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Found 72 result(s)
The FAIRDOMHub is built upon the SEEK software suite, which is an open source web platform for sharing scientific research assets, processes and outcomes. FAIRDOM (Web Site) will establish a support and service network for European Systems Biology. It will serve projects in standardizing, managing and disseminating data and models in a FAIR manner: Findable, Accessible, Interoperable and Reusable. FAIRDOM is an initiative to develop a community, and establish an internationally sustained Data and Model Management service to the European Systems Biology community. FAIRDOM is a joint action of ERA-Net EraSysAPP and European Research Infrastructure ISBE.
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Macquarie University's Institutional Research Data Repository (RDR) allows researchers to upload, publish, search and download research data. The RDR promotes collaboration, data sharing and discovery amongst researchers globally according to FAIR data principles. The RDR is based on Figshare for Institutions, which has been specifically tailored to suit the needs of the Macquarie University research community.
Science Photo Library (SPL) provides creative professionals with striking specialist imagery, unrivalled in quality, accuracy and depth of information. We have more than 600,000 images and 40,000 clips to choose from, with hundreds of new submissions uploaded to the website each week.
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The Research Data Repository is a technological infrastructure that allows the preservation and access to research data produced at Universidad Andrés Bello (Chile). The repository complies with international standards for the deposit and access of data, highlighting the FAIR principles. These principles guarantee that the data will be Findable, Accessible, Interoperable and Reusable.
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.
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.
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TERN's AEKOS data portal is the original gateway to Australian ecology data. It is a ‘data and research methods’ data portal for Australia’s land-dwelling plants, animals and their environments. The primary focus of data content is raw co-located ‘species and environment’ ecological survey data that has been collected at the ‘plot’ level to describe biodiversity, its patterns and ecological processes. It is openly accessible with standard discovery metadata and user-oriented, contextual metadata critical for data reuse. Our services support the ecosystem science community, land managers and governments seeking to publish under COPE publishing ethics and the FAIR data publishing principles. AEKOS is registered with Thomson & Reuters Data Citation Index and is a recommended repository of Nature Publishing’s Scientific Data. There are currently 97,037 sites covering mostly plant biodiversity and co-located environmental data of Australia. The AEKOS initiative is supported by TERN (tern.org.au), hosted by The University of Adelaide and funded by the Australian Government’s National Research Infrastructure for Australia.
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In 2018, the Ministry of Higher Education, Research and Innovation has included in its roadmap the creation of a new infrastructure called the National Biodiversity Data Centre (PNDB). The PNDB's missions are part of a FAIR (Easy to Find, Accessible, Interoperable, Reusable) approach, and consist in - providing access to datasets and metadata, associated services and products derived from the analyses - promoting scientific leadership to identify gaps and foster the emergence of community-driven systems of users and producers - facilitate the sharing of practices with other research communities, encourage the sharing of data and their reuse, and be part of the reflection on the future Earth System infrastructure. - promote coherence with national, European and international efforts concerning access to and use of biodiversity research data and the promotion of products and services. The PNDB is supported by the Muséum national d'Histoire naturelle, more specifically by the UMS 2006 PatriNat, a MNHN CNRS and AFB unit. The project is closely linked with the FRB and several of its founding institutions (AFB, BRGM, CIRAD, CNRS, Ifremer, INERIS, INRA, IRD, IRSTEA, MNHN, Univ. Montpellier).
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.
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.
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DisGeNET is a discovery platform containing one of the largest publicly available collections of genes and variants associated to human diseases. DisGeNET integrates data from expert curated repositories, GWAS catalogues, animal models and the scientific literature. DisGeNET data are homogeneously annotated with controlled vocabularies and community-driven ontologies. Additionally, several original metrics are provided to assist the prioritization of genotype–phenotype relationships.
The online digital research data repository of multi-disciplinary research datasets produced at the University of Nottingham, hosted by Information Services and managed and curated by Libraries, Research & Learning Resources. University of Nottingham researchers who have produced research data associated with an existing or forthcoming publication, or which has potential use for other researchers, are invited to upload their dataset.
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Université Côte d'Azur has its own institutional space on the Entrepôt Recherche Data Gouv. This is a multidisciplinary dissemination space.
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KU Leuven RDR (pronounced "RaDaR") is KU Leuven's Research Data Repository, built on Dataverse.org - open source repository software built by Harvard University. RDR gives KU Leuven researchers a one-stop platform to upload, describe, and share their research data, conveniently and with support from university staff.
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The repository KITopen is a key infrastructure service at KIT. Immediately KITopen not only allows the publication and archiving of publications, but also on research data from all disciplines and data types. The focus is on research data from publication projects that are specifically prepared for re-use.
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Multidisciplinary research data repository, hosted by DTU, the Danish Technical University.
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.
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The Data Repository of the Department of Statistical Sciences of the University of Padova is a research data archive with the objective of sharing datasets collected within the Department. The service aims to facilitate data discovery, data sharing, and reuse.
Teesside University Research Data Repository links to the University's Research Portal and enables your datasets to be linked to your staff profile. It helps prevent data loss by storing it in a safe secure environment and enables your research data to be open access. https://researchdata.tees.ac.uk/about.