This dataset aggregates information about 191 research data repositories that were shut down. The data collection was based on the registry of research data repositories re3data and a comprehensive content analysis of repository websites and related materials. Documented in the dataset are the period in which a repository was active, the risks resulting in its shutdown, and the repositories taking over custody of the data after.

A list of NIH-supported repositories that accept submissions of appropriate scientific research data from biomedical researchers. It includes resources that aggregate information about biomedical data and information sharing systems. Links are provided to information about submitting data to and accessing data from the listed repositories. Additional information about the repositories and points-of contact for further information or inquiries can be found on the websites of the individual repositories.

Inventory of Online Public Databases and Repositories Holding Agricultural Data in 2017

Metadata Updated: March 30, 2024

United States agricultural researchers have many options for making their data available online. This dataset aggregates the primary sources of ag-related data and determines where researchers are likely to deposit their agricultural data. These data serve as both a current landscape analysis and a baseline for future studies of ag research data.

Purpose As sources of agricultural data become more numerous and disparate, and collaboration and open data become more expected if not required, this research provides a landscape inventory of online sources of open agricultural data. An inventory of current agricultural data-sharing options will help assess how the Ag Data Commons, a platform for USDA-funded data cataloging and publication, can best support data-intensive and multidisciplinary research. It will also help agricultural librarians assist their researchers in data management and publication. The goals of this study were to:

• Establish where agricultural researchers in the United States—land grant and USDA researchers, primarily ARS, NRCS, USFS, and other agencies—currently publish their data, including general research data repositories, domain-specific databases, and the top journals.
• Compare how much data is in institutional vs. domain-specific vs. federal platforms.
• Determine which repositories are recommended by top journals that require or recommend the publication of supporting data.
• Ascertain where researchers not affiliated with funding or initiatives possessing a designated open data repository can publish data.

Approach The National Agricultural Library team focused on Agricultural Research Service (ARS), Natural Resources Conservation Service (NRCS), and United States Forest Service (USFS) style research data, rather than ag economics, statistics, and social sciences data. To find domain-specific, general, institutional, and federal agency repositories and databases that are open to US research submissions and have some amount of ag data, resources including re3data, libguides, and ARS lists were analyzed. Primarily environmental or public health databases were not included, but places where ag grantees would publish data were considered.

Search Methods - We first compiled a list of known domain-specific USDA/ARS datasets/databases represented in the Ag Data Commons, including ARS Image Gallery, ARS Nutrition Databases (sub-components), SoyBase, PeanutBase, National Fungus Collection, i5K Workspace @ NAL, and GRIN. - We then searched using search engines such as Bing and Google for non-USDA/federal ag databases, using Boolean variations of “agricultural data” /“ag data” / “scientific data” + NOT + USDA (to filter out the federal/USDA results). Most of these results were domain-specific, though some contained a mix of data subjects. - We searched using search engines such as Bing and Google to find top agricultural university repositories using variations of “agriculture”, “ag data” and “university” to find schools with agriculture programs. Using that list of universities, we searched each university website to see if their institution had a repository for their unique, independent research data if not apparent in the initial web browser search. - We found both ag-specific university repositories and general university repositories that housed a portion of agricultural data. Ag-specific university repositories are included in the list of domain-specific repositories. Results included Columbia University – International Research Institute for Climate and Society, UC Davis – Cover Crops Database, etc. If a general university repository existed, we determined whether that repository could filter to include only data results after our chosen ag search terms were applied. General university databases that contain ag data included Colorado State University Digital Collections, University of Michigan ICPSR (Inter-university Consortium for Political and Social Research), and University of Minnesota DRUM (Digital Repository of the University of Minnesota). - We then split out NCBI (National Center for Biotechnology Information) repositories. - Next, we searched the internet for open general data repositories using a variety of search engines, and repositories containing a mix of data, journals, books, and other types of records were tested to determine whether that repository could filter for data results after search terms were applied. General subject data repositories include Figshare, Open Science Framework, PANGEA, Protein Data Bank, and Zenodo. - Finally, we compared scholarly journal suggestions for data repositories against our list to fill in any missing repositories that might contain agricultural data. Extensive lists of journals were compi...

