: Clinical data of CVS patients</p>
Data from: Digitizing extant bat diversity: an open-access repository of 3D μCT-scanned skulls for research and education
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African Digital Research Repositories: Mapping the Landscape
<p>This data set accompanies the text at doi <a href="https://doi.org/10.5281/zenodo.3732273">10.5281/zenodo.3732273</a>. // Correspondence: JH: <a href="mailto:info@africarxiv.org">info@africarxiv.org</a>, SK: <a href="mailto:sk111@soas.ac.uk">sk111@soas.ac.uk</a></p> <p><strong>Visual Map: </strong><a href="https://kumu.io/access2perspectives/african-digital-research-repositories"><strong>https://kumu.io/access2perspectives/african-digital-research-repositories</strong></a><strong> <br> Dataset: </strong><a href="https://tinyurl.com/African-Research-Repositories"><strong>https://tinyurl.com/African-Research-Repositories</strong></a><br> <strong>Archived at </strong><a href="https://info.africarxiv.org/african-digital-research-repositories/"><strong>https://info.africarxiv.org/african-digital-research-repositories/</strong></a><strong> <br> Submission form: </strong><a href="https://forms.gle/CnyGPmBxN59nWVB38"><strong>https://forms.gle/CnyGPmBxN59nWVB38</strong></a></p> <p> </p> <p><strong>Licensing</strong>: Text and Visual Map – CC-BY-SA 4.0 // Dataset – CC0 (Public Domain) // The licensing of each database is determined by the database itself</p> <p>Preprint doi: <a href="https://doi.org/10.5281/zenodo.3732273">10.5281/zenodo.3732273</a>. <br> Data set doi: <a href="http://doi.org/10.5281/zenodo.3732172">10.5281/zenodo.3732172</a> // available in different formats (pdf, xls, ods, csv)</p> <p> </p> <p><strong><a href="https://info.africarxiv.org">AfricarXiv</a> in collaboration with the <a href="https://www.internationalafricaninstitute.org">International African Institute </a>(IAI) presents an interactive map of African digital research literature repositories. This drew from IAI’s earlier work from 2016 onwards to identify and list Africa-based institutional repositories that focused on identifying repositories based in African university libraries. Our earlier resources are available at </strong><a href="https://www.internationalafricaninstitute.org/repositories"><strong>https://www.internationalafricaninstitute.org/repositories</strong></a><strong>.</strong></p> <p><strong>The interactive map extends the work of the IAI to include organizational, governmental, and international repositories. It also maps the interactions between research repositories. In this dataset, we focus on institutional repositories for scholarly works, as defined by Wikipedia contributors (March 2020).</strong><br> </p> <p><strong>Objective</strong></p> <p>The map of African digital repositories was created as a resource to be used in activities addressing the following aims:</p> <ol> <li> <p>Improving the discoverability of African research and publications </p> </li> <li> <p>Enhance the interoperability of existing and emerging African repositories</p> </li> <li> <p>Identify ways through which digital scholarly search engines can enhance the discoverability of African research</p> </li> </ol> <p>We promote the dissemination of research-based knowledge from African repositories as part of a bigger landscape that also includes online journals, research data repositories, and scholarly publishers to enhance the interconnectivity and accessibility of such repositories across and beyond the African continent and to contribute to a more granular understanding of the continent’s scholarly resources. </p> <p> </p> <p><strong>Data archiving and maintenance</strong></p> <p>The map and corresponding dataset are hosted on the AfricArXiv website under ‘Resources’ at <a href="https://info.africarxiv.org/african-digital-research-repositories/">https://info.africarxiv.org/african-digital-research-repositories/</a>. The listing is not exhaustive and therefore we encourage any repositories relevant for the African continent not listed here to the <strong>submission form at </strong><a href="https://forms.gle/CnyGPmBxN59nWVB38"><strong>https://forms.gle/CnyGPmBxN59nWVB38</strong></a>, or to notify the International African Institute (email <a href="mailto:sk111@soas.ac.uk">sk111@soas.ac.uk</a>). Both AfricArXiv and IAI will continue to maintain the list of repositories as a resource for African researchers and other stakeholders including international African studies communities.</p>
Data from: The location of the citation: changing practices in how publications cite original data in the Dryad Digital Repository
While stakeholders in scholarly communication generally agree on the importance of data citation, there is not consensus on where those citations should be placed within the publication – particularly when the publication is citing original data. Recently, CrossRef and the Digital Curation Center (DCC) have recommended as a best practice that original data citations appear in the works cited sections of the article. In some fields, such as the life sciences, this contrasts with the common practice of only listing data identifier(s) within the article body (intratextually). We inquired whether data citation practice has been changing in light of the guidance from CrossRef and the DCC. We examined data citation practices from 2011 to 2014 in a corpus of 1,125 articles associated with original data in the Dryad Digital Repository. The percentage of articles that include no reference to the original data has declined each year, from 31% in 2011 to 15% in 2014. The percentage of articles that include data identifiers intratextually has grown from 69% to 83%, while the percentage that cite data in the works cited section has grown from 5% to 8%. If the proportions continue to grow at the current rate of 19-20% annually, the proportion of articles with data citations in the works cited section will not exceed 90% until 2030.
EIAH data model: semantic interoperability between distributed digital repositories
<p>The authors described their information architecture project aimed at improving access to the Encyclopaedia of Iranian architectural history (EIAH) by signalling relationships between concepts and between concepts and documents. The outcome will be presented in a semantic portal or might be used for complex search queries by end users.</p>
Data from: The location of the citation: changing practices in how publications cite original data in the Dryad Digital Repository
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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.