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Found 81 result(s)
The Society of American Archivists (SAA) Dataverse is an SAA data service that was established to support the needs and interests of SAA’s members and the broader archives community. The SAA Dataverse supports the reuse of datasets for purposes of fostering knowledge, insights, and a deeper understanding of archival organizations, the status of archivists, and the impact of archives and archival work on the broader society. Deposited datasets should be “actionable” in that they should support direct analysis and interpretation. The SAA Dataverse welcomes deposits of collections of quantitative or qualitative data and associated documentation. SAA membership is not required to deposit or use data in the SAA Dataverse.
Data products developed and distributed by the National Institute of Standards and Technology span multiple disciplines of research and are widely used in research and development programs by industry and academia. NIST's publicly available data sets showcase its committment to providing accurate, well-curated measurements of physical properties, exemplified by the Standard Reference Data program, as well as its committment to advancing basic research. In accordance with U.S. Government Open Data Policy and the NIST Plan for providing public access to the results of federally funded research data, NIST maintains a publicly accessible listing of available data, the NIST Public Dataset List (json). Additionally, these data are assigned a Digital Object Identifier (DOI) to increase the discovery and access to research output; these DOIs are registered with DataCite and provide globally unique persistent identifiers. The NIST Science Data Portal provides a user-friendly discovery and exploration tool for publically available datasets at NIST. This portal is designed and developed with data.gov Project Open Data standards and principles. The portal software is hosted in the usnistgov github repository.
ODC-TBI is a community platform to Share Data, Publish Data with a DOI, and get Citations. Advancing Traumatic Brain Injury research through sharing of data from basic and clinical research.
Sharing and preserving data are central to protecting the integrity of science. DataHub, a Research Computing endeavor, provides tools and services to meet scientific data challenges at Pacific Northwest National Laboratory (PNNL). DataHub helps researchers address the full data life cycle for their institutional projects and provides a path to creating findable, accessible, interoperable, and reusable (FAIR) data products. Although open science data is a crucial focus of DataHub’s core services, we are interested in working with evidence-based data throughout the PNNL research community.
Reference anatomies of the brain and corresponding atlases play a central role in experimental neuroimaging workflows and are the foundation for reporting standardized results. The choice of such references —i.e., templates— and atlases is one relevant source of methodological variability across studies, which has recently been brought to attention as an important challenge to reproducibility in neuroscience. TemplateFlow is a publicly available framework for human and nonhuman brain models. The framework combines an open database with software for access, management, and vetting, allowing scientists to distribute their resources under FAIR —findable, accessible, interoperable, reusable— principles. TemplateFlow supports a multifaceted insight into brains across species, and enables multiverse analyses testing whether results generalize across standard references, scales, and in the long term, species, thereby contributing to increasing the reliability of neuroimaging results.
The ColabFit Exchange is an online resource for the discovery, exploration and submission of datasets for data-driven interatomic potential (DDIP) development for materials science and chemistry applications. ColabFit's goal is to increase the Findability, Accessibility, Interoperability, and Reusability (FAIR) of DDIP data by providing convenient access to well-curated and standardized first-principles and experimental datasets. Content on the ColabFit Exchange is open source and freely available.
The UA Campus Repository is an institutional repository that facilitates access to the research, creative works, publications and teaching materials of the University by collecting, sharing and archiving content selected and deposited by faculty, researchers, staff and affiliated contributors.
The Johns Hopkins Research Data Repository is an open access repository for Johns Hopkins University researchers to share their research data. The Repository is administered by professional curators at JHU Data Services, who will work with depositors to enable future discovery and reuse of your data, and ensure your data is Findable, Accessible, Interoperable and Reusable (FAIR). More information about the benefits of archiving data can be found here: https://dataservices.library.jhu.edu/
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.
Content type(s)
NCI Imaging Data Commons (IDC) is a cloud-based repository of publicly available cancer imaging data co-located with the analysis and exploration tools and resources. IDC is a node within the broader NCI Cancer Research Data Commons (CRDC) infrastructure that provides secure access to a large, comprehensive, and expanding collection of cancer research data.
The long-term vision of the NMDC is to support microbiome data exploration through a sustainable data discovery platform that promotes open science and shared-ownership across a broad and diverse community of researchers, funders, publishers, and societies. The NMDC is developing a distributed data infrastructure while engaging with the research community to enable multidisciplinary and FAIR microbiome data.
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.
AceView provides a curated, comprehensive and non-redundant sequence representation of all public mRNA sequences (mRNAs from GenBank or RefSeq, and single pass cDNA sequences from dbEST and Trace). These experimental cDNA sequences are first co-aligned on the genome then clustered into a minimal number of alternative transcript variants and grouped into genes. Using exhaustively and with high quality standards the available cDNA sequences evidences the beauty and complexity of mammals’ transcriptome, and the relative simplicity of the nematode and plant transcriptomes. Genes are classified according to their inferred coding potential; many presumably non-coding genes are discovered. Genes are named by Entrez Gene names when available, else by AceView gene names, stable from release to release. Alternative features (promoters, introns and exons, polyadenylation signals) and coding potential, including motifs, domains, and homologies are annotated in depth; tissues where expression has been observed are listed in order of representation; diseases, phenotypes, pathways, functions, localization or interactions are annotated by mining selected sources, in particular PubMed, GAD and Entrez Gene, and also by performing manual annotation, especially in the worm. In this way, both the anatomy and physiology of the experimentally cDNA supported human, mouse and nematode genes are thoroughly annotated.
CESM is a fully-coupled, community, global climate model that provides state-of-the-art computer simulations of the Earth's past, present, and future climate states.
Content type(s)
CUGIR is an active online repository in the National Spatial Data Clearinghouse program. CUGIR provides geospatial data and metadata for New York State, with special emphasis on those natural features relevant to agriculture, ecology, natural resources, and human-environment interactions. In order to provide the best possible access to geospatial data for New York State, CUGIR coordinates its activities with those of the New York State GIS Clearinghouse
The International Satellite Cloud Climatology Project (ISCCP) is a database of intended for researchers to share information about cloud radiative properties. The data sets focus on the effects of clouds on the climate, the radiation budget, and the long-term hydrologic cycle. Within the data sets the data entries are broken down into entries of specific characteristics based on temporal resolution, spatial resolution, or temporal coverage.
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.
Smithsonian figshare is best for sharing data that need a DOI including those that underlie peer-reviewed publications; bounded datasets of mixed formats; or data that is periodically updated and needs to be versioned. See the Figshare Confluence site for more information.
Welcome to Smithsonian Open Access, where you can download, share, and reuse millions of the Smithsonian’s images—right now, without asking. With new platforms and tools, you have easier access to nearly 3 million 2D and 3D digital items from our collections—with many more to come. This includes images and data from across the Smithsonian’s 19 museums, nine research centers, libraries, archives, and the National Zoo.
MICASE provides a collection of transcripts of academic speech events recorded at the University of Michigan. The original DAT audiotapes are held in the English Language Institute and may be consulted by bona fide researchers under special arrangements. Additional access: https://lsa.umich.edu/eli/language-resources/micase-micusp.html
The Maine Dataverse Network is a cloud-based data repository intended to act as a long-term archive and to facilitate data sharing among the research community in accordance with NSF, NIH, NASA and other granting authority data management plan requirements. The Maine Dataverse Network offers a convenient and secure method of sharing and archiving data and is made available to the Maine research community at no cost.