Data collected from major Canadian and international research data repositories cover data storage, preservation, metadata, interchange, data file types, and other standard features used in the retention and sharing of research data. The outputs of this project primarily aim to assist in the establishment of recommended minimum requirements for a Canadian research data infrastructure. The committee also aims to further develop guidelines and criteria for the assessment and selection o f repositories for deposit of Canadian research data by researchers, data managers, librarians, archivists etc.

This file collection is part of the ORD Landscape and Cost Analysis Project (DOI: 10.5281/zenodo.2643460), a study jointly commissioned by the SNSF and swissuniversities in 2018.

Please cite this data collection as: von der Heyde, M. (2019). Data and tools of the landscape and cost analysis of data repositories currently used by the Swiss research community. Retrieved from https://doi.org/10.5281/zenodo.2643495

Connected data papers are: von der Heyde, M. (2019). Open Data Landscape: Repository Usage of the Swiss Research Community: Description of collection, collected data, and analysis methods [Data paper]. Retrieved from https://doi.org/10.5281/zenodo.2643430 von der Heyde, M. (2019). International Open Data Repository Survey: Description of collection, collected data, and analysis methods [Data paper]. Retrieved from https://doi.org/10.5281/zenodo.2643450

Connected data sets are: von der Heyde, M. (2019). Data from the Swiss Open Data Repository Landscape survey. Retrieved from https://doi.org/10.5281/zenodo.2643487 von der Heyde, M. (2019). Data from the International Open Data Repository Survey. Retrieved from https://doi.org/10.5281/zenodo.2643493

Contact

Swiss National Science Foundation (SNSF)

Open Research Data Group

E-mail: ord@snf.ch

swissuniversities

Program "Scientific Information"

Gabi Schneider

E-Mail: isci@swissuniversities.ch

Combined Survey ResponsesThis spreadsheet shows the combined survey responses from Dryad Digital Repository, Figshare and TreeBASE survey populations.combined_survey_responses.csv

About

This dataset lists over 215k top projects by star with over 167 stars. Contains a lot of useful information (attributes).

I collected this dataset using github search api. This allows you to get only the first thousand for a query, so I looped through the low/high (stars) pairs that return less than a thousand repositories when query=stars:{low}..{high}.

The Github API Terms of Service apply.

You may not use this dataset for spamming purposes, including for the purposes of selling GitHub users' personal information, such as to recruiters, headhunters, and job boards.

Columns

This document describes data collected from the Main Collection of the Web of Science database. Records of published studies addressing the intersection of Open Science and data repository were searched up to January 15th, 2024, and the final dataset was comprised of 545 records for bibliometric analysis.

This dataset provides guidance materials and templates to help you prepare your research datasets for deposit in the U of G Research Data Repositories.Please refer to the U of G Research Data Repositories LibGuide for detailed information about the U of G Research Data Repositories including additional resources for preparing datasets for deposit. The library offers a self-deposit with curation service. The deposit workflow is as follows:Create your repository account.If you are a first-time depositor, complete the U of G Research Data Repositories New Depositor Intake Form.Activate your Data Repositories account by logging in with your U of G username and password.Once your account is created, contact us to set up your dataset creator access to your home department’s collection in the Data Repositories.Note: If you already have a Data Repositories account and dataset creator access, you can log in and begin a new deposit to your home department’s collection right away.Prepare your dataset.Assemble your dataset following the Dataset Deposit Guidelines. Use the README file template to capture data documentation.Create a draft dataset record.Log in to the Data Repositories and create a draft dataset record following the instructions in the Dataset Submission Guide.Submit your draft dataset for review.Dataset review.Data Repositories staff will review (also referred to as curate) your dataset for alignment with the Dataset Deposit Guidelines using a standard curation workflow.The curator will collaborate with you to enhance the dataset.Public release.Once ready, the dataset curator will make the dataset publicly available in the Data Repositories, with appropriate file access controls. Support: If you have any questions about preparing and depositing your dataset, please make a Publishing and Author Support Request.

The Administrative Data Repository (ADR) was established to provide support for the administrative data elements relative to multiple categories of a person entity such as demographic and eligibility information. Although initially focused on the computing needs of the Veterans Health Administration, the ADR is positioned to provide identity management and demographics support for all IT systems within the Department of Veterans Affairs.

The attached data sets provides an overview of the landscape of research data repositories in 2015. They are based on an analysis of the re3data - registry of research data repositories from December 2015.

