Filter
Reset all

Subjects

Content Types

Countries

AID systems

API

Certificates

Data access

Data access restrictions

Database access

Database licenses

Data licenses

Data upload

Data upload restrictions

Enhanced publication

Institution responsibility type

Institution type

Keywords

Metadata standards

PID systems

Provider types

Quality management

Repository languages

Software

Syndications

Repository types

Versioning

  • * at the end of a keyword allows wildcard searches
  • " quotes can be used for searching phrases
  • + represents an AND search (default)
  • | represents an OR search
  • - represents a NOT operation
  • ( and ) implies priority
  • ~N after a word specifies the desired edit distance (fuzziness)
  • ~N after a phrase specifies the desired slop amount
  • 1 (current)
Found 16 result(s)
The Duke Research Data Repository is a service of the Duke University Libraries that provides curation, access, and preservation of research data produced by the Duke community. Duke's RDR is a discipline agnostic institutional data repository that is intended to preserve and make public data related to the teaching and research mission of Duke University including data linked to a publication, research project, and/or class, as well as supplementary software code and documentation used to provide context for the data.
The Arizona State University (ASU) Research Data Repository provides a platform for ASU-affiliated researchers to share, preserve, cite, and make research data accessible and discoverable. The ASU Research Data Repository provides a permanent digital identifier for research data, which complies with data sharing policies. The repository is powered by the Dataverse open-source application, developed and used by Harvard University. Both the ASU Research Data Repository and the KEEP Institutional Repository are managed by the ASU Library to ensure research produced at Arizona State University is discoverable and accessible to the global community.
The WashU Research Data repository accepts any publishable research data set, including textual, tabular, geospatial, imagery, computer code, or 3D data files, from researchers affiliated with Washington University in St. Louis. Datasets include metadata and are curated and assigned a DOI to align with FAIR data principles.
The US BRAIN Initiative archive for publishing and sharing neurophysiology data including electrophysiology, optophysiology, and behavioral time-series, and images from immunostaining experiments.
Open Context is a free, open access resource for the electronic publication of primary field research from archaeology and related disciplines. It emerged as a means for scholars and students to easily find and reuse content created by others, which are key to advancing research and education. Open Context's technologies focus on ease of use, open licensing frameworks, informal data integration and, most importantly, data portability.Open Context currently publishes 132 projects.
UltraViolet is part of a suite of repositories at New York University that provide a home for research materials, operated as a partnership of the Division of Libraries and NYU IT's Research and Instruction Technology. UltraViolet provides faculty, students, and researchers within our university community with a place to deposit scholarly materials for open access and long-term preservation. UltraViolet also houses some NYU Libraries collections, including proprietary data collections.
SESAR, the System for Earth Sample Registration, is a global registry for specimens (rocks, sediments, minerals, fossils, fluids, gas) and related sampling features from our natural environment. SESAR's objective is to overcome the problem of ambiguous sample naming in the Earth Sciences. SESAR maintains a database of sample records that are contributed by its users. Each sample that is registered with SESAR is assigned an International Geo Sample Number IGSN to ensure its global unique identification.
The Pennsieve platform is a cloud-based scientific data management platform focused on integrating complex datasets, fostering collaboration and publishing scientific data according to all FAIR principles of data sharing. The platform is developed to enable individual labs, consortiums, or inter-institutional projects to manage, share and curate data in a secure cloud-based environment and to integrate complex metadata associated with scientific files into a high-quality interconnected data ecosystem. The platform is used as the backend for a number of public repositories including the NIH SPARC Portal and Pennsieve Discover repositories. It supports flexible metadata schemas and a large number of scientific file-formats and modalities.
TCIA is a service which de-identifies and hosts a large archive of medical images of cancer accessible for public download. The data are organized as “collections”; typically patients’ imaging related by a common disease (e.g. lung cancer), image modality or type (MRI, CT, digital histopathology, etc) or research focus. Supporting data related to the images such as patient outcomes, treatment details, genomics and expert analyses are also provided when available.
ReDATA is the research data repository for the University of Arizona and a sister repository to the UA Campus Repository (which is intended for document-based materials). The UA Research Data Repository (ReDATA) serves as the institutional repository for non-traditional scholarly outputs resulting from research activities by University of Arizona researchers. Depositing research materials (datasets, code, images, videos, etc.) associated with published articles and/or completed grants and research projects, into ReDATA helps UA researchers ensure compliance with funder and journal data sharing policies as well as University data retention policies. ReDATA is designed for materials intended for public availability.
The overall vision for the SPARC Portal is to accelerate autonomic neuroscience research and device development by providing access to digital resources that can be shared, cited, visualized, computed, and used for virtual experimentation.