Use of a persistent identifier for access to journal articles (the DOI) is now almost universal amongst researchers. It directs to the journal landing page where the human has to then take over navigation (or payment). Recently, the deposition of data into open access repositories and the resulting assignment of a data-DOI to the data or fileset has started to be increasingly adopted, and in the near future probably mandated by funders. Unfortunately, mechanisms for the retrieval and application of the data from such sources are still inherited from those developed for journal articles. We argue these mechanisms are not fit for (data) purpose. In these three demonstrations, we show how existing standards can be used to automate the data retrieval process, starting purely from the DOI assigned to the objects. The first of these utilises the 10320/loc method (see doi:10.1021/ci500302p) which is flexible and efficient, but is not supported by the DataCite registry. The next two schemes were developed to achieve such interoperability, the first using the DataCite Media API and the second exploiting added metadata such as relatedMetadataScheme = ORE to use the repository ORE resource map. We have embedded these methods into a Javascript-based data viewing demonstrator (JSmol), which is designed to display molecular information. Handlers for other types of data could be readily incorporated, and the system could also be exploited for data-mining. Examples of recently published journal articles which use such data-DOI handling will be cited.

Our dataset "repository_survey" summarizes a comprehensive survey of over 150 data repositories, characterizing their metadata documentation and standardization, data curation and validation, and tracking of dataset use in the literature. In addition, "survey_model_evaluation" includes our findings on model evaluation for five methodological repositories. Column descriptions and further details can be found in "README.pdf." The data are associated with our paper "Towards an Ideal Methodological Data Repository: Lessons and Recommendations."

This dataset contains 189 survey responses from a respository/ data managers' survey where we explored the current status, needs and challenges of research data repositories.

In the modern era, the near impossibility of true anonymization means we must provide tangible recommendations for researchers who need to share de-identified, person-level data that could potentially be re-identified due to the presence of quasi-identifiers. While various repository aggregators like Re3data and DataCite Repository Finder provide lists of data repositories, navigating these can be cumbersome when trying to locate options for depositing restricted data. These listings rarely include certain necessary details, making the process of recommending third-party repositories to researchers time-consuming – or even limited, and we often end up relying on a short list of well-known repositories. An additional challenge is the difficulty of identifying repositories that mediate access via data usage agreements, where the repository handles access requests to ensure potential users meet established security and privacy requirements and have taken the necessary steps to protect confidentiality and commit to appropriate data use. As part of a capstone project for the Data Services Continuing Education Program, we identified and created a spreadsheet of restricted data repositories with mediated access processes for researchers. While our project scope was limited to the social sciences and US based repositories, in sharing this work, we hope others will continue to contribute to this work and expand on it.

ADR provides an authoritative data store for shared administrative, demographic, enrollment, and eligibility information which is managed as a corporate asset. This administrative database system offers mission-critical database support for all VA Medical 21st Century Core applications such as Enrollment Systems, Identity Management System, Community Care Program, Veterans's Choice program, President's Affordable Care Act project, Patient Advocacy Tracking System, Veterans 360, and others.

Availability of data, code, and plot creation for various figures throughout my PhD thesis. Rough organisation currently. Pertains to Figures 5.4, 5.8, 6.11, 6.18, 7.3, 7.12, and Table 6.1.

The goal of BioLINCC is to facilitate and coordinate the existing activities of the NHLBI Biorepository and the Data Repository and to expand their scope and usability to the scientific community through a single web-based user interface.

QUT Research Data Respository Dataset Resource available for download

This file collection is part of the ORD Landscape and Cost Analysis Project (DOI: 10.5281/zenodo.2643460), a study jointly commissioned by the SNSF and swissuniversities in 2018.

Please cite this data collection as: von der Heyde, M. (2019). Data from the International Open Data Repository Survey. Retrieved from https://doi.org/10.5281/zenodo.2643493

Further information is given in the corresponding data paper: von der Heyde, M. (2019). International Open Data Repository Survey: Description of collection, collected data, and analysis methods [Data paper]. Retrieved from https://doi.org/10.5281/zenodo.2643450

Contact

Swiss National Science Foundation (SNSF)

Open Research Data Group

E-mail: ord@snf.ch

swissuniversities

Program "Scientific Information"

Gabi Schneider

E-Mail: isci@swissuniversities.